Plotting coverage in sub windows pfhrp3 deletion

Setup

Downloads

meta.tab.txt metaByBioSample real_mccoil_COI_calls.tsv allBasicInfo_filt_sp_mat.Rdata rowAnnoColors.Rdata allCov_summaryStats.tab.txt.gz

Code

meta = readr::read_tsv("../meta/metadata/meta.tab.txt") %>% 
  mutate(country = gsub("South East Asia - East", "Cambodia", country))
metaByBioSample = readr::read_tsv("../meta/metadata/metaByBioSample.tab.txt") %>% 
  mutate(country = gsub("South East Asia - East", "Cambodia", country))
realmccoilCoiCalls = readr::read_tsv("wgs_variants/THEREALMcCOIL/categorical_method/real_mccoil_COI_calls.tsv")

realmccoilCoiCalls_poly = realmccoilCoiCalls %>% 
  filter(random_median != 1 | topHE_median != 1)


allMetaDeletionCalls = readr::read_tsv("allMetaDeletionCalls.tab.txt") %>% 
  filter(BiologicalSample %!in% realmccoilCoiCalls_poly$BiologicalSample)


hrp3Pat2_samplesWithTare1 = readr::read_tsv("deletion_patterns/hrp3Pat2_samplesWithTare1.tsv")

# char11 tare1 
chr11_tare_calls = readr::read_tsv("deletion_patterns/finalHRPII_HRPIII_windows_investTelemeraseHealing_chr11_full_out_step50_windowSize100_rowAnno.tsv")
chr11_tare_calls_hasTare1 = chr11_tare_calls %>% 
  filter(`TARE1 On Chr11`)

# these are only pattern 2 aka chr11/chr13-
stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta = readr::read_tsv("deletion_patterns/stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta.tsv")

stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta = stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta %>% 
  mutate(Pattern = case_when(
    `TARE1 On Chr5` | `Transposition With Chr5` ~ "13-5++",
    `TARE1 On Chr13` ~ "13-TARE1",
    T ~ NA
  ))
    # mutate(Pattern = case_when(
  #   `TARE1 On Chr5` | `Transposition With Chr5` ~ "5++/13-", 
  #   `TARE1 On Chr13` ~ "11/13-TARE1", 
  #   T ~ NA
  # ))

allMetaDeletionCalls_chr11_deleted = allMetaDeletionCalls %>% 
  filter(possiblyChr11Deleted)%>% 
  left_join(stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta %>% 
              select(sample, Pattern)) %>% 
  mutate(Pattern = ifelse(HRP3_deletionPattern == "Pattern 1", "13-11++", Pattern))%>%
  mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1", Pattern))
  # mutate(Pattern = ifelse(HRP3_deletionPattern == "Pattern 1", "11++/13-", Pattern))%>% 
  # mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1/13", Pattern))

allMetaDeletionCalls_hrp2_deleted = allMetaDeletionCalls %>% 
  filter(possiblyHRP2Deleted)%>% 
  left_join(stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta %>% 
              select(sample, Pattern)) %>% 
  mutate(Pattern = ifelse(HRP3_deletionPattern == "Pattern 1", "13-11++", Pattern))%>%
  mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1", Pattern))
  # mutate(Pattern = ifelse(HRP3_deletionPattern == "Pattern 1", "11++/13-", Pattern))%>% 
  # mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1/13", Pattern))

allMetaDeletionCalls_hrp3_deleted = allMetaDeletionCalls %>% 
  filter(possiblyHRP3Deleted)%>% 
  left_join(stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta %>% 
              select(sample, Pattern)) %>% 
  mutate(Pattern = ifelse(HRP3_deletionPattern == "Pattern 1", "13-11++", Pattern))%>%
  mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1", Pattern)) %>% 
  # mutate(Pattern = ifelse(HRP3_deletionPattern == "Pattern 1", "11++/13-", Pattern)) %>% 
  # mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1/13", Pattern)) %>% 
  mutate(Pattern = ifelse(is.na(Pattern), "13-", Pattern)) 
  


  #mutate(Pattern = factor(Pattern, levels = c("13-11++", "13-5++", "13-TARE1", "13-"))) %>%

Code

load("allBasicInfo_filt_sp_mat.Rdata")
load("rowAnnoColors.Rdata")

Sample Meta data

Code

cov = readr::read_tsv("../meta/allCov_summaryStats.tab.txt.gz")
meta = readr::read_tsv("../meta/metadata/meta.tab.txt")
masterTable = readr::read_tsv("../meta/metadata/masterTable.tab.txt") 
coveredSamples = readr::read_tsv("samplesCovered.txt", col_names = "sample") %>% 
  left_join(meta %>% 
              select(sample, ExperimentSample, BiologicalSample))

# chr07_dup_samplesCovered = readr::read_tsv("rRNA_chr05_chr07/samplesCovered.txt", col_names = c("sample"))

# chr07_dup = readr::read_tsv("rRNA_chr05_chr07/possible_chrom5_deletion_samples.txt", col_names = c("sample")) %>% 
#   left_join(cov %>% 
#               select(sample, meanPerBaseCov)) %>% 
#   left_join(masterTable)%>% 
#   mutate(chr05chr07rRNAPattern = "05-/07++") 



deletionCalls = allMetaDeletionCalls %>% 
  select(-HRP3_deletionPattern) %>% 
  left_join(allMetaDeletionCalls_hrp3_deleted %>% 
              ungroup() %>% 
              select(sample, Pattern))   %>% 
  mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1", Pattern)) %>% 
  # mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1/13", Pattern)) %>% 
  left_join(cov %>% 
              select(sample, meanPerBaseCov)) 
# %>% 
#   full_join(chr07_dup)

meta_allOthers = meta %>% 
  filter(BiologicalSample %!in% deletionCalls$BiologicalSample)%>% 
  left_join(cov %>% 
              select(sample, meanPerBaseCov)) %>% 
  left_join(masterTable %>% 
              select(sample, SRARuns))%>%
  filter(PreferredSample) %>% 
  select(-sample, -ExperimentSample,-PreferredSample) %>%
  rename(sample = BiologicalSample) %>% 
  filter(!is.na(SRARuns))


meta_withDeletionMetaOutput = bind_rows(
  deletionCalls %>% 
  select(-sample, -ExperimentSample,-PreferredSample) %>%
  rename(sample = BiologicalSample) , 
  meta_allOthers
) %>% 
  mutate(uncallable = sample %!in% coveredSamples$BiologicalSample) %>% 
  rename(HRP2Call = possiblyHRP2Deleted, 
         HRP3Call = possiblyHRP3Deleted, 
         HRPsCall = hrpCall, 
         Chr11TelemericCall = possiblyChr11Deleted) %>% 
  mutate(HRP2Call = case_when(uncallable ~ "uncallable", 
                              is.na(HRP2Call) ~ "present", 
                              !is.na(HRP2Call) & HRP2Call ~ "deletion", 
                              T ~ "present"), 
         HRP3Call = case_when(uncallable ~ "uncallable", 
                              is.na(HRP3Call) ~ "present", 
                              !is.na(HRP3Call) & HRP3Call ~ "deletion", 
                              T ~ "present"), 
         HRPsCall = case_when(uncallable ~ "uncallable",
                              is.na(HRPsCall) ~ "pfhrp2+/pfhrp3+",
                              T ~ HRPsCall), 
         Chr11TelemericCall = case_when(uncallable ~ "uncallable",
                                        Chr11TelemericCall ~ "deletion",
                                        is.na(Chr11TelemericCall) ~ "present", 
                                        T ~ "uncallable"
                                        )
         )

# %>% 
#   mutate(chr05chr07rRNAPattern = case_when(sample %in% chr07_dup$sample ~ "05-/07++", 
#                                            sample %in% chr07_dup_samplesCovered$sample ~ "05/07", 
#                                            T ~ "uncallable")) 


masterTable_withDeletionMetaOutput_fieldSamples_labIsolates = meta_withDeletionMetaOutput %>% filter(IsFieldSample | site == "LabIsolate")

create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates)

Code

write_tsv(meta_withDeletionMetaOutput, "sample_metadata_withAllDeletionCalls.tsv")
write_tsv(meta_withDeletionMetaOutput, "Supplemental Table - sample metadata.tsv")
write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates, "Supplemental Table - sample metadata - field samples and Lab Isolates.tsv")

sample_metadata_withAllDeletionCalls.tsv

Deletion Counts

Continent

HRP2

Code

masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp2 = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>% 
  filter(HRP2Call == "deletion") %>% 
  group_by(secondaryRegion) %>% 
  rename(continent = secondaryRegion) %>% 
  count() %>% 
  group_by() %>% 
  mutate(total = sum(n))%>% 
  mutate(percentage = n * 100/total)

write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp2, "hrp2_continent_deletion_counts.tsv")
create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp2)

hrp2_continent_deletion_counts.tsv

HRP3

Code

masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3 = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>% 
  filter(HRP3Call == "deletion") %>% 
  group_by(secondaryRegion) %>% 
  rename(continent = secondaryRegion) %>% 
  count() %>% 
  group_by() %>% 
  mutate(total = sum(n)) %>% 
  mutate(percentage = n * 100/total)

write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3, "hrp3_continent_deletion_counts.tsv")
create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3)

hrp3_continent_deletion_counts.tsv

HRP3 Pattern

Code

masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3_pattern = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>% 
  filter(HRP3Call == "deletion") %>% 
  group_by(secondaryRegion, Pattern) %>% 
  rename(continent = secondaryRegion) %>% 
  count() %>% 
  group_by(Pattern) %>% 
  mutate(PatternTotal = sum(n, na.rm = T)) %>% 
  mutate(PatternPercentage = n * 100/PatternTotal) %>% 
  group_by(continent) %>% 
  mutate(continentTotal = sum(n)) %>% 
  mutate(continentPercentage = n * 100/continentTotal) %>% 
  group_by() %>% 
  mutate(total = sum(n)) %>% 
  mutate(percentage = n * 100/total)

write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3_pattern, "hrp3_pattern_continent_deletion_counts.tsv")
create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3_pattern)

hrp3_pattern_continent_deletion_counts.tsv

Code

masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3_pattern_raw = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>% 
  filter(HRP3Call == "deletion") %>% 
  group_by(Pattern) %>% 
  count() %>% 
  group_by() %>% 
  mutate(PatternTotal = sum(n, na.rm = T)) %>% 
  mutate(percentage = n * 100/PatternTotal)

write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3_pattern_raw, "hrp3_pattern_deletion_counts.tsv")
create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3_pattern_raw)

hrp3_pattern_continent_deletion_counts.tsv

HRP2 and HRP3

Code

masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp2_and_hrp3 = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>% 
  filter(HRP2Call == "deletion" & HRP3Call == "deletion") %>% 
  group_by(secondaryRegion, Pattern) %>% 
  rename(continent = secondaryRegion) %>% 
  count() %>% 
  group_by() %>% 
  mutate(total = sum(n)) %>% 
  mutate(percentage = n * 100/total)

write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp2_and_hrp3, "hrp2_and_hrp3_continent_deletion_counts.tsv")
create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp2_and_hrp3)

hrp2_and_hrp3_continent_deletion_counts.tsv

Chr11 Deletion

Code

masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_chr11 = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>%
  filter(Chr11TelemericCall == "deletion") %>%
  group_by(secondaryRegion) %>%
  rename(continent = secondaryRegion) %>%
  count() %>%
  group_by() %>%
  mutate(total = sum(n)) %>%
  mutate(percentage = n * 100 / total)

write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_chr11, "chr11_continent_deletion_counts.tsv")
create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_chr11)

chr11_continent_deletion_counts.tsv

HRP Calls

Code

masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrpCalls = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>%
  group_by(HRPsCall) %>%
  count() %>%
  group_by() %>%
  mutate(total = sum(n)) %>%
  mutate(percentage = n * 100 / total)

write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrpCalls, "hrpCalls_deletion_counts.tsv")
create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrpCalls)

hrpCalls_deletion_counts.tsv

Pattern

Code

masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_pattern = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>%
  group_by(Pattern) %>%
  count() %>%
  group_by() %>%
  mutate(total = sum(n)) %>%
  mutate(percentage = n * 100 / total)

write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_pattern, "pattern_counts.tsv")
create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_pattern)

pattern_counts.tsv

Plotting Coverage

Coverage of genomic regions invovled in pfhrp3 deletions of samples with pfhrp3 deletions

Displaying from Pf3D7 genomic version=2015-06-18 of the following chromosome regions

chromosome 05: 944389 - 988747 944kb:988kb
chromosome 11: 1897157 - 2003328 1,897kb:2,003kb
chromosome 13: 2769916 - 2844777 2,769kb:2,844kb

