Last updated: 2021-09-24
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Knit directory: femNATCD_MethSeq/
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Home = getwd()
Dark8 = brewer.pal(8, "Dark2")
source(paste0(Home,"/code/custom_functions.R"))
Lade nötiges Paket: kableExtra
Lade nötiges Paket: tidyverse
-- Attaching packages --------------------------------------- tidyverse 1.3.0 --
v ggplot2 3.3.3 v purrr 0.3.4
v tibble 3.0.4 v dplyr 1.0.2
v tidyr 1.1.2 v stringr 1.4.0
v readr 1.4.0 v forcats 0.5.0
-- Conflicts ------------------------------------------ tidyverse_conflicts() --
x dplyr::collapse() masks IRanges::collapse()
x dplyr::combine() masks Biobase::combine(), BiocGenerics::combine()
x dplyr::count() masks matrixStats::count()
x dplyr::desc() masks IRanges::desc()
x tidyr::expand() masks S4Vectors::expand()
x dplyr::filter() masks stats::filter()
x dplyr::first() masks S4Vectors::first()
x dplyr::group_rows() masks kableExtra::group_rows()
x dplyr::lag() masks stats::lag()
x ggplot2::Position() masks BiocGenerics::Position(), base::Position()
x purrr::reduce() masks GenomicRanges::reduce(), IRanges::reduce()
x dplyr::rename() masks S4Vectors::rename()
x dplyr::slice() masks IRanges::slice()
Lade nötiges Paket: compareGroups
Lade nötiges Paket: scales
Attache Paket: 'scales'
The following object is masked from 'package:purrr':
discard
The following object is masked from 'package:readr':
col_factor
load(paste0(Home,"/output/dds_filt_analyzed.RData"))
load(paste0(Home,"/output/resultsdmr_table.RData"))
Patdata=colData(dds_filt)
cpm=counts(dds_filt, normalized=T)
log2_cpm=log2(cpm+1)
res=results(dds_filt)
GRresultