Processing Samples for chr13 TARE1 presence

Set up

Downloads

meta.tab.txtmetaByBioSample

Reading in data

Code
allMetaSamplesByBio = readr::read_tsv("../../meta/metadata/metaByBioSample.tab.txt")
allMetaSamples = readr::read_tsv("../../meta/metadata/meta.tab.txt")
allMetaDeletionCalls = readr::read_tsv("../metaSelected.tab.txt")
allMetaDeletionCalls_possiblyHRP2Deleted = allMetaDeletionCalls %>% 
  filter(possiblyHRP2Deleted)
allMetaDeletionCalls_possiblyChr11Deleted = allMetaDeletionCalls %>% 
  filter(possiblyChr11Deleted)
allMetaDeletionCalls_Hrp3pattern2 = readr::read_tsv("../allMetaDeletionCalls_Hrp3pattern2.tab.txt")

realmccoilCoiCalls = readr::read_tsv("../wgs_variants/THEREALMcCOIL/categorical_method/real_mccoil_COI_calls.tsv")

realmccoilCoiCalls_poly = realmccoilCoiCalls %>% 
  filter(random_median != 1 | topHE_median != 1) %>% 
  left_join(allMetaSamples %>% 
              select(sample, BiologicalSample))

Creating a region to investigate on chromosome 13

Code
finalHRPII_HRPIII_windows = readr::read_tsv("../../windowAnalysis/windows/finalHRPII_HRPIII_windows_withTuned.bed", col_names = F) %>% 
  mutate(genomicID = paste0(X1, "-", X2, "-", X3)) %>% 
  mutate(chrom = X1, len = X3 -X2) %>% 
  rename(name = X4)

finalHRPII_HRPIII_windows_investTelemeraseHealing = finalHRPII_HRPIII_windows %>% 
  filter("Pf3D7_13_v3" == X1, X2 >= 2813887)

write_tsv(finalHRPII_HRPIII_windows_investTelemeraseHealing %>% 
            select(1:7), "finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_largeRegions.bed", col_names = F)
Code
finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full = finalHRPII_HRPIII_windows %>% 
  filter("Pf3D7_13_v3" == X1, X2 >= 2817793)

finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out = finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full %>%
  group_by(X1) %>% summarise(X2 = min(X2),
                             X3 = max(X3)) %>%
  mutate(name = paste0(X1, "-", X2, "-", X3)) %>%
  mutate(len = X3 - X2,
         strand = "+")


write_tsv(finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out %>% 
            select(1:6), "finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out.bed", col_names = F)

Create sub-windows within this large window to investigate

Code
elucidator createWindowsInRegions --bed finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out.bed --step 1000 --windowSize 1000 --minLen 50 | elucidator bedGetIntersectingGenesInGff --gff /tank/data/genomes/plasmodium/genomes/pf/info/gff/Pf3D7.gff --extraAttributes description  --bed STDIN --overWrite --out finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000.bed

elucidator createWindowsInRegions --bed finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out.bed --step 100 --windowSize 100 --minLen 50 | elucidator bedGetIntersectingGenesInGff --gff /tank/data/genomes/plasmodium/genomes/pf/info/gff/Pf3D7.gff --extraAttributes description  --bed STDIN --overWrite --out finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step100_windowSize100.bed

rsync -raPh finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000.bed hathawan@calderon.barrel-of-knowledge.info:/tank/data/plasmodium/falciparum/beds/hrps/redesign_2020_11_22
rsync -raPh finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step100_windowSize100.bed hathawan@calderon.barrel-of-knowledge.info:/tank/data/plasmodium/falciparum/beds/hrps/redesign_2020_11_22

rsync -raPh ../allMetaDeletionCalls_Hrp3pattern2_samples.txt hathawan@calderon.barrel-of-knowledge.info:/tank/data/plasmodium/falciparum/beds/hrps/redesign_2020_11_22

Finding regions with TARE1 sequence

Code
nohup elucidator runMultipleCommands --cmdFile runRegionCmds.txt --additionalFields "{DIRNAME}:finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000_NoTrim_keep;{SAMPLE}:/tank/data/plasmodium/falciparum/beds/hrps/redesign_2020_11_22/allMetaDeletionCalls_Hrp3pattern2_samples.txt;{BEDFNP}:\"/tank/data/plasmodium/falciparum/beds/hrps/redesign_2020_11_22/finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000.bed\";{NCPUS}:4 --keepTemporaryFiles --qualCheck 5 --keepImproperMates" --replaceFields --numThreads 11 &

cd finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000_NoTrim_keep 

PathWeaver runProcessClustersOnRecon --overWriteDir --dout popClustering --pat _finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000_NoTrim_keep --numThreads 5  --groupingsFile /tank/data/plasmodium/falciparum/pfdata/metadata/meta.tab.txt --samples /tank/data/plasmodium/falciparum/beds/hrps/redesign_2020_11_22/allMetaDeletionCalls_Hrp3pattern2_samples.txt 



# 5`-3` "TT[CT]AGGGTT[CT]AGGG"
# 3`-5` "CCCT[AG]AACCCT[AG]AA"

elucidator countPWExtractedReadsWithPattern --seqPat "TT[CT]AGGGTT[CT]AGGG","CCCT[AG]AACCCT[AG]AA" --pat _finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000_NoTrim_keep --bedFnp /tank/data/plasmodium/falciparum/beds/hrps/redesign_2020_11_22/finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000.bed  --minReadCounts 1 --numThreads 10 --overWrite --out finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000_countTares.txt --samples /tank/data/plasmodium/falciparum/beds/hrps/redesign_2020_11_22/allMetaDeletionCalls_Hrp3pattern2_samples.txt
Code
nohup elucidator runMultipleCommands --cmdFile runRegionCmds.txt --additionalFields "{DIRNAME}:finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step100_windowSize100_NoTrim_keep;{SAMPLE}:/tank/data/plasmodium/falciparum/beds/hrps/redesign_2020_11_22/allMetaDeletionCalls_Hrp3pattern2_samples.txt;{BEDFNP}:\"/tank/data/plasmodium/falciparum/beds/hrps/redesign_2020_11_22/finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step100_windowSize100.bed\"" --replaceFields --numThreads 11 &

cd finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step100_windowSize100_NoTrim_keep 

PathWeaver runProcessClustersOnRecon --overWriteDir --dout popClustering --pat _finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step100_windowSize100_NoTrim_keep --numThreads 5  --groupingsFile /tank/data/plasmodium/falciparum/pfdata/metadata/meta.tab.txt --samples /tank/data/plasmodium/falciparum/beds/hrps/redesign_2020_11_22/allMetaDeletionCalls_Hrp3pattern2_samples.txt
Code
finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000_countTares = readr::read_tsv("finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000_NoTrim_keep/finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000_countTares.txt")

finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000_countTares_sum = finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000_countTares %>% 
  group_by(sample, region, seqPat) %>% 
  summarise(count = sum(count))

hrp3Pat2_samplesWithTare1 = finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000_countTares_sum %>% 
  ungroup() %>% 
  select(sample, region) %>% 
  unique() %>% 
  rename(breakwithinRegion = region)

Plotting coverage

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


allReports = readr::read_tsv("finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000_NoTrim_keep/popClustering/reports/allBasicInfo.tab.txt.gz") %>% 
  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)) %>% 
  filter(sample %!in% realmccoilCoiCalls_poly$sample)

allReports_sp = allReports %>% 
  select(sample, name, perBaseCoverageNormRounded) %>% 
  spread(name, perBaseCoverageNormRounded)

allReports_sp_mat = as.matrix(allReports_sp[,2:ncol(allReports_sp)])
rownames(allReports_sp_mat) = allReports_sp$sample

allReports_sp_mat[allReports_sp_mat >2] = 2

annotationTextSize = 20

topAnno = allReports %>% 
  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`))

topAnnoDf = topAnno %>% 
  select(-name) %>% 
  as.data.frame()
topAnnoColors = createColorListFromDf(topAnnoDf)