Code

allBasicInfo_filt_sp_mat_hrp3_deleted = allBasicInfo_filt_sp_mat[rownames(allBasicInfo_filt_sp_mat) %in% allMetaDeletionCalls_hrp3_deleted$sample, ]
metaSelected_hrp3_deleted = allMetaDeletionCalls_hrp3_deleted[match(rownames(allBasicInfo_filt_sp_mat_hrp3_deleted), allMetaDeletionCalls_hrp3_deleted$sample), ]
allBasicInfo_filt_sp_mat_hrp3_deleted_hclust = hclust(dist(allBasicInfo_filt_sp_mat_hrp3_deleted))

allBasicInfo_filt_sp_mat_hrp3_deleted_hclust_ordering = tibble(
  sample = rownames(allBasicInfo_filt_sp_mat_hrp3_deleted)[allBasicInfo_filt_sp_mat_hrp3_deleted_hclust$order], 
  hclustInputOrder = allBasicInfo_filt_sp_mat_hrp3_deleted_hclust$order, 
  hclustOutputOrder = 1:nrow(allBasicInfo_filt_sp_mat_hrp3_deleted)
)

rowAnnoDf_hrp3_deleted  = metaSelected_hrp3_deleted %>%
  left_join(allBasicInfo_filt_sp_mat_hrp3_deleted_hclust_ordering) %>%
  select("Pattern", "secondaryRegion", "hrpCall", hclustOutputOrder) %>% 
  rename(continent = secondaryRegion) %>%
  as.data.frame()

rowAnnoColorsMod = rowAnnoColors
rowAnnoColorsMod[["Pattern"]] = rowAnnoColorsMod_hrp3DeletionPattern
rowAnnoColorsMod[["pfhrp3- Pattern"]] = rowAnnoColorsMod_hrp3DeletionPattern


rowAnnoColorsMod[["DeletionPattern"]] = rowAnnoColorsMod_hrp3DeletionPattern

rowAnnoColorsMod[["pfhrps Call"]] = pfhrpsCallColors
topAnnoColors_mod = list()
topAnnoColors_mod[["Genes"]] = c("other" = "#56B4E9", hrp = "#009E73", Pf332 = "#D55E00", rRNA = "#FF5AAF", "pfmdr1" = "#7CFFFA")
topAnnoColors_mod[["Genes"]] = c("other" = "#56B4E9", hrp = "#8400CD", Pf332 = "#D55E00", rRNA = "#FF5AAF", "pfmdr1" = "#7CFFFA")
topAnnoColors_mod[["Genomic Region"]] = c("Chr11/13 Duplicated Region" = "#0072B2", "Subtelomere" = "#E69F00", "Chr5 Duplication" = "#EF0096")

rowAnnoDf_hrp3_deleted_sorted = rowAnnoDf_hrp3_deleted %>%
  as_tibble() %>%
  mutate(rowID = row_number()) %>%
  #mutate(Pattern = factor(Pattern, levels = c("11++/13-", "5++/13-", "11/13-TARE1", "13-"))) %>%
  #mutate(Pattern = gsub("11/13-TARE1", "13-")) %>%
  mutate(Pattern = factor(Pattern, levels = c("13-11++", "13-5++", "13-TARE1", "13-"))) %>%
  arrange(Pattern, continent, hrpCall, hclustOutputOrder) %>%
  rename("pfhrps Call" = hrpCall)

rowAnnoDf_hrp3_deleted_sortedDf = rowAnnoDf_hrp3_deleted_sorted %>%
  select(-rowID, -hclustOutputOrder) %>%
  as.data.frame()

allBasicInfo_filt_sp_mat_noLabs = allBasicInfo_filt_sp_mat_hrp3_deleted
rownames(allBasicInfo_filt_sp_mat_noLabs) = NULL
colnames(allBasicInfo_filt_sp_mat_noLabs) = NULL

allBasicInfo_filt_sp_mat_noLabs_chr08 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_08_", colnames(allBasicInfo_filt_sp_mat))] #08: 1290365 - 1387982 1,290kb:1,387kb
allBasicInfo_filt_sp_mat_noLabs_chr11 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_11_", colnames(allBasicInfo_filt_sp_mat))] #11: 1897157 - 2003328 1,897kb:2,003kb
allBasicInfo_filt_sp_mat_noLabs_chr13 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_13_", colnames(allBasicInfo_filt_sp_mat))] #13: 2769916 - 2844777 2,769kb:2,844kb

#05: 944389 - 988747 944kb:988kb
#08: 1290365 - 1387982 1,290kb:1,387kb
#11: 1897157 - 2003328 1,897kb:2,003kb
#13: 2769916 - 2844777 2,769kb:2,844kb

allBasicInfo_filt_sp_mat_noLabs_chr11_sorted = allBasicInfo_filt_sp_mat_noLabs_chr11[rowAnnoDf_hrp3_deleted_sorted$rowID,]
allBasicInfo_filt_sp_mat_noLabs_chr13_sorted = allBasicInfo_filt_sp_mat_noLabs_chr13[rowAnnoDf_hrp3_deleted_sorted$rowID,]
rowAnnoDf_hrp3_deleted_sortedDf_mod = rowAnnoDf_hrp3_deleted_sortedDf
rowAnnoDf_hrp3_deleted_sortedDf_mod = rowAnnoDf_hrp3_deleted_sortedDf_mod%>% 
  rename("pfhrp3- Pattern" = "Pattern")


annotationTextSize = 20
sideAnno = rowAnnotation(
  df = rowAnnoDf_hrp3_deleted_sortedDf_mod,
  col = rowAnnoColorsMod,
  gp = gpar(col = "grey10"),
    simple_anno_size = unit(1.5, "cm"),
  annotation_name_gp = gpar(fontsize = annotationTextSize),
  annotation_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold")
  ),
  na_col = c("#99999900"),
  gap = unit(0.1, "cm")
)

topAnnoDf  = regions[,c("inGene", "genomicRegion", "chrom")] %>% as.data.frame()

topAnnoDf_chr08 = topAnnoDf %>% filter(grepl("_08_",chrom)) %>% select(-chrom)
topAnnoDf_chr11 = topAnnoDf %>% filter(grepl("_11_",chrom)) %>% select(-chrom)
topAnnoDf_chr13 = topAnnoDf %>% filter(grepl("_13_",chrom)) %>% select(-chrom)


topAnnoDf_chr11_mod = topAnnoDf_chr11 %>%
  rename("Genomic Region" = genomicRegion, "Genes" = "inGene") %>%
  mutate(Genes = ifelse(Genes, "other", NA)) %>%
  mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`))%>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`))

topAnnoDf_chr13_mod = topAnnoDf_chr13 %>%
  rename("Genomic Region" = genomicRegion, "Genes" = "inGene")%>%
  mutate(Genes = ifelse(Genes, "other", NA)) %>%
  mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`)) %>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`))

topAnno_chr11 = HeatmapAnnotation(
    df = topAnnoDf_chr11_mod,
    col = topAnnoColors_mod,
    annotation_name_gp = gpar(fontsize = annotationTextSize),
    annotation_legend_param = list(
        labels_gp = gpar(fontsize = annotationTextSize),
        title_gp = gpar(fontsize = annotationTextSize, fontface = "bold")
    ),
    annotation_name_side = "left",
    show_annotation_name = T,
    na_col = "#FFFFFF00",
  gap = unit(0.1, "cm")
)

topAnno_chr13 = HeatmapAnnotation(
  df = topAnnoDf_chr13_mod,
  col = topAnnoColors_mod,
  annotation_name_gp = gpar(fontsize = annotationTextSize),
  annotation_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold")
  ),
  annotation_name_side = "left",
  show_annotation_name = F,
  na_col = "#FFFFFF00",
  gap = unit(0.1, "cm")
)
library(circlize)
col_fun = colorRamp2(c(0, 1, 2), c(heat.colors(3)))

allCoverageHeatMap_chr11 = Heatmap(
  allBasicInfo_filt_sp_mat_noLabs_chr11_sorted,
  cluster_columns = F,
  cluster_rows = F,
  col = col_fun,
  name = "coverage",
  top_annotation = topAnno_chr11,
  left_annotation = sideAnno,
  row_dend_width = unit(5, "cm"),
  column_dend_height = unit(5, "cm"),
  heatmap_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold"),
    title = "coverage", at = c(0, 0.5, 1, 1.5, 2),
        labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x")
  ),
  column_title = "Chr11[1,897kb:2,003kb]",
  column_title_gp = gpar(fontsize = 20, fontface = "italic")
)

allCoverageHeatMap_chr13 = Heatmap(
  allBasicInfo_filt_sp_mat_noLabs_chr13_sorted,
  cluster_columns = F,
  cluster_rows = F,
  col = col_fun,
  name = "coverage",
  top_annotation = topAnno_chr13,
  # left_annotation = sideAnno,
  row_dend_width = unit(5, "cm"),
  column_dend_height = unit(5, "cm"),
  heatmap_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold",
                    title = "coverage", at = c(0, 0.5, 1, 1.5, 2),
        labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x"))
  ),
  column_title = "              Chr13[2,769kb:2,844kb]  pfhrp3",
  column_title_gp = gpar(fontsize = 20, fontface = "italic")
)

Reading in chromosome 5 pfmdr1 dup region

Code

cov = readr::read_tsv("../meta/allCov_summaryStats.tab.txt.gz")

allReports_chr5 = readr::read_tsv("deletion_patterns/stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200/popClustering/reports/allBasicInfo.tab.txt.gz") %>%
  filter(start >= 944389) %>%
  #filter(sample %in% allMetaDeletionCalls_Hrp3pattern2_samples$sample) %>%
  filter(sample %in% rownames(allBasicInfo_filt_sp_mat_hrp3_deleted)) %>%
  mutate(inGene =  !is.na(extraField0) ) %>%
  left_join(cov) %>%
  mutate(medianCov = median(perBaseCoverage),
            meanCov = mean(perBaseCoverage)) %>%
  mutate(perBaseCoverageNorm = ifelse(inGene, perBaseCoverage/medianPerBaseCov_inGenes, perBaseCoverage/medianPerBaseCov_notInGenes))  %>%
  mutate(perBaseCoverageNormRounded = ifelse(perBaseCoverageNorm >0.10 & perBaseCoverageNorm <= 1, 1, perBaseCoverageNorm))  %>%
  mutate(perBaseCoverageNormRounded = round(perBaseCoverageNormRounded))

allReports_chr5_sp = allReports_chr5 %>%
  select(sample, name, perBaseCoverageNormRounded) %>%
  spread(name, perBaseCoverageNormRounded)

allReports_chr5_sp_mat = as.matrix(allReports_chr5_sp[,2:ncol(allReports_chr5_sp)])
rownames(allReports_chr5_sp_mat) = allReports_chr5_sp$sample

allReports_chr5_sp_mat = allReports_chr5_sp_mat[match(rownames(allBasicInfo_filt_sp_mat_hrp3_deleted)[rowAnnoDf_hrp3_deleted_sorted$rowID], rownames(allReports_chr5_sp_mat)), ]

allReports_chr5_sp_mat[allReports_chr5_sp_mat >2] = 2


topAnno_chr05 = allReports_chr5 %>%
  filter(sample == .$sample[1]) %>%
  select(name, extraField0) %>%
  rename(`Gene Description` = extraField0) %>%
  mutate(`Gene Description` = gsub(".*description=", "", `Gene Description`))%>%
  mutate(`Gene Description` = gsub("\\].*", "", `Gene Description`)) %>%
  mutate(`Gene Description` = ifelse(grepl("PHIST", `Gene Description`), gsub("\\).*", "", gsub(".*PHIST", "PHIST", `Gene Description`)), `Gene Description`))


topAnno_chr05Df = topAnno_chr05 %>%
  separate(name, into = c("chrom", "start", "end"), remove = F, convert = T, sep = "-") %>%
  mutate(`Genomic Region` = ifelse(start >= 952474 & end <= 979431, "Chr5 Duplication", NA)) %>%
  select(-name, -chrom, -start, -end) %>%
  as.data.frame()

topAnno_chr05Colors = createColorListFromDf(topAnno_chr05Df)

# 05: 944389 - 988747 944kb:988kb

topAnno_chr05Df_mod = topAnno_chr05Df %>%
  select(`Gene Description`, `Genomic Region`) %>%
  mutate(Genes = ifelse(is.na(`Gene Description`), NA, "other")) %>%
  mutate(Genes = ifelse(`Gene Description` == "multidrug resistance protein 1", "pfmdr1", Genes)) %>%
  select(`Genes`, `Genomic Region`)

topAnno_chr05HM = HeatmapAnnotation(
  df = topAnno_chr05Df_mod,
  col = topAnnoColors_mod,
  annotation_name_gp = gpar(fontsize = annotationTextSize),
  annotation_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold")
  ),
  annotation_name_side = "left",
  na_col = c("#99999900"),
  gap = unit(0.1, "cm"),
  show_annotation_name = F
)


allReports_chr5_sp_mat_nolab = allReports_chr5_sp_mat
colnames(allReports_chr5_sp_mat_nolab) = NULL
rownames(allReports_chr5_sp_mat_nolab) = NULL
allReports_chr5_sp_mat_hm = Heatmap(
  allReports_chr5_sp_mat_nolab,
  cluster_columns = F,
  cluster_rows = F,
  col = col_fun,
  name = "coverage",
  top_annotation = topAnno_chr05HM,
  #right_annotation = sideAnno,
  row_dend_width = unit(5, "cm"),
  column_dend_height = unit(5, "cm"),
  heatmap_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold",
                    title = "coverage", at = c(0, 0.5, 1, 1.5, 2),
        labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x"))
  ),
  column_title = "Chr05[944kb:988kb]",
  column_title_gp = gpar(fontsize = 20, fontface = "italic")
)

Code

#05: 944389 - 988747 944kb:988kb
#11: 1897157 - 2003328 1,897kb:2,003kb
#13: 2769916 - 2844777 2,769kb:2,844kb

hms_list = allCoverageHeatMap_chr11 + allCoverageHeatMap_chr13 + allReports_chr5_sp_mat_hm

draw(hms_list, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom",
     ht_gap = unit(2, "cm"),
     #padding = unit(c(5.5 *5*2, 5.5, 5.5, 5.5), "points")
     )

Code

#05: 944389 - 988747 944kb:988kb
#11: 1897157 - 2003328 1,897kb:2,003kb
#13: 2769916 - 2844777 2,769kb:2,844kb
hms_list = allCoverageHeatMap_chr11 + allCoverageHeatMap_chr13 + allReports_chr5_sp_mat_hm

pdf("allHeatmap_byChrom_filtered_chr11_chr13_chr5_sorted.pdf", useDingbats = F, width = 16, height = 12)
draw(hms_list, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom",
     ht_gap = unit(2, "cm"),
     padding = unit(c(5.5 *5, 5.5, 5.5, 5.5), "points")
     )
dev.off()

allHeatmap_byChrom_filtered_chr11_chr13_chr5_sorted.pdf

Coverage of genomic regions in pfhrp2 deleted strains

Displaying from Pf3D7 genomic version=2015-06-18 of the following chromosome regions

chromosome 08: 1290365 - 1387982 1,290kb:1,387kb
chromosome 11: 1897157 - 2003328 1,897kb:2,003kb
chromosome 13: 2769916 - 2844777 2,769kb:2,844kb

Code

allBasicInfo_filt_sp_mat_hrp2_deleted = allBasicInfo_filt_sp_mat[rownames(allBasicInfo_filt_sp_mat) %in% allMetaDeletionCalls_hrp2_deleted$sample, ]
metaSelected_hrp2_deleted = allMetaDeletionCalls_hrp2_deleted[match(rownames(allBasicInfo_filt_sp_mat_hrp2_deleted), allMetaDeletionCalls_hrp2_deleted$sample), ]

allBasicInfo_filt_sp_mat_hrp2_deleted_hclust = hclust(dist(allBasicInfo_filt_sp_mat_hrp2_deleted))

allBasicInfo_filt_sp_mat_hrp2_deleted_hclust_ordering = tibble(
  sample = rownames(allBasicInfo_filt_sp_mat_hrp2_deleted)[allBasicInfo_filt_sp_mat_hrp2_deleted_hclust$order], 
  hclustInputOrder = allBasicInfo_filt_sp_mat_hrp2_deleted_hclust$order, 
  hclustOutputOrder = 1:nrow(allBasicInfo_filt_sp_mat_hrp2_deleted)
)


rowAnnoDf_hrp2_deleted  = metaSelected_hrp2_deleted %>%
  left_join(allBasicInfo_filt_sp_mat_hrp2_deleted_hclust_ordering) %>%
  select("Pattern", "secondaryRegion", "hrpCall", hclustOutputOrder) %>% 
  rename(continent = secondaryRegion) %>%
  as.data.frame()

rowAnnoColorsMod = rowAnnoColors
rowAnnoColorsMod[["Pattern"]] = rowAnnoColorsMod_hrp3DeletionPattern
rowAnnoColorsMod[["pfhrp3- Pattern"]] = rowAnnoColorsMod_hrp3DeletionPattern


rowAnnoColorsMod[["DeletionPattern"]] = rowAnnoColorsMod_hrp3DeletionPattern

rowAnnoColorsMod[["pfhrps Call"]] = pfhrpsCallColors

topAnnoColors_mod = list()
topAnnoColors_mod[["Genes"]] = c("other" = "#56B4E9", hrp = "#009E73", Pf332 = "#D55E00", rRNA = "#FF5AAF", "pfmdr1" = "#7CFFFA")
topAnnoColors_mod[["Genes"]] = c("other" = "#56B4E9", hrp = "#8400CD", Pf332 = "#D55E00", rRNA = "#FF5AAF", "pfmdr1" = "#7CFFFA")
topAnnoColors_mod[["Genomic Region"]] = c("Chr11/13 Duplicated Region" = "#0072B2", "Subtelomere" = "#E69F00", "Chr5 Duplication" = "#EF0096")

rowAnnoDf_hrp2_deleted_sorted = rowAnnoDf_hrp2_deleted %>%
  as_tibble() %>%
  mutate(rowID = row_number()) %>%
  # mutate(Pattern = factor(Pattern, levels = c("11++/13-", "5++/13-", "11/13-TARE1", "11-TARE1/13"))) %>%
  # mutate(Pattern = factor(Pattern, levels = c("13-11++", "13-5++", "13-TARE1", "13-"))) %>%
  mutate(Pattern = factor(Pattern, levels = c("13-11++"))) %>%
  arrange(Pattern, continent, hrpCall, hclustOutputOrder) %>%
  rename("pfhrps Call" = hrpCall)

rowAnnoDf_hrp2_deleted_sortedDf = rowAnnoDf_hrp2_deleted_sorted %>%
  select(-rowID,-hclustOutputOrder) %>%
  as.data.frame()

allBasicInfo_filt_sp_mat_noLabs = allBasicInfo_filt_sp_mat_hrp2_deleted
rownames(allBasicInfo_filt_sp_mat_noLabs) = NULL
colnames(allBasicInfo_filt_sp_mat_noLabs) = NULL

allBasicInfo_filt_sp_mat_noLabs_chr08 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_08_", colnames(allBasicInfo_filt_sp_mat))] #08: 1290365 - 1387982 1,290kb:1,387kb
allBasicInfo_filt_sp_mat_noLabs_chr11 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_11_", colnames(allBasicInfo_filt_sp_mat))] #11: 1897157 - 2003328 1,897kb:2,003kb
allBasicInfo_filt_sp_mat_noLabs_chr13 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_13_", colnames(allBasicInfo_filt_sp_mat))] #13: 2769916 - 2844777 2,769kb:2,844kb

#08: 1290365 - 1387982 1,290kb:1,387kb
#11: 1897157 - 2003328 1,897kb:2,003kb
#13: 2769916 - 2844777 2,769kb:2,844kb

allBasicInfo_filt_sp_mat_noLabs_chr08_sorted = allBasicInfo_filt_sp_mat_noLabs_chr08[rowAnnoDf_hrp2_deleted_sorted$rowID,]
allBasicInfo_filt_sp_mat_noLabs_chr11_sorted = allBasicInfo_filt_sp_mat_noLabs_chr11[rowAnnoDf_hrp2_deleted_sorted$rowID,]
allBasicInfo_filt_sp_mat_noLabs_chr13_sorted = allBasicInfo_filt_sp_mat_noLabs_chr13[rowAnnoDf_hrp2_deleted_sorted$rowID,]


rowAnnoDf_hrp2_deleted_sortedDf_mod = rowAnnoDf_hrp2_deleted_sortedDf
rowAnnoDf_hrp2_deleted_sortedDf_mod = rowAnnoDf_hrp2_deleted_sortedDf_mod%>% 
  rename("pfhrp3- Pattern" = "Pattern")

annotationTextSize = 20
sideAnno = rowAnnotation(
  df = rowAnnoDf_hrp2_deleted_sortedDf_mod,
  col = rowAnnoColorsMod,
  gp = gpar(col = "grey10"),
    simple_anno_size = unit(1.5, "cm"),
  annotation_name_gp = gpar(fontsize = annotationTextSize),
  annotation_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold")
  ),
  na_col = c("#99999900"),
  gap = unit(0.1, "cm")
)

topAnnoDf  = regions[,c("inGene", "genomicRegion", "chrom")] %>% as.data.frame()

topAnnoDf_chr08 = topAnnoDf %>% filter(grepl("_08_",chrom)) %>% select(-chrom)
topAnnoDf_chr11 = topAnnoDf %>% filter(grepl("_11_",chrom)) %>% select(-chrom)
topAnnoDf_chr13 = topAnnoDf %>% filter(grepl("_13_",chrom)) %>% select(-chrom)

topAnnoDf_chr08_mod = topAnnoDf_chr08 %>%
  rename("Genomic Region" = genomicRegion, "Genes" = "inGene") %>%
  mutate(Genes = ifelse(Genes, "other", NA)) %>%
  mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`))%>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`)) %>%
  mutate(`Genomic Region` = NA)

topAnnoDf_chr11_mod = topAnnoDf_chr11 %>%
  rename("Genomic Region" = genomicRegion, "Genes" = "inGene") %>%
  mutate(Genes = ifelse(Genes, "other", NA)) %>%
  mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`)) %>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`))

topAnnoDf_chr13_mod = topAnnoDf_chr13 %>%
  rename("Genomic Region" = genomicRegion, "Genes" = "inGene")%>%
  mutate(Genes = ifelse(Genes, "other", NA)) %>%
  mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`)) %>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`))

topAnno_chr08 = HeatmapAnnotation(
    df = topAnnoDf_chr08_mod,
    col = topAnnoColors_mod,
    annotation_name_gp = gpar(fontsize = annotationTextSize),
    annotation_legend_param = list(
        labels_gp = gpar(fontsize = annotationTextSize),
        title_gp = gpar(fontsize = annotationTextSize, fontface = "bold")
    ),
    annotation_name_side = "left",
    show_annotation_name = T,
    na_col = "#FFFFFF00",
  gap = unit(0.1, "cm")
)

topAnno_chr11 = HeatmapAnnotation(
    df = topAnnoDf_chr11_mod,
    col = topAnnoColors_mod,
    annotation_name_gp = gpar(fontsize = annotationTextSize),
    annotation_legend_param = list(
        labels_gp = gpar(fontsize = annotationTextSize),
        title_gp = gpar(fontsize = annotationTextSize, fontface = "bold")
    ),
    annotation_name_side = "left",
    show_annotation_name = F,
    na_col = "#FFFFFF00",
  gap = unit(0.1, "cm")
)

topAnno_chr13 = HeatmapAnnotation(
  df = topAnnoDf_chr13_mod,
  col = topAnnoColors_mod,
  annotation_name_gp = gpar(fontsize = annotationTextSize),
  annotation_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold")
  ),
  annotation_name_side = "left",
  show_annotation_name = F,
  na_col = "#FFFFFF00",
  gap = unit(0.1, "cm")
)
library(circlize)
col_fun = colorRamp2(c(0, 1, 2), c(heat.colors(3)))
allCoverageHeatMap_chr08 = Heatmap(
  allBasicInfo_filt_sp_mat_noLabs_chr08_sorted,
  cluster_columns = F,
  cluster_rows = F,
  col = col_fun,
  name = "coverage",
  top_annotation = topAnno_chr08,
  left_annotation = sideAnno,
  row_dend_width = unit(5, "cm"),
  column_dend_height = unit(5, "cm"),
  heatmap_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold"),
    title = "coverage", at = c(0, 0.5, 1, 1.5, 2),
        labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x")
  ),
  column_title = "Chr08[1,290kb:1,387kb]      pfhrp2",
  column_title_gp = gpar(fontsize = 30, fontface = "italic")
)

allCoverageHeatMap_chr11 = Heatmap(
  allBasicInfo_filt_sp_mat_noLabs_chr11_sorted,
  cluster_columns = F,
  cluster_rows = F,
  col = col_fun,
  name = "coverage",
  top_annotation = topAnno_chr11,
  #left_annotation = sideAnno,
  row_dend_width = unit(5, "cm"),
  column_dend_height = unit(5, "cm"),
  heatmap_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold"),
    title = "coverage", at = c(0, 0.5, 1, 1.5, 2),
        labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x")
  ),
  column_title = "Chr11[1,897kb:2,003kb]",
  column_title_gp = gpar(fontsize = 30, fontface = "italic")
)

allCoverageHeatMap_chr13 = Heatmap(
  allBasicInfo_filt_sp_mat_noLabs_chr13_sorted,
  cluster_columns = F,
  cluster_rows = F,
  col = col_fun,
  name = "coverage",
  top_annotation = topAnno_chr13,
  # left_annotation = sideAnno,
  row_dend_width = unit(5, "cm"),
  column_dend_height = unit(5, "cm"),
  heatmap_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold",
                    title = "coverage", at = c(0, 0.5, 1, 1.5, 2),
        labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x"))
  ),
  column_title = "Chr13[2,769kb:2,844kb]  pfhrp3",
  column_title_gp = gpar(fontsize = 30, fontface = "italic")
)