allReports_sp_mat_sampleOrder = hclust(dist(allReports_sp_mat))$order
allReports_sp_mat_sampleOrderDf = tibble(
  sample = rownames(allReports_sp_mat)[allReports_sp_mat_sampleOrder], 
  order = 1:nrow(allReports_sp_mat)
  #order = allReports_sp_mat_sampleOrder
)

metaReSelected = allMetaDeletionCalls[match(rownames(allReports_sp_mat), allMetaDeletionCalls$sample), ] %>% 
  left_join(allReports_sp_mat_sampleOrderDf)

rowAnno = tibble(metaReSelected[,c("sample","country", "order")]) %>% 
  mutate(`TARE1 Present On Chr13` = sample %in% hrp3Pat2_samplesWithTare1$sample) %>%  
  #mutate(`Transposition With 5` = sample %in% samplesWithTransitionToChr5$sample) %>% 
  #select(-order)
  #arrange(`TARE1 Present On Chr13`, `Transposition With 5`, order) %>%
  arrange(order) %>% 
  select(-order)

metaReSelected = metaReSelected[match(rowAnno$sample, metaReSelected$sample),]
allReports_sp_mat = allReports_sp_mat[match(rowAnno$sample, rownames(allReports_sp_mat)), ]



rowAnnoDf = rowAnno %>% 
  select(-sample) %>% 
  as.data.frame()
rowAnnoColors = createColorListFromDf(rowAnnoDf)
sideAnno = rowAnnotation(
  df = rowAnnoDf,
  col = rowAnnoColors,
  gp = gpar(col = "grey10"),
  annotation_name_gp = gpar(fontsize = annotationTextSize),
  annotation_legend_param = list(
    labels_gp = gpar(fontsize = annotationTextSize),
    title_gp = gpar(fontsize = annotationTextSize, fontface = "bold")
  ), 
  gap = unit(0.1, "cm")
)

topAnno = HeatmapAnnotation(
  df = topAnnoDf,
  col = topAnnoColors,
  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 = "#FFFFFF00"
)
library(circlize)
col_fun = colorRamp2(c(0, 1, 2), c(heat.colors(3)))


allReports_sp_mat_nolab = allReports_sp_mat
colnames(allReports_sp_mat_nolab) = NULL
allReports_sp_mat_hm = Heatmap(
  allReports_sp_mat_nolab,
  cluster_columns = F,
  cluster_rows = F,
  col = col_fun,
  name = "coverage",
  top_annotation = topAnno,
  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")
  ),
  cell_fun = function(j, i, x, y, width, height, fill) {
    grid.rect(
      x = x,
      y = y,
      width = width,
      height = height * .9,
      gp = gpar(fill = fill, col = NA)
    )
  },
  rect_gp = gpar(type = "none"),
  column_title = "Chr13[2,817kb:2,844kb]",
  column_title_gp = gpar(fontsize = 20, fontface = "italic")
)

allReports_sp_mat_hm_noCluster = Heatmap(
  allReports_sp_mat_nolab,
  cluster_columns = F,
  cluster_rows = F,
  col = col_fun,
  name = "coverage",
  top_annotation = topAnno,
  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")
  ), 
  cell_fun = function(j, i, x, y, width, height, fill) {
        grid.rect(x = x, y = y, width = width, height = height *.9, 
                  gp = gpar(fill = fill, col = NA))
  }, 
  rect_gp = gpar(type = "none"), 
  column_title = "Chr13[2,817kb:2,844kb]",
  column_title_gp = gpar(fontsize = 20, fontface = "italic")
)

Final Plot

Code
draw(allReports_sp_mat_hm, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom", padding = unit(c(40, 2, 2, 2), "mm")) # , legend_border = T

Code
cairo_pdf("finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000.pdf", width = 20, height = 12.5)
draw(allReports_sp_mat_hm, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom", padding = unit(c(40, 2, 2, 2), "mm")) # , legend_border = T
dev.off()
quartz_off_screen 
                2
Code
allReports_region_summary = allReports %>% 
  filter(sample == .$sample[1]) %>% 
  group_by(`#chrom`) %>% 
  summarise(start = min(start), 
            end = max(end)) %>% 
  mutate(length = end - start)
create_dt(allReports_region_summary)