Code

#08: 1290365 - 1387982 1,290kb:1,387kb
#11: 1897157 - 2003328 1,897kb:2,003kb
#13: 2769916 - 2844777 2,769kb:2,844kb

hms_list = allCoverageHeatMap_chr08 + allCoverageHeatMap_chr11 + allCoverageHeatMap_chr13

draw(hms_list, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom",
     ht_gap = unit(2, "cm"),
     #padding = unit(c(5.5 *5*2, 5.5, 5.5, 5.5), "points")
     )

Code

#08: 1290365 - 1387982 1,290kb:1,387kb
#11: 1897157 - 2003328 1,897kb:2,003kb
#13: 2769916 - 2844777 2,769kb:2,844kb

pdf("allHeatmap_byChrom_filtered_chr08_chr11_chr13_sorted_hrp2_deleted.pdf", useDingbats = F, width = 20, height = 12)
draw(hms_list, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom",
     ht_gap = unit(2, "cm"),
     padding = unit(c(5.5 *5, 5.5, 5.5, 5.5 *5*2.5), "points")
     )
dev.off()

allHeatmap_byChrom_filtered_chr08_chr11_chr13_sorted_hrp2_deleted.pdf

Coverage of genomic regions in chromosome 11 deleted strains

Displaying from Pf3D7 genomic version=2015-06-18 of the following chromosome regions

chromosome 08: 1290365 - 1387982 1,290kb:1,387kb
chromosome 11: 1897157 - 2003328 1,897kb:2,003kb
chromosome 13: 2769916 - 2844777 2,769kb:2,844kb

Code

allBasicInfo_filt_sp_mat_chr11_deleted = allBasicInfo_filt_sp_mat[rownames(allBasicInfo_filt_sp_mat) %in% allMetaDeletionCalls_chr11_deleted$sample, ]
metaSelected_chr11_deleted = allMetaDeletionCalls_chr11_deleted[match(rownames(allBasicInfo_filt_sp_mat_chr11_deleted), allMetaDeletionCalls_chr11_deleted$sample), ]

allBasicInfo_filt_sp_mat_chr11_deleted_hclust = hclust(dist(allBasicInfo_filt_sp_mat_chr11_deleted))

allBasicInfo_filt_sp_mat_chr11_deleted_hclust_ordering = tibble(
  sample = rownames(allBasicInfo_filt_sp_mat_chr11_deleted)[allBasicInfo_filt_sp_mat_chr11_deleted_hclust$order], 
  hclustInputOrder = allBasicInfo_filt_sp_mat_chr11_deleted_hclust$order, 
  hclustOutputOrder = 1:nrow(allBasicInfo_filt_sp_mat_chr11_deleted)
)

rowAnnoDf_chr11_deleted  = metaSelected_chr11_deleted %>%
  left_join(allBasicInfo_filt_sp_mat_chr11_deleted_hclust_ordering) %>%
  select("Pattern", "secondaryRegion", "hrpCall", hclustOutputOrder) %>% 
  rename(continent = secondaryRegion) %>%
  as.data.frame()

rowAnnoColorsMod = rowAnnoColors
rowAnnoColorsMod[["Pattern"]] = rowAnnoColorsMod_hrp3DeletionPattern
rowAnnoColorsMod[["pfhrp3- Pattern"]] = rowAnnoColorsMod_hrp3DeletionPattern


rowAnnoColorsMod[["DeletionPattern"]] = rowAnnoColorsMod_hrp3DeletionPattern

rowAnnoColorsMod[["pfhrps Call"]] = pfhrpsCallColors
topAnnoColors_mod = list()
topAnnoColors_mod[["Genes"]] = c("other" = "#56B4E9", hrp = "#009E73", Pf332 = "#D55E00", rRNA = "#FF5AAF", "pfmdr1" = "#7CFFFA")
topAnnoColors_mod[["Genes"]] = c("other" = "#56B4E9", hrp = "#8400CD", Pf332 = "#D55E00", rRNA = "#FF5AAF", "pfmdr1" = "#7CFFFA")
topAnnoColors_mod[["Genomic Region"]] = c("Chr11/13 Duplicated Region" = "#0072B2", "Subtelomere" = "#E69F00", "Chr5 Duplication" = "#EF0096")



rowAnnoDf_chr11_deleted_sorted = rowAnnoDf_chr11_deleted %>%
  as_tibble()  %>% 
  mutate(rowID = row_number()) %>%
  # mutate(Pattern = factor(Pattern, levels = c("11++/13-", "5++/13-", "11/13-TARE1", "11-TARE1/13"))) %>%
  mutate(Pattern = ifelse(is.na(Pattern), "13++11-", Pattern)) %>%
  mutate(Pattern = factor(Pattern, levels = c("13-11++", "11-TARE1", "13++11-"))) %>%
  arrange(Pattern, continent, hrpCall, hclustOutputOrder) %>%
  #arrange(Pattern, continent, hrpCall) %>%
  rename("pfhrps Call" = hrpCall) %>% 
  select(-hclustOutputOrder)

rowAnnoDf_chr11_deleted_sortedDf = rowAnnoDf_chr11_deleted_sorted %>%
  select(-rowID) %>%
  as.data.frame()



allBasicInfo_filt_sp_mat_noLabs = allBasicInfo_filt_sp_mat_chr11_deleted
rownames(allBasicInfo_filt_sp_mat_noLabs) = NULL
colnames(allBasicInfo_filt_sp_mat_noLabs) = NULL

allBasicInfo_filt_sp_mat_noLabs_chr08 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_08_", colnames(allBasicInfo_filt_sp_mat))] #08: 1290365 - 1387982 1,290kb:1,387kb
allBasicInfo_filt_sp_mat_noLabs_chr11 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_11_", colnames(allBasicInfo_filt_sp_mat))] #11: 1897157 - 2003328 1,897kb:2,003kb
allBasicInfo_filt_sp_mat_noLabs_chr13 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_13_", colnames(allBasicInfo_filt_sp_mat))] #13: 2769916 - 2844777 2,769kb:2,844kb

#08: 1290365 - 1387982 1,290kb:1,387kb
#11: 1897157 - 2003328 1,897kb:2,003kb
#13: 2769916 - 2844777 2,769kb:2,844kb

allBasicInfo_filt_sp_mat_noLabs_chr08_sorted = allBasicInfo_filt_sp_mat_noLabs_chr08[rowAnnoDf_chr11_deleted_sorted$rowID,]
allBasicInfo_filt_sp_mat_noLabs_chr11_sorted = allBasicInfo_filt_sp_mat_noLabs_chr11[rowAnnoDf_chr11_deleted_sorted$rowID,]
allBasicInfo_filt_sp_mat_noLabs_chr13_sorted = allBasicInfo_filt_sp_mat_noLabs_chr13[rowAnnoDf_chr11_deleted_sorted$rowID,]

rowAnnoDf_chr11_deleted_sortedDf_mod = rowAnnoDf_chr11_deleted_sortedDf
rowAnnoDf_chr11_deleted_sortedDf_mod = rowAnnoDf_chr11_deleted_sortedDf_mod%>% 
  rename("pfhrp3- Pattern" = "Pattern")

annotationTextSize = 20
sideAnno = rowAnnotation(
  df = rowAnnoDf_chr11_deleted_sortedDf,
  col = rowAnnoColorsMod,
  gp = gpar(col = "grey10"),
    simple_anno_size = unit(1.5, "cm"),
  annotation_name_gp = gpar(fontsize = annotationTextSize),
  annotation_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold")
  ),
  na_col = c("#99999900"),
  gap = unit(0.1, "cm")
)

topAnnoDf  = regions[,c("inGene", "genomicRegion", "chrom")] %>% as.data.frame()

topAnnoDf_chr08 = topAnnoDf %>% filter(grepl("_08_",chrom)) %>% select(-chrom)
topAnnoDf_chr11 = topAnnoDf %>% filter(grepl("_11_",chrom)) %>% select(-chrom)
topAnnoDf_chr13 = topAnnoDf %>% filter(grepl("_13_",chrom)) %>% select(-chrom)

topAnnoDf_chr08_mod = topAnnoDf_chr08 %>%
  rename("Genomic Region" = genomicRegion, "Genes" = "inGene") %>%
  mutate(Genes = ifelse(Genes, "other", NA)) %>%
  mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`))%>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`)) %>%
  mutate(`Genomic Region` = NA)

topAnnoDf_chr11_mod = topAnnoDf_chr11 %>%
  rename("Genomic Region" = genomicRegion, "Genes" = "inGene") %>%
  mutate(Genes = ifelse(Genes, "other", NA)) %>%
  mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`)) %>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`))

topAnnoDf_chr13_mod = topAnnoDf_chr13 %>%
  rename("Genomic Region" = genomicRegion, "Genes" = "inGene")%>%
  mutate(Genes = ifelse(Genes, "other", NA)) %>%
  mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`)) %>%
  mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`))

topAnno_chr08 = HeatmapAnnotation(
    df = topAnnoDf_chr08_mod,
    col = topAnnoColors_mod,
    annotation_name_gp = gpar(fontsize = annotationTextSize),
    annotation_legend_param = list(
        labels_gp = gpar(fontsize = annotationTextSize),
        title_gp = gpar(fontsize = annotationTextSize, fontface = "bold")
    ),
    annotation_name_side = "left",
    show_annotation_name = T,
    na_col = "#FFFFFF00",
  gap = unit(0.1, "cm")
)

topAnno_chr11 = HeatmapAnnotation(
    df = topAnnoDf_chr11_mod,
    col = topAnnoColors_mod,
    annotation_name_gp = gpar(fontsize = annotationTextSize),
    annotation_legend_param = list(
        labels_gp = gpar(fontsize = annotationTextSize),
        title_gp = gpar(fontsize = annotationTextSize, fontface = "bold")
    ),
    annotation_name_side = "left",
    show_annotation_name = F,
    na_col = "#FFFFFF00",
  gap = unit(0.1, "cm")
)

topAnno_chr13 = HeatmapAnnotation(
  df = topAnnoDf_chr13_mod,
  col = topAnnoColors_mod,
  annotation_name_gp = gpar(fontsize = annotationTextSize),
  annotation_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold")
  ),
  annotation_name_side = "left",
  show_annotation_name = F,
  na_col = "#FFFFFF00",
  gap = unit(0.1, "cm")
)
library(circlize)
col_fun = colorRamp2(c(0, 1, 2), c(heat.colors(3)))
allCoverageHeatMap_chr08 = Heatmap(
  allBasicInfo_filt_sp_mat_noLabs_chr08_sorted,
  cluster_columns = F,
  cluster_rows = F,
  col = col_fun,
  name = "coverage",
  top_annotation = topAnno_chr08,
  left_annotation = sideAnno,
  row_dend_width = unit(5, "cm"),
  column_dend_height = unit(5, "cm"),
  heatmap_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold"),
    title = "coverage", at = c(0, 0.5, 1, 1.5, 2),
        labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x")
  ),                                
  column_title = "Chr08[1,290kb:1,387kb]      pfhrp2",
  column_title_gp = gpar(fontsize = 30, fontface = "italic")
)

allCoverageHeatMap_chr11 = Heatmap(
  allBasicInfo_filt_sp_mat_noLabs_chr11_sorted,
  cluster_columns = F,
  cluster_rows = F,
  col = col_fun,
  name = "coverage",
  top_annotation = topAnno_chr11,
  #left_annotation = sideAnno,
  row_dend_width = unit(5, "cm"),
  column_dend_height = unit(5, "cm"),
  heatmap_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold"),
    title = "coverage", at = c(0, 0.5, 1, 1.5, 2),
        labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x")
  ),
  column_title = "Chr11[1,897kb:2,003kb]",
  column_title_gp = gpar(fontsize = 30, fontface = "italic")
)

allCoverageHeatMap_chr13 = Heatmap(
  allBasicInfo_filt_sp_mat_noLabs_chr13_sorted,
  cluster_columns = F,
  cluster_rows = F,
  col = col_fun,
  name = "coverage",
  top_annotation = topAnno_chr13,
  # left_annotation = sideAnno,
  row_dend_width = unit(5, "cm"),
  column_dend_height = unit(5, "cm"),
  heatmap_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold",
                    title = "coverage", at = c(0, 0.5, 1, 1.5, 2),
        labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x"))
  ),
  column_title = "Chr13[2,769kb:2,844kb]  pfhrp3",
  column_title_gp = gpar(fontsize = 30, fontface = "italic")
)

Code

#08: 1290365 - 1387982 1,290kb:1,387kb
#11: 1897157 - 2003328 1,897kb:2,003kb
#13: 2769916 - 2844777 2,769kb:2,844kb

hms_list = allCoverageHeatMap_chr08 + allCoverageHeatMap_chr11 + allCoverageHeatMap_chr13

draw(hms_list, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom",
     ht_gap = unit(2, "cm"),
     #padding = unit(c(5.5 *5*2, 5.5, 5.5, 5.5), "points")
     )

Code

#08: 1290365 - 1387982 1,290kb:1,387kb
#11: 1897157 - 2003328 1,897kb:2,003kb
#13: 2769916 - 2844777 2,769kb:2,844kb

pdf("allHeatmap_byChrom_filtered_chr08_chr11_chr13_sorted_chr11_deleted.pdf", useDingbats = F, width = 20, height = 12)
draw(hms_list, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom",
     ht_gap = unit(2, "cm"),
     padding = unit(c(5.5, 5.5, 5.5, 5.5 *5*2.5), "points")
     )
dev.off()

allHeatmap_byChrom_filtered_chr08_chr11_chr13_sorted_chr11_deleted.pdf

--- title: "Plotting coverage in sub windows pfhrp3 deletion" --- ```{r setup, echo=FALSE, message=FALSE} source("../common.R") ``` # Setup ## Downloads ```{r} #| results: asis #| echo: false cat(createDownloadLink("../meta/metadata/meta.tab.txt")) cat(createDownloadLink("../meta/metadata/metaByBioSample")) cat(createDownloadLink("wgs_variants/THEREALMcCOIL/categorical_method/real_mccoil_COI_calls.tsv")) cat(createDownloadLink("allBasicInfo_filt_sp_mat.Rdata")) cat(createDownloadLink("rowAnnoColors.Rdata")) cat(createDownloadLink("../meta/allCov_summaryStats.tab.txt.gz")) ``` ```{r} meta = readr::read_tsv("../meta/metadata/meta.tab.txt") %>% mutate(country = gsub("South East Asia - East", "Cambodia", country)) metaByBioSample = readr::read_tsv("../meta/metadata/metaByBioSample.tab.txt") %>% mutate(country = gsub("South East Asia - East", "Cambodia", country)) realmccoilCoiCalls = readr::read_tsv("wgs_variants/THEREALMcCOIL/categorical_method/real_mccoil_COI_calls.tsv") realmccoilCoiCalls_poly = realmccoilCoiCalls %>% filter(random_median != 1 | topHE_median != 1) allMetaDeletionCalls = readr::read_tsv("allMetaDeletionCalls.tab.txt") %>% filter(BiologicalSample %!in% realmccoilCoiCalls_poly$BiologicalSample) hrp3Pat2_samplesWithTare1 = readr::read_tsv("deletion_patterns/hrp3Pat2_samplesWithTare1.tsv") # char11 tare1 chr11_tare_calls = readr::read_tsv("deletion_patterns/finalHRPII_HRPIII_windows_investTelemeraseHealing_chr11_full_out_step50_windowSize100_rowAnno.tsv") chr11_tare_calls_hasTare1 = chr11_tare_calls %>% filter(`TARE1 On Chr11`) # these are only pattern 2 aka chr11/chr13- stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta = readr::read_tsv("deletion_patterns/stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta.tsv") stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta = stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta %>% mutate(Pattern = case_when( `TARE1 On Chr5` | `Transposition With Chr5` ~ "13-5++", `TARE1 On Chr13` ~ "13-TARE1", T ~ NA )) # mutate(Pattern = case_when( # `TARE1 On Chr5` | `Transposition With Chr5` ~ "5++/13-", # `TARE1 On Chr13` ~ "11/13-TARE1", # T ~ NA # )) allMetaDeletionCalls_chr11_deleted = allMetaDeletionCalls %>% filter(possiblyChr11Deleted)%>% left_join(stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta %>% select(sample, Pattern)) %>% mutate(Pattern = ifelse(HRP3_deletionPattern == "Pattern 1", "13-11++", Pattern))%>% mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1", Pattern)) # mutate(Pattern = ifelse(HRP3_deletionPattern == "Pattern 1", "11++/13-", Pattern))%>% # mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1/13", Pattern)) allMetaDeletionCalls_hrp2_deleted = allMetaDeletionCalls %>% filter(possiblyHRP2Deleted)%>% left_join(stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta %>% select(sample, Pattern)) %>% mutate(Pattern = ifelse(HRP3_deletionPattern == "Pattern 1", "13-11++", Pattern))%>% mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1", Pattern)) # mutate(Pattern = ifelse(HRP3_deletionPattern == "Pattern 1", "11++/13-", Pattern))%>% # mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1/13", Pattern)) allMetaDeletionCalls_hrp3_deleted = allMetaDeletionCalls %>% filter(possiblyHRP3Deleted)%>% left_join(stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200_sampleRegion_hrp3_pat2_sample_deletion_meta %>% select(sample, Pattern)) %>% mutate(Pattern = ifelse(HRP3_deletionPattern == "Pattern 1", "13-11++", Pattern))%>% mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1", Pattern)) %>% # mutate(Pattern = ifelse(HRP3_deletionPattern == "Pattern 1", "11++/13-", Pattern)) %>% # mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1/13", Pattern)) %>% mutate(Pattern = ifelse(is.na(Pattern), "13-", Pattern)) #mutate(Pattern = factor(Pattern, levels = c("13-11++", "13-5++", "13-TARE1", "13-"))) %>% ``` ```{r} load("allBasicInfo_filt_sp_mat.Rdata") load("rowAnnoColors.Rdata") ``` ## Sample Meta data ```{r} cov = readr::read_tsv("../meta/allCov_summaryStats.tab.txt.gz") meta = readr::read_tsv("../meta/metadata/meta.tab.txt") masterTable = readr::read_tsv("../meta/metadata/masterTable.tab.txt") coveredSamples = readr::read_tsv("samplesCovered.txt", col_names = "sample") %>% left_join(meta %>% select(sample, ExperimentSample, BiologicalSample)) # chr07_dup_samplesCovered = readr::read_tsv("rRNA_chr05_chr07/samplesCovered.txt", col_names = c("sample")) # chr07_dup = readr::read_tsv("rRNA_chr05_chr07/possible_chrom5_deletion_samples.txt", col_names = c("sample")) %>% # left_join(cov %>% # select(sample, meanPerBaseCov)) %>% # left_join(masterTable)%>% # mutate(chr05chr07rRNAPattern = "05-/07++") deletionCalls = allMetaDeletionCalls %>% select(-HRP3_deletionPattern) %>% left_join(allMetaDeletionCalls_hrp3_deleted %>% ungroup() %>% select(sample, Pattern)) %>% mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1", Pattern)) %>% # mutate(Pattern = ifelse(is.na(Pattern) & sample %in% chr11_tare_calls_hasTare1$sample, "11-TARE1/13", Pattern)) %>% left_join(cov %>% select(sample, meanPerBaseCov)) # %>% # full_join(chr07_dup) meta_allOthers = meta %>% filter(BiologicalSample %!in% deletionCalls$BiologicalSample)%>% left_join(cov %>% select(sample, meanPerBaseCov)) %>% left_join(masterTable %>% select(sample, SRARuns))%>% filter(PreferredSample) %>% select(-sample, -ExperimentSample,-PreferredSample) %>% rename(sample = BiologicalSample) %>% filter(!is.na(SRARuns)) meta_withDeletionMetaOutput = bind_rows( deletionCalls %>% select(-sample, -ExperimentSample,-PreferredSample) %>% rename(sample = BiologicalSample) , meta_allOthers ) %>% mutate(uncallable = sample %!in% coveredSamples$BiologicalSample) %>% rename(HRP2Call = possiblyHRP2Deleted, HRP3Call = possiblyHRP3Deleted, HRPsCall = hrpCall, Chr11TelemericCall = possiblyChr11Deleted) %>% mutate(HRP2Call = case_when(uncallable ~ "uncallable", is.na(HRP2Call) ~ "present", !is.na(HRP2Call) & HRP2Call ~ "deletion", T ~ "present"), HRP3Call = case_when(uncallable ~ "uncallable", is.na(HRP3Call) ~ "present", !is.na(HRP3Call) & HRP3Call ~ "deletion", T ~ "present"), HRPsCall = case_when(uncallable ~ "uncallable", is.na(HRPsCall) ~ "pfhrp2+/pfhrp3+", T ~ HRPsCall), Chr11TelemericCall = case_when(uncallable ~ "uncallable", Chr11TelemericCall ~ "deletion", is.na(Chr11TelemericCall) ~ "present", T ~ "uncallable" ) ) # %>% # mutate(chr05chr07rRNAPattern = case_when(sample %in% chr07_dup$sample ~ "05-/07++", # sample %in% chr07_dup_samplesCovered$sample ~ "05/07", # T ~ "uncallable")) masterTable_withDeletionMetaOutput_fieldSamples_labIsolates = meta_withDeletionMetaOutput %>% filter(IsFieldSample | site == "LabIsolate") create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates) write_tsv(meta_withDeletionMetaOutput, "sample_metadata_withAllDeletionCalls.tsv") write_tsv(meta_withDeletionMetaOutput, "Supplemental Table - sample metadata.tsv") write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates, "Supplemental Table - sample metadata - field samples and Lab Isolates.tsv") ``` ```{r} #| results: asis #| echo: false cat(createDownloadLink("sample_metadata_withAllDeletionCalls.tsv")) ``` ### Deletion Counts ### Continent #### HRP2 ```{r} masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp2 = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>% filter(HRP2Call == "deletion") %>% group_by(secondaryRegion) %>% rename(continent = secondaryRegion) %>% count() %>% group_by() %>% mutate(total = sum(n))%>% mutate(percentage = n * 100/total) write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp2, "hrp2_continent_deletion_counts.tsv") create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp2) ``` ```{r} #| results: asis #| echo: false cat(createDownloadLink("hrp2_continent_deletion_counts.tsv")) ``` #### HRP3 ```{r} masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3 = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>% filter(HRP3Call == "deletion") %>% group_by(secondaryRegion) %>% rename(continent = secondaryRegion) %>% count() %>% group_by() %>% mutate(total = sum(n)) %>% mutate(percentage = n * 100/total) write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3, "hrp3_continent_deletion_counts.tsv") create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3) ``` ```{r} #| results: asis #| echo: false cat(createDownloadLink("hrp3_continent_deletion_counts.tsv")) ``` #### HRP3 Pattern ```{r} masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3_pattern = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>% filter(HRP3Call == "deletion") %>% group_by(secondaryRegion, Pattern) %>% rename(continent = secondaryRegion) %>% count() %>% group_by(Pattern) %>% mutate(PatternTotal = sum(n, na.rm = T)) %>% mutate(PatternPercentage = n * 100/PatternTotal) %>% group_by(continent) %>% mutate(continentTotal = sum(n)) %>% mutate(continentPercentage = n * 100/continentTotal) %>% group_by() %>% mutate(total = sum(n)) %>% mutate(percentage = n * 100/total) write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3_pattern, "hrp3_pattern_continent_deletion_counts.tsv") create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3_pattern) ``` ```{r} #| results: asis #| echo: false cat(createDownloadLink("hrp3_pattern_continent_deletion_counts.tsv")) ``` ```{r} masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3_pattern_raw = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>% filter(HRP3Call == "deletion") %>% group_by(Pattern) %>% count() %>% group_by() %>% mutate(PatternTotal = sum(n, na.rm = T)) %>% mutate(percentage = n * 100/PatternTotal) write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3_pattern_raw, "hrp3_pattern_deletion_counts.tsv") create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp3_pattern_raw) ``` ```{r} #| results: asis #| echo: false cat(createDownloadLink("hrp3_pattern_continent_deletion_counts.tsv")) ``` #### HRP2 and HRP3 ```{r} masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp2_and_hrp3 = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>% filter(HRP2Call == "deletion" & HRP3Call == "deletion") %>% group_by(secondaryRegion, Pattern) %>% rename(continent = secondaryRegion) %>% count() %>% group_by() %>% mutate(total = sum(n)) %>% mutate(percentage = n * 