Plotting presence of TARE1 to match up with coverage

Code
hrp3Pat2_samplesWithTare1_filler = expand_grid(
  sample = rownames(allReports_sp_mat),
  breakwithinRegion = colnames(allReports_sp_mat) 
  ) %>%
  mutate(marker = 0)

hrp3Pat2_samplesWithTare1_sel = hrp3Pat2_samplesWithTare1 %>% 
  select(sample, breakwithinRegion) %>% 
  mutate(marker = 1) %>% 
  bind_rows(hrp3Pat2_samplesWithTare1_filler) %>% 
  group_by(sample, breakwithinRegion) %>% 
  summarise(marker = sum(marker))

hrp3Pat2_samplesWithTare1_sel_sp = hrp3Pat2_samplesWithTare1_sel %>% 
  group_by() %>% 
  spread(breakwithinRegion, marker)

hrp3Pat2_samplesWithTare1_sel_sp_mat = as.matrix(hrp3Pat2_samplesWithTare1_sel_sp[,2:ncol(hrp3Pat2_samplesWithTare1_sel_sp)])
rownames(hrp3Pat2_samplesWithTare1_sel_sp_mat) = hrp3Pat2_samplesWithTare1_sel_sp$sample 

hrp3Pat2_samplesWithTare1_sel_sp_mat = hrp3Pat2_samplesWithTare1_sel_sp_mat[match(rownames(allReports_sp_mat), rownames(hrp3Pat2_samplesWithTare1_sel_sp_mat)),]
hrp3Pat2_samplesWithTare1_sel_sp_mat_noLab = hrp3Pat2_samplesWithTare1_sel_sp_mat

colnames(hrp3Pat2_samplesWithTare1_sel_sp_mat_noLab) = NULL
allReports_sp_mat_hm_tare1Present = Heatmap(
  hrp3Pat2_samplesWithTare1_sel_sp_mat_noLab,
  cluster_columns = F,
  cluster_rows = F,
  col = colorRamp2(c(0, 1), c("#FFFFFF00", "green")),
  name = "coverage",
  top_annotation = topAnno,
  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")
  ),
  cell_fun = function(j, i, x, y, width, height, fill) {
    grid.rect(
      x = x,
      y = y,
      width = width,
      height = height * .9,
      gp = gpar(fill = fill, col = NA)
    )
  },
  rect_gp = gpar(type = "none")
)
Code
cairo_pdf("finalHRPII_HRPIII_windows_investTelemeraseHealing_chr13_full_out_step1000_windowSize1000_tare1_Present.pdf", width = 20, height = 12.5, onefile = T)
draw(allReports_sp_mat_hm_noCluster, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom", padding = unit(c(20, 2, 2, 2), "mm"))
draw(allReports_sp_mat_hm_tare1Present, background = "transparent", merge_legend = TRUE, heatmap_legend_side = "bottom", annotation_legend_side = "bottom", padding = unit(c(20, 2, 2, 2), "mm"))
dev.off()
quartz_off_screen 
                2

hrp3Pat2 samples With Tare1 on chr13

Code
hrp3Pat2_samplesWithTare1 = hrp3Pat2_samplesWithTare1 %>% 
  left_join(allMetaDeletionCalls)

create_dt(hrp3Pat2_samplesWithTare1)
Code
hrp3Pat2_samplesWithTare1_mod = hrp3Pat2_samplesWithTare1 %>% 
  separate(breakwithinRegion, into = c("chrom", "start", "end", "strand"), remove = F, convert = T, sep = "-")

hrp3Pat2_samplesWithTare1_mod_filt = hrp3Pat2_samplesWithTare1_mod %>% 
  group_by(sample) %>% 
  slice_max(end)

pf3d7_chrom13_coreEnding = 2853482

hrp3Pat2_samplesWithTare1_mod_filt =hrp3Pat2_samplesWithTare1_mod_filt %>% 
  mutate(pf3d7_chrom13_core_deletion = pf3d7_chrom13_coreEnding - end)

write_tsv(hrp3Pat2_samplesWithTare1, "hrp3Pat2_samplesWithTare1.tsv")