100/total) write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp2_and_hrp3, "hrp2_and_hrp3_continent_deletion_counts.tsv") create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrp2_and_hrp3) ``` ```{r} #| results: asis #| echo: false cat(createDownloadLink("hrp2_and_hrp3_continent_deletion_counts.tsv")) ``` #### Chr11 Deletion ```{r} masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_chr11 = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>% filter(Chr11TelemericCall == "deletion") %>% group_by(secondaryRegion) %>% rename(continent = secondaryRegion) %>% count() %>% group_by() %>% mutate(total = sum(n)) %>% mutate(percentage = n * 100 / total) write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_chr11, "chr11_continent_deletion_counts.tsv") create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_chr11) ``` ```{r} #| results: asis #| echo: false cat(createDownloadLink("chr11_continent_deletion_counts.tsv")) ```                   ### HRP Calls ```{r} masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrpCalls = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>% group_by(HRPsCall) %>% count() %>% group_by() %>% mutate(total = sum(n)) %>% mutate(percentage = n * 100 / total) write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrpCalls, "hrpCalls_deletion_counts.tsv") create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_hrpCalls) ``` ```{r} #| results: asis #| echo: false cat(createDownloadLink("hrpCalls_deletion_counts.tsv")) ``` ### Pattern ```{r} masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_pattern = masterTable_withDeletionMetaOutput_fieldSamples_labIsolates %>% group_by(Pattern) %>% count() %>% group_by() %>% mutate(total = sum(n)) %>% mutate(percentage = n * 100 / total) write_tsv(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_pattern, "pattern_counts.tsv") create_dt(masterTable_withDeletionMetaOutput_fieldSamples_labIsolates_pattern) ``` ```{r} #| results: asis #| echo: false cat(createDownloadLink("pattern_counts.tsv")) ``` # Plotting Coverage ## Coverage of genomic regions invovled in _pfhrp3_ deletions of samples with _pfhrp3_ deletions Displaying from Pf3D7 genomic version=2015-06-18 of the following chromosome regions * chromosome 05: 944389 - 988747 944kb:988kb * chromosome 11: 1897157 - 2003328 1,897kb:2,003kb * chromosome 13: 2769916 - 2844777 2,769kb:2,844kb ```{r} allBasicInfo_filt_sp_mat_hrp3_deleted = allBasicInfo_filt_sp_mat[rownames(allBasicInfo_filt_sp_mat) %in% allMetaDeletionCalls_hrp3_deleted$sample, ] metaSelected_hrp3_deleted = allMetaDeletionCalls_hrp3_deleted[match(rownames(allBasicInfo_filt_sp_mat_hrp3_deleted), allMetaDeletionCalls_hrp3_deleted$sample), ] allBasicInfo_filt_sp_mat_hrp3_deleted_hclust = hclust(dist(allBasicInfo_filt_sp_mat_hrp3_deleted)) allBasicInfo_filt_sp_mat_hrp3_deleted_hclust_ordering = tibble( sample = rownames(allBasicInfo_filt_sp_mat_hrp3_deleted)[allBasicInfo_filt_sp_mat_hrp3_deleted_hclust$order], hclustInputOrder = allBasicInfo_filt_sp_mat_hrp3_deleted_hclust$order, hclustOutputOrder = 1:nrow(allBasicInfo_filt_sp_mat_hrp3_deleted) ) rowAnnoDf_hrp3_deleted = metaSelected_hrp3_deleted %>% left_join(allBasicInfo_filt_sp_mat_hrp3_deleted_hclust_ordering) %>% select("Pattern", "secondaryRegion", "hrpCall", hclustOutputOrder) %>% rename(continent = secondaryRegion) %>% as.data.frame() rowAnnoColorsMod = rowAnnoColors rowAnnoColorsMod[["Pattern"]] = rowAnnoColorsMod_hrp3DeletionPattern rowAnnoColorsMod[["pfhrp3- Pattern"]] = rowAnnoColorsMod_hrp3DeletionPattern rowAnnoColorsMod[["DeletionPattern"]] = rowAnnoColorsMod_hrp3DeletionPattern rowAnnoColorsMod[["pfhrps Call"]] = pfhrpsCallColors topAnnoColors_mod = list() topAnnoColors_mod[["Genes"]] = c("other" = "#56B4E9", hrp = "#009E73", Pf332 = "#D55E00", rRNA = "#FF5AAF", "pfmdr1" = "#7CFFFA") topAnnoColors_mod[["Genes"]] = c("other" = "#56B4E9", hrp = "#8400CD", Pf332 = "#D55E00", rRNA = "#FF5AAF", "pfmdr1" = "#7CFFFA") topAnnoColors_mod[["Genomic Region"]] = c("Chr11/13 Duplicated Region" = "#0072B2", "Subtelomere" = "#E69F00", "Chr5 Duplication" = "#EF0096") rowAnnoDf_hrp3_deleted_sorted = rowAnnoDf_hrp3_deleted %>% as_tibble() %>% mutate(rowID = row_number()) %>% #mutate(Pattern = factor(Pattern, levels = c("11++/13-", "5++/13-", "11/13-TARE1", "13-"))) %>% #mutate(Pattern = gsub("11/13-TARE1", "13-")) %>% mutate(Pattern = factor(Pattern, levels = c("13-11++", "13-5++", "13-TARE1", "13-"))) %>% arrange(Pattern, continent, hrpCall, hclustOutputOrder) %>% rename("pfhrps Call" = hrpCall) rowAnnoDf_hrp3_deleted_sortedDf = rowAnnoDf_hrp3_deleted_sorted %>% select(-rowID, -hclustOutputOrder) %>% as.data.frame() allBasicInfo_filt_sp_mat_noLabs = allBasicInfo_filt_sp_mat_hrp3_deleted rownames(allBasicInfo_filt_sp_mat_noLabs) = NULL colnames(allBasicInfo_filt_sp_mat_noLabs) = NULL allBasicInfo_filt_sp_mat_noLabs_chr08 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_08_", colnames(allBasicInfo_filt_sp_mat))] #08: 1290365 - 1387982 1,290kb:1,387kb allBasicInfo_filt_sp_mat_noLabs_chr11 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_11_", colnames(allBasicInfo_filt_sp_mat))] #11: 1897157 - 2003328 1,897kb:2,003kb allBasicInfo_filt_sp_mat_noLabs_chr13 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_13_", colnames(allBasicInfo_filt_sp_mat))] #13: 2769916 - 2844777 2,769kb:2,844kb #05: 944389 - 988747 944kb:988kb #08: 1290365 - 1387982 1,290kb:1,387kb #11: 1897157 - 2003328 1,897kb:2,003kb #13: 2769916 - 2844777 2,769kb:2,844kb allBasicInfo_filt_sp_mat_noLabs_chr11_sorted = allBasicInfo_filt_sp_mat_noLabs_chr11[rowAnnoDf_hrp3_deleted_sorted$rowID,] allBasicInfo_filt_sp_mat_noLabs_chr13_sorted = allBasicInfo_filt_sp_mat_noLabs_chr13[rowAnnoDf_hrp3_deleted_sorted$rowID,] rowAnnoDf_hrp3_deleted_sortedDf_mod = rowAnnoDf_hrp3_deleted_sortedDf rowAnnoDf_hrp3_deleted_sortedDf_mod = rowAnnoDf_hrp3_deleted_sortedDf_mod%>% rename("pfhrp3- Pattern" = "Pattern") annotationTextSize = 20 sideAnno = rowAnnotation( df = rowAnnoDf_hrp3_deleted_sortedDf_mod, col = rowAnnoColorsMod, gp = gpar(col = "grey10"), simple_anno_size = unit(1.5, "cm"), annotation_name_gp = gpar(fontsize = annotationTextSize), annotation_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold") ), na_col = c("#99999900"), gap = unit(0.1, "cm") ) topAnnoDf = regions[,c("inGene", "genomicRegion", "chrom")] %>% as.data.frame() topAnnoDf_chr08 = topAnnoDf %>% filter(grepl("_08_",chrom)) %>% select(-chrom) topAnnoDf_chr11 = topAnnoDf %>% filter(grepl("_11_",chrom)) %>% select(-chrom) topAnnoDf_chr13 = topAnnoDf %>% filter(grepl("_13_",chrom)) %>% select(-chrom) topAnnoDf_chr11_mod = topAnnoDf_chr11 %>% rename("Genomic Region" = genomicRegion, "Genes" = "inGene") %>% mutate(Genes = ifelse(Genes, "other", NA)) %>% mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`))%>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`)) topAnnoDf_chr13_mod = topAnnoDf_chr13 %>% rename("Genomic Region" = genomicRegion, "Genes" = "inGene")%>% mutate(Genes = ifelse(Genes, "other", NA)) %>% mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`)) %>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`)) topAnno_chr11 = HeatmapAnnotation( df = topAnnoDf_chr11_mod, col = topAnnoColors_mod, annotation_name_gp = gpar(fontsize = annotationTextSize), annotation_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold") ), annotation_name_side = "left", show_annotation_name = T, na_col = "#FFFFFF00", gap = unit(0.1, "cm") ) topAnno_chr13 = HeatmapAnnotation( df = topAnnoDf_chr13_mod, col = topAnnoColors_mod, annotation_name_gp = gpar(fontsize = annotationTextSize), annotation_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold") ), annotation_name_side = "left", show_annotation_name = F, na_col = "#FFFFFF00", gap = unit(0.1, "cm") ) library(circlize) col_fun = colorRamp2(c(0, 1, 2), c(heat.colors(3))) allCoverageHeatMap_chr11 = Heatmap( allBasicInfo_filt_sp_mat_noLabs_chr11_sorted, cluster_columns = F, cluster_rows = F, col = col_fun, name = "coverage", top_annotation = topAnno_chr11, left_annotation = sideAnno, row_dend_width = unit(5, "cm"), column_dend_height = unit(5, "cm"), heatmap_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold"), title = "coverage", at = c(0, 0.5, 1, 1.5, 2), labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x") ), column_title = "Chr11[1,897kb:2,003kb]", column_title_gp = gpar(fontsize = 20, fontface = "italic") ) allCoverageHeatMap_chr13 = Heatmap( allBasicInfo_filt_sp_mat_noLabs_chr13_sorted, cluster_columns = F, cluster_rows = F, col = col_fun, name = "coverage", top_annotation = topAnno_chr13, # left_annotation = sideAnno, row_dend_width = unit(5, "cm"), column_dend_height = unit(5, "cm"), heatmap_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold", title = "coverage", at = c(0, 0.5, 1, 1.5, 2), labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x")) ), column_title = " Chr13[2,769kb:2,844kb] pfhrp3", column_title_gp = gpar(fontsize = 20, fontface = "italic") ) ``` ### Reading in chromosome 5 pfmdr1 dup region ```{r} cov = readr::read_tsv("../meta/allCov_summaryStats.tab.txt.gz") allReports_chr5 = readr::read_tsv("deletion_patterns/stableWindows_05_regionOfInterestNarrow_full_step150_windowSize200/popClustering/reports/allBasicInfo.tab.txt.gz") %>% filter(start >= 944389) %>% #filter(sample %in% allMetaDeletionCalls_Hrp3pattern2_samples$sample) %>% filter(sample %in% rownames(allBasicInfo_filt_sp_mat_hrp3_deleted)) %>% mutate(inGene = !is.na(extraField0) ) %>% left_join(cov) %>% mutate(medianCov = median(perBaseCoverage), meanCov = mean(perBaseCoverage)) %>% mutate(perBaseCoverageNorm = ifelse(inGene, perBaseCoverage/medianPerBaseCov_inGenes, perBaseCoverage/medianPerBaseCov_notInGenes)) %>% mutate(perBaseCoverageNormRounded = ifelse(perBaseCoverageNorm >0.10 & perBaseCoverageNorm <= 1, 1, perBaseCoverageNorm)) %>% mutate(perBaseCoverageNormRounded = round(perBaseCoverageNormRounded)) allReports_chr5_sp = allReports_chr5 %>% select(sample, name, perBaseCoverageNormRounded) %>% spread(name, perBaseCoverageNormRounded) allReports_chr5_sp_mat = as.matrix(allReports_chr5_sp[,2:ncol(allReports_chr5_sp)]) rownames(allReports_chr5_sp_mat) = allReports_chr5_sp$sample allReports_chr5_sp_mat = allReports_chr5_sp_mat[match(rownames(allBasicInfo_filt_sp_mat_hrp3_deleted)[rowAnnoDf_hrp3_deleted_sorted$rowID], rownames(allReports_chr5_sp_mat)), ] allReports_chr5_sp_mat[allReports_chr5_sp_mat >2] = 2 topAnno_chr05 = allReports_chr5 %>% filter(sample == .$sample[1]) %>% select(name, extraField0) %>% rename(`Gene Description` = extraField0) %>% mutate(`Gene Description` = gsub(".*description=", "", `Gene Description`))%>% mutate(`Gene Description` = gsub("\\].*", "", `Gene Description`)) %>% mutate(`Gene Description` = ifelse(grepl("PHIST", `Gene Description`), gsub("\\).*", "", gsub(".