Amount of “core” genome deleted with telomere healing on chromosome 13

Code
skimr::skim(hrp3Pat2_samplesWithTare1_mod_filt %>% as_data_frame())
Data summary
Name hrp3Pat2_samplesWithTare1…
Number of rows 20
Number of columns 24
_______________________
Column type frequency:
character 14
Date 1
logical 5
numeric 4
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
sample 0 1 8 9 0 20 0
breakwithinRegion 0 1 31 31 0 7 0
chrom 0 1 11 11 0 1 0
strand 0 1 3 3 0 1 0
country 0 1 4 8 0 6 0
site 0 1 6 10 0 8 0
ExperimentSample 0 1 8 8 0 20 0
BiologicalSample 0 1 8 8 0 20 0
region 0 1 11 22 0 4 0
subRegion 0 1 11 11 0 3 0
secondaryRegion 0 1 4 6 0 2 0
hrpCall 0 1 15 15 0 1 0
isolate 0 1 5 5 0 1 0
hrp3DeletionPattern 0 1 9 9 0 1 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
collection_date 19 0.05 2012-09-01 2012-09-01 2012-09-01 1

Variable type: logical

skim_variable n_missing complete_rate mean count
PreferredSample 0 1 1 TRU: 20
IsFieldSample 0 1 1 TRU: 20
possiblyHRP2Deleted 0 1 0 FAL: 20
possiblyHRP3Deleted 0 1 1 TRU: 20
possiblyChr11Deleted 0 1 0 FAL: 20

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
start 0 1 2833493.00 4856.90 2821793 2830793 2835793 2836793 2840793 ▂▁▅▇▁
end 0 1 2834493.00 4856.90 2822793 2831793 2836793 2837793 2841793 ▂▁▅▇▁
collection_year 0 1 2009.55 2.67 2002 2009 2010 2011 2014 ▁▁▇▇▅
pf3d7_chrom13_core_deletion 0 1 18989.00 4856.90 11689 15689 16689 21689 30689 ▁▇▅▁▂
Code
allReports_tare1Present = allReports %>% 
  filter(sample %in% hrp3Pat2_samplesWithTare1$sample) %>% 
  filter(perBaseCoverageNormRounded > 0) %>% 
  group_by(sample) %>% 
  slice_max(order_by = start)

allReports_tare1Present_sel = allReports_tare1Present %>% 
  select(sample, name, `#chrom`, start, extraField0) %>% 
  left_join(allMetaDeletionCalls %>% 
              select(sample, country, region)) %>% 
  arrange(start)

create_dt(allReports_tare1Present_sel)
Code
allReports_tare1Present_sel_startCounts = allReports_tare1Present_sel %>% group_by(start) %>% count() %>% 
  arrange(desc(n))



cat( paste0(sum(allReports_tare1Present_sel_startCounts$n), " samples contain evidence of telomere healing on chromosome 13 resulting in the deletion of pfhrp3 as evidenced by the presence of TARE1(Vernick and McCutchan 1988) contiguous with the genomic sequence at the genomic location where coverage drops off. These breaks occur on chromosome 13 at ", paste0(format(allReports_tare1Present_sel_startCounts$start[1:(length(allReports_tare1Present_sel_startCounts$start) - 1)], nsmall=0, big.mark=","), " (n=", allReports_tare1Present_sel_startCounts$n, "), ", collapse = ""), "and ", format(allReports_tare1Present_sel_startCounts$start[length(allReports_tare1Present_sel_startCounts$start)], nsmall=0, big.mark=","), " (n=", allReports_tare1Present_sel_startCounts$n[length(allReports_tare1Present_sel_startCounts$n)], ")", ". "))
19 samples contain evidence of telomere healing on chromosome 13 resulting in the deletion of pfhrp3 as evidenced by the presence of TARE1(Vernick and McCutchan 1988) contiguous with the genomic sequence at the genomic location where coverage drops off. These breaks occur on chromosome 13 at 2,836,793 (n=8), 2,830,793 (n=4), 2,829,793 (n=2), 2,821,793 (n=1), 2,822,793 (n=1), 2,833,793 (n=1), 2,834,793 (n=1), 2,836,793 (n=1), and 2,840,793 (n=1).