*PHIST", "PHIST", `Gene Description`)), `Gene Description`)) topAnno_chr05Df = topAnno_chr05 %>% separate(name, into = c("chrom", "start", "end"), remove = F, convert = T, sep = "-") %>% mutate(`Genomic Region` = ifelse(start >= 952474 & end <= 979431, "Chr5 Duplication", NA)) %>% select(-name, -chrom, -start, -end) %>% as.data.frame() topAnno_chr05Colors = createColorListFromDf(topAnno_chr05Df) # 05: 944389 - 988747 944kb:988kb topAnno_chr05Df_mod = topAnno_chr05Df %>% select(`Gene Description`, `Genomic Region`) %>% mutate(Genes = ifelse(is.na(`Gene Description`), NA, "other")) %>% mutate(Genes = ifelse(`Gene Description` == "multidrug resistance protein 1", "pfmdr1", Genes)) %>% select(`Genes`, `Genomic Region`) topAnno_chr05HM = HeatmapAnnotation( df = topAnno_chr05Df_mod, col = topAnnoColors_mod, annotation_name_gp = gpar(fontsize = annotationTextSize), annotation_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold") ), annotation_name_side = "left", na_col = c("#99999900"), gap = unit(0.1, "cm"), show_annotation_name = F ) allReports_chr5_sp_mat_nolab = allReports_chr5_sp_mat colnames(allReports_chr5_sp_mat_nolab) = NULL rownames(allReports_chr5_sp_mat_nolab) = NULL allReports_chr5_sp_mat_hm = Heatmap( allReports_chr5_sp_mat_nolab, cluster_columns = F, cluster_rows = F, col = col_fun, name = "coverage", top_annotation = topAnno_chr05HM, #right_annotation = sideAnno, row_dend_width = unit(5, "cm"), column_dend_height = unit(5, "cm"), heatmap_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold", title = "coverage", at = c(0, 0.5, 1, 1.5, 2), labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x")) ), column_title = "Chr05[944kb:988kb]", column_title_gp = gpar(fontsize = 20, fontface = "italic") ) ``` ```{r} #| fig-column: screen-inset #| fig-height: 12 #| fig-width: 16 #05: 944389 - 988747 944kb:988kb #11: 1897157 - 2003328 1,897kb:2,003kb #13: 2769916 - 2844777 2,769kb:2,844kb hms_list = allCoverageHeatMap_chr11 + allCoverageHeatMap_chr13 + allReports_chr5_sp_mat_hm draw(hms_list, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom", ht_gap = unit(2, "cm"), #padding = unit(c(5.5 *5*2, 5.5, 5.5, 5.5), "points") ) ``` ```{r} #| results: hide #05: 944389 - 988747 944kb:988kb #11: 1897157 - 2003328 1,897kb:2,003kb #13: 2769916 - 2844777 2,769kb:2,844kb hms_list = allCoverageHeatMap_chr11 + allCoverageHeatMap_chr13 + allReports_chr5_sp_mat_hm pdf("allHeatmap_byChrom_filtered_chr11_chr13_chr5_sorted.pdf", useDingbats = F, width = 16, height = 12) draw(hms_list, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom", ht_gap = unit(2, "cm"), padding = unit(c(5.5 *5, 5.5, 5.5, 5.5), "points") ) dev.off() ``` ```{r} #| echo: false #| results: asis cat(createDownloadLink("allHeatmap_byChrom_filtered_chr11_chr13_chr5_sorted.pdf")) ``` ## Coverage of genomic regions in _pfhrp2_ deleted strains Displaying from Pf3D7 genomic version=2015-06-18 of the following chromosome regions * chromosome 08: 1290365 - 1387982 1,290kb:1,387kb * chromosome 11: 1897157 - 2003328 1,897kb:2,003kb * chromosome 13: 2769916 - 2844777 2,769kb:2,844kb ```{r} allBasicInfo_filt_sp_mat_hrp2_deleted = allBasicInfo_filt_sp_mat[rownames(allBasicInfo_filt_sp_mat) %in% allMetaDeletionCalls_hrp2_deleted$sample, ] metaSelected_hrp2_deleted = allMetaDeletionCalls_hrp2_deleted[match(rownames(allBasicInfo_filt_sp_mat_hrp2_deleted), allMetaDeletionCalls_hrp2_deleted$sample), ] allBasicInfo_filt_sp_mat_hrp2_deleted_hclust = hclust(dist(allBasicInfo_filt_sp_mat_hrp2_deleted)) allBasicInfo_filt_sp_mat_hrp2_deleted_hclust_ordering = tibble( sample = rownames(allBasicInfo_filt_sp_mat_hrp2_deleted)[allBasicInfo_filt_sp_mat_hrp2_deleted_hclust$order], hclustInputOrder = allBasicInfo_filt_sp_mat_hrp2_deleted_hclust$order, hclustOutputOrder = 1:nrow(allBasicInfo_filt_sp_mat_hrp2_deleted) ) rowAnnoDf_hrp2_deleted = metaSelected_hrp2_deleted %>% left_join(allBasicInfo_filt_sp_mat_hrp2_deleted_hclust_ordering) %>% select("Pattern", "secondaryRegion", "hrpCall", hclustOutputOrder) %>% rename(continent = secondaryRegion) %>% as.data.frame() rowAnnoColorsMod = rowAnnoColors rowAnnoColorsMod[["Pattern"]] = rowAnnoColorsMod_hrp3DeletionPattern rowAnnoColorsMod[["pfhrp3- Pattern"]] = rowAnnoColorsMod_hrp3DeletionPattern rowAnnoColorsMod[["DeletionPattern"]] = rowAnnoColorsMod_hrp3DeletionPattern rowAnnoColorsMod[["pfhrps Call"]] = pfhrpsCallColors topAnnoColors_mod = list() topAnnoColors_mod[["Genes"]] = c("other" = "#56B4E9", hrp = "#009E73", Pf332 = "#D55E00", rRNA = "#FF5AAF", "pfmdr1" = "#7CFFFA") topAnnoColors_mod[["Genes"]] = c("other" = "#56B4E9", hrp = "#8400CD", Pf332 = "#D55E00", rRNA = "#FF5AAF", "pfmdr1" = "#7CFFFA") topAnnoColors_mod[["Genomic Region"]] = c("Chr11/13 Duplicated Region" = "#0072B2", "Subtelomere" = "#E69F00", "Chr5 Duplication" = "#EF0096") rowAnnoDf_hrp2_deleted_sorted = rowAnnoDf_hrp2_deleted %>% as_tibble() %>% mutate(rowID = row_number()) %>% # mutate(Pattern = factor(Pattern, levels = c("11++/13-", "5++/13-", "11/13-TARE1", "11-TARE1/13"))) %>% # mutate(Pattern = factor(Pattern, levels = c("13-11++", "13-5++", "13-TARE1", "13-"))) %>% mutate(Pattern = factor(Pattern, levels = c("13-11++"))) %>% arrange(Pattern, continent, hrpCall, hclustOutputOrder) %>% rename("pfhrps Call" = hrpCall) rowAnnoDf_hrp2_deleted_sortedDf = rowAnnoDf_hrp2_deleted_sorted %>% select(-rowID,-hclustOutputOrder) %>% as.data.frame() allBasicInfo_filt_sp_mat_noLabs = allBasicInfo_filt_sp_mat_hrp2_deleted rownames(allBasicInfo_filt_sp_mat_noLabs) = NULL colnames(allBasicInfo_filt_sp_mat_noLabs) = NULL allBasicInfo_filt_sp_mat_noLabs_chr08 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_08_", colnames(allBasicInfo_filt_sp_mat))] #08: 1290365 - 1387982 1,290kb:1,387kb allBasicInfo_filt_sp_mat_noLabs_chr11 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_11_", colnames(allBasicInfo_filt_sp_mat))] #11: 1897157 - 2003328 1,897kb:2,003kb allBasicInfo_filt_sp_mat_noLabs_chr13 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_13_", colnames(allBasicInfo_filt_sp_mat))] #13: 2769916 - 2844777 2,769kb:2,844kb #08: 1290365 - 1387982 1,290kb:1,387kb #11: 1897157 - 2003328 1,897kb:2,003kb #13: 2769916 - 2844777 2,769kb:2,844kb allBasicInfo_filt_sp_mat_noLabs_chr08_sorted = allBasicInfo_filt_sp_mat_noLabs_chr08[rowAnnoDf_hrp2_deleted_sorted$rowID,] allBasicInfo_filt_sp_mat_noLabs_chr11_sorted = allBasicInfo_filt_sp_mat_noLabs_chr11[rowAnnoDf_hrp2_deleted_sorted$rowID,] allBasicInfo_filt_sp_mat_noLabs_chr13_sorted = allBasicInfo_filt_sp_mat_noLabs_chr13[rowAnnoDf_hrp2_deleted_sorted$rowID,] rowAnnoDf_hrp2_deleted_sortedDf_mod = rowAnnoDf_hrp2_deleted_sortedDf rowAnnoDf_hrp2_deleted_sortedDf_mod = rowAnnoDf_hrp2_deleted_sortedDf_mod%>% rename("pfhrp3- Pattern" = "Pattern") annotationTextSize = 20 sideAnno = rowAnnotation( df = rowAnnoDf_hrp2_deleted_sortedDf_mod, col = rowAnnoColorsMod, gp = gpar(col = "grey10"), simple_anno_size = unit(1.5, "cm"), annotation_name_gp = gpar(fontsize = annotationTextSize), annotation_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold") ), na_col = c("#99999900"), gap = unit(0.1, "cm") ) topAnnoDf = regions[,c("inGene", "genomicRegion", "chrom")] %>% as.data.frame() topAnnoDf_chr08 = topAnnoDf %>% filter(grepl("_08_",chrom)) %>% select(-chrom) topAnnoDf_chr11 = topAnnoDf %>% filter(grepl("_11_",chrom)) %>% select(-chrom) topAnnoDf_chr13 = topAnnoDf %>% filter(grepl("_13_",chrom)) %>% select(-chrom) topAnnoDf_chr08_mod = topAnnoDf_chr08 %>% rename("Genomic Region" = genomicRegion, "Genes" = "inGene") %>% mutate(Genes = ifelse(Genes, "other", NA)) %>% mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`))%>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`)) %>% mutate(`Genomic Region` = NA) topAnnoDf_chr11_mod = topAnnoDf_chr11 %>% rename("Genomic Region" = genomicRegion, "Genes" = "inGene") %>% mutate(Genes = ifelse(Genes, "other", NA)) %>% mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`)) %>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`)) topAnnoDf_chr13_mod = topAnnoDf_chr13 %>% rename("Genomic Region" = genomicRegion, "Genes" = "inGene")%>% mutate(Genes = ifelse(Genes, "other", NA)) %>% mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`)) %>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`)) topAnno_chr08 = HeatmapAnnotation( df = topAnnoDf_chr08_mod, col = topAnnoColors_mod, annotation_name_gp = gpar(fontsize = annotationTextSize), annotation_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold") ), annotation_name_side = "left", show_annotation_name = T, na_col = "#FFFFFF00", gap = unit(0.1, "cm") ) topAnno_chr11 = HeatmapAnnotation( df = topAnnoDf_chr11_mod, col = topAnnoColors_mod, annotation_name_gp = gpar(fontsize = annotationTextSize), annotation_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold") ), annotation_name_side = "left", show_annotation_name = F, na_col = "#FFFFFF00", gap = unit(0.1, "cm") ) topAnno_chr13 = HeatmapAnnotation( df = topAnnoDf_chr13_mod, col = topAnnoColors_mod, annotation_name_gp = gpar(fontsize = annotationTextSize), annotation_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold") ), annotation_name_side = "left", show_annotation_name = F, na_col = "#FFFFFF00", gap = unit(0.1, "cm") ) library(circlize) col_fun = colorRamp2(c(0, 1, 2), c(heat.colors(3))) allCoverageHeatMap_chr08 = Heatmap( allBasicInfo_filt_sp_mat_noLabs_chr08_sorted, cluster_columns = F, cluster_rows = F, col = col_fun, name = "coverage", top_annotation = topAnno_chr08, left_annotation = sideAnno, row_dend_width = unit(5, "cm"), column_dend_height = unit(5, "cm"), heatmap_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold"), title = "coverage", at = c(0, 0.5, 1, 1.5, 2), labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x") ), column_title = "Chr08[1,290kb:1,387kb] pfhrp2", column_title_gp = gpar(fontsize = 30, fontface = "italic") ) allCoverageHeatMap_chr11 = Heatmap( allBasicInfo_filt_sp_mat_noLabs_chr11_sorted, cluster_columns = F, cluster_rows = F, col = col_fun, name = "coverage", top_annotation = topAnno_chr11, #left_annotation = sideAnno, row_dend_width = unit(5, "cm"), column_dend_height = unit(5, "cm"), heatmap_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold"), title = "coverage", at = c(0, 0.5, 1, 1.5, 2), labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x") ), column_title = "Chr11[1,897kb:2,003kb]", column_title_gp = gpar(fontsize = 30, fontface = "italic") ) allCoverageHeatMap_chr13 = Heatmap( allBasicInfo_filt_sp_mat_noLabs_chr13_sorted, cluster_columns = F, cluster_rows = F, col = col_fun, name = "coverage", top_annotation = topAnno_chr13, # left_annotation = sideAnno, row_dend_width = unit(5, "cm"), column_dend_height = unit(5, "cm"), heatmap_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold", title = "coverage", at = c(0, 0.5, 1, 1.5, 2), labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x")) ), column_title = "Chr13[2,769kb:2,844kb] pfhrp3", column_title_gp = gpar(fontsize = 30, fontface = "italic") ) ``` ```{r} #| fig-column: screen-inset #| fig-height: 12 #| fig-width: 20 #08: 1290365 - 1387982 1,290kb:1,387kb #11: 1897157 - 2003328 1,897kb:2,003kb #13: 2769916 - 2844777 2,769kb:2,844kb hms_list = allCoverageHeatMap_chr08 + allCoverageHeatMap_chr11 + allCoverageHeatMap_chr13 draw(hms_list, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom", ht_gap = unit(2, "cm"), #padding = unit(c(5.5 *5*2, 5.5, 5.5, 5.5), "points") ) ``` ```{r} #| results: hide #08: 1290365 - 1387982 1,290kb:1,387kb #11: 1897157 - 2003328 1,897kb:2,003kb #13: 2769916 - 2844777 2,769kb:2,844kb pdf("allHeatmap_byChrom_filtered_chr08_chr11_chr13_sorted_hrp2_deleted.pdf", useDingbats = F, width = 20, height = 12) draw(hms_list, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom", ht_gap = unit(2, "cm"), padding = unit(c(5.5 *5, 5.5, 5.5, 5.5 *5*2.5), "points") ) dev.off() ``` ```{r} #| echo: false #| results: asis cat(createDownloadLink("allHeatmap_byChrom_filtered_chr08_chr11_chr13_sorted_hrp2_deleted.pdf")) ``` ## Coverage of genomic regions in chromosome 11 deleted strains Displaying from Pf3D7 genomic version=2015-06-18 of the following chromosome regions * chromosome 08: 1290365 - 1387982 1,290kb:1,387kb * chromosome 11: 1897157 - 2003328 1,897kb:2,003kb * chromosome 13: 2769916 - 2844777 2,769kb:2,844kb ```{r} allBasicInfo_filt_sp_mat_chr11_deleted = allBasicInfo_filt_sp_mat[rownames(allBasicInfo_filt_sp_mat) %in% allMetaDeletionCalls_chr11_deleted$sample, ] metaSelected_chr11_deleted = allMetaDeletionCalls_chr11_deleted[match(rownames(allBasicInfo_filt_sp_mat_chr11_deleted), allMetaDeletionCalls_chr11_deleted$sample), ] allBasicInfo_filt_sp_mat_chr11_deleted_hclust = hclust(dist(allBasicInfo_filt_sp_mat_chr11_deleted)) allBasicInfo_filt_sp_mat_chr11_deleted_hclust_ordering = tibble( sample = rownames(allBasicInfo_filt_sp_mat_chr11_deleted)[allBasicInfo_filt_sp_mat_chr11_deleted_hclust$order], hclustInputOrder = allBasicInfo_filt_sp_mat_chr11_deleted_hclust$order, hclustOutputOrder = 1:nrow(allBasicInfo_filt_sp_mat_chr11_deleted) ) rowAnnoDf_chr11_deleted = metaSelected_chr11_deleted %>% left_join(allBasicInfo_filt_sp_mat_chr11_deleted_hclust_ordering) %>% select("Pattern", "secondaryRegion", "hrpCall", hclustOutputOrder) %>% rename(continent = secondaryRegion) %>% as.data.frame() rowAnnoColorsMod = rowAnnoColors rowAnnoColorsMod[["Pattern"]] = rowAnnoColorsMod_hrp3DeletionPattern rowAnnoColorsMod[["pfhrp3- Pattern"]] = rowAnnoColorsMod_hrp3DeletionPattern rowAnnoColorsMod[["DeletionPattern"]] = rowAnnoColorsMod_hrp3DeletionPattern rowAnnoColorsMod[["pfhrps Call"]] = pfhrpsCallColors topAnnoColors_mod = list() topAnnoColors_mod[["Genes"]] = c("other" = "#56B4E9", hrp = "#009E73", Pf332 = "#D55E00", rRNA = "#FF5AAF", "pfmdr1" = "#7CFFFA") topAnnoColors_mod[["Genes"]] = c("other" = "#56B4E9", hrp = "#8400CD", Pf332 = "#D55E00", rRNA = "#FF5AAF", "pfmdr1" = "#7CFFFA") topAnnoColors_mod[["Genomic Region"]] = c("Chr11/13 Duplicated Region" = "#0072B2", "Subtelomere" = "#E69F00", "Chr5 Duplication" = "#EF0096") rowAnnoDf_chr11_deleted_sorted = rowAnnoDf_chr11_deleted %>% as_tibble() %>% mutate(rowID = row_number()) %>% # mutate(Pattern = factor(Pattern, levels = c("11++/13-", "5++/13-", "11/13-TARE1", "11-TARE1/13"))) %>% mutate(Pattern = ifelse(is.na(Pattern), "13++11-", Pattern)) %>% mutate(Pattern = factor(Pattern, levels = c("13-11++", "11-TARE1", "13++11-"))) %>% arrange(Pattern, continent, hrpCall, hclustOutputOrder) %>% #arrange(Pattern, continent, hrpCall) %>% rename("pfhrps Call" = hrpCall) %>% select(-hclustOutputOrder) rowAnnoDf_chr11_deleted_sortedDf = rowAnnoDf_chr11_deleted_sorted %>% select(-rowID) %>% as.data.frame() allBasicInfo_filt_sp_mat_noLabs = allBasicInfo_filt_sp_mat_chr11_deleted rownames(allBasicInfo_filt_sp_mat_noLabs) = NULL colnames(allBasicInfo_filt_sp_mat_noLabs) = NULL allBasicInfo_filt_sp_mat_noLabs_chr08 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_08_", colnames(allBasicInfo_filt_sp_mat))] #08: 1290365 - 1387982 1,290kb:1,387kb allBasicInfo_filt_sp_mat_noLabs_chr11 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_11_", colnames(allBasicInfo_filt_sp_mat))] #11: 1897157 - 2003328 1,897kb:2,003kb allBasicInfo_filt_sp_mat_noLabs_chr13 = allBasicInfo_filt_sp_mat_noLabs[,grepl("_13_", colnames(allBasicInfo_filt_sp_mat))] #13: 2769916 - 2844777 2,769kb:2,844kb #08: 1290365 - 1387982 1,290kb:1,387kb #11: 1897157 - 2003328 1,897kb:2,003kb #13: 2769916 - 2844777 2,769kb:2,844kb allBasicInfo_filt_sp_mat_noLabs_chr08_sorted = allBasicInfo_filt_sp_mat_noLabs_chr08[rowAnnoDf_chr11_deleted_sorted$rowID,] allBasicInfo_filt_sp_mat_noLabs_chr11_sorted = allBasicInfo_filt_sp_mat_noLabs_chr11[rowAnnoDf_chr11_deleted_sorted$rowID,] allBasicInfo_filt_sp_mat_noLabs_chr13_sorted = allBasicInfo_filt_sp_mat_noLabs_chr13[rowAnnoDf_chr11_deleted_sorted$rowID,] rowAnnoDf_chr11_deleted_sortedDf_mod = rowAnnoDf_chr11_deleted_sortedDf rowAnnoDf_chr11_deleted_sortedDf_mod = rowAnnoDf_chr11_deleted_sortedDf_mod%>% rename("pfhrp3- Pattern" = "Pattern") annotationTextSize = 20 sideAnno = rowAnnotation( df = rowAnnoDf_chr11_deleted_sortedDf, col = rowAnnoColorsMod, gp = gpar(col = "grey10"), simple_anno_size = unit(1.5, "cm"), annotation_name_gp = gpar(fontsize = annotationTextSize), annotation_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold") ), na_col = c("#99999900"), gap = unit(0.1, "cm") ) topAnnoDf = regions[,c("inGene", "genomicRegion", "chrom")] %>% as.data.frame() topAnnoDf_chr08 = topAnnoDf %>% filter(grepl("_08_",chrom)) %>% select(-chrom) topAnnoDf_chr11 = topAnnoDf %>% filter(grepl("_11_",chrom)) %>% select(-chrom) topAnnoDf_chr13 = topAnnoDf %>% filter(grepl("_13_",chrom)) %>% select(-chrom) topAnnoDf_chr08_mod = topAnnoDf_chr08 %>% rename("Genomic Region" = genomicRegion, "Genes" = "inGene") %>% mutate(Genes = ifelse(Genes, "other", NA)) %>% mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`))%>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`)) %>% mutate(`Genomic Region` = NA) topAnnoDf_chr11_mod = topAnnoDf_chr11 %>% rename("Genomic Region" = genomicRegion, "Genes" = "inGene") %>% mutate(Genes = ifelse(Genes, "other", NA)) %>% mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`)) %>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`)) topAnnoDf_chr13_mod = topAnnoDf_chr13 %>% rename("Genomic Region" = genomicRegion, "Genes" = "inGene")%>% mutate(Genes = ifelse(Genes, "other", NA)) %>% mutate(Genes = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "rRNA"), `Genomic Region`, Genes)) %>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("hrp", "Pf332", "After Duplicated Region"), "Subtelomere", `Genomic Region`))%>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("rRNA", "Duplicated Region"), "Chr11/13 Duplicated Region", `Genomic Region`)) %>% mutate(`Genomic Region` = ifelse(`Genomic Region` %in% c("other"), NA, `Genomic Region`)) topAnno_chr08 = HeatmapAnnotation( df = topAnnoDf_chr08_mod, col = topAnnoColors_mod, annotation_name_gp = gpar(fontsize = annotationTextSize), annotation_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold") ), annotation_name_side = "left", show_annotation_name = T, na_col = "#FFFFFF00", gap = unit(0.1, "cm") ) topAnno_chr11 = HeatmapAnnotation( df = topAnnoDf_chr11_mod, col = topAnnoColors_mod, annotation_name_gp = gpar(fontsize = annotationTextSize), annotation_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold") ), annotation_name_side = "left", show_annotation_name = F, na_col = "#FFFFFF00", gap = unit(0.1, "cm") ) topAnno_chr13 = HeatmapAnnotation( df = topAnnoDf_chr13_mod, col = topAnnoColors_mod, annotation_name_gp = gpar(fontsize = annotationTextSize), annotation_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold") ), annotation_name_side = "left", show_annotation_name = F, na_col = "#FFFFFF00", gap = unit(0.1, "cm") ) library(circlize) col_fun = colorRamp2(c(0, 1, 2), c(heat.colors(3))) allCoverageHeatMap_chr08 = Heatmap( allBasicInfo_filt_sp_mat_noLabs_chr08_sorted, cluster_columns = F, cluster_rows = F, col = col_fun, name = "coverage", top_annotation = topAnno_chr08, left_annotation = sideAnno, row_dend_width = unit(5, "cm"), column_dend_height = unit(5, "cm"), heatmap_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold"), title = "coverage", at = c(0, 0.5, 1, 1.5, 2), labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x") ), column_title = "Chr08[1,290kb:1,387kb] pfhrp2", column_title_gp = gpar(fontsize = 30, fontface = "italic") ) allCoverageHeatMap_chr11 = Heatmap( allBasicInfo_filt_sp_mat_noLabs_chr11_sorted, cluster_columns = F, cluster_rows = F, col = col_fun, name = "coverage", top_annotation = topAnno_chr11, #left_annotation = sideAnno, row_dend_width = unit(5, "cm"), column_dend_height = unit(5, "cm"), heatmap_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold"), title = "coverage", at = c(0, 0.5, 1, 1.5, 2), labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x") ), column_title = "Chr11[1,897kb:2,003kb]", column_title_gp = gpar(fontsize = 30, fontface = "italic") ) allCoverageHeatMap_chr13 = Heatmap( allBasicInfo_filt_sp_mat_noLabs_chr13_sorted, cluster_columns = F, cluster_rows = F, col = col_fun, name = "coverage", top_annotation = topAnno_chr13, # left_annotation = sideAnno, row_dend_width = unit(5, "cm"), column_dend_height = unit(5, "cm"), heatmap_legend_param = list( labels_gp = gpar(fontsize = annotationTextSize), title_gp = gpar(fontsize = annotationTextSize, fontface = "bold", title = "coverage", at = c(0, 0.5, 1, 1.5, 2), labels = c("0", "0.5x", "1.0x", "1.5x", ">=2x")) ), column_title = "Chr13[2,769kb:2,844kb] pfhrp3", column_title_gp = gpar(fontsize = 30, fontface = "italic") ) ``` ```{r} #| fig-column: screen-inset #| fig-height: 12 #| fig-width: 20 #08: 1290365 - 1387982 1,290kb:1,387kb #11: 1897157 - 2003328 1,897kb:2,003kb #13: 2769916 - 2844777 2,769kb:2,844kb hms_list = allCoverageHeatMap_chr08 + allCoverageHeatMap_chr11 + allCoverageHeatMap_chr13 draw(hms_list, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom", ht_gap = unit(2, "cm"), #padding = unit(c(5.5 *5*2, 5.5, 5.5, 5.5), "points") ) ``` ```{r} #| results: hide #08: 1290365 - 1387982 1,290kb:1,387kb #11: 1897157 - 2003328 1,897kb:2,003kb #13: 2769916 - 2844777 2,769kb:2,844kb pdf("allHeatmap_byChrom_filtered_chr08_chr11_chr13_sorted_chr11_deleted.pdf", useDingbats = F, width = 20, height = 12) draw(hms_list, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom", ht_gap = unit(2, "cm"), padding = unit(c(5.5, 5.5, 5.5, 5.5 *5*2.5), "points") ) dev.off() ``` ```{r} #| echo: false #| results: asis cat(createDownloadLink("allHeatmap_byChrom_filtered_chr08_chr11_chr13_sorted_chr11_deleted.pdf")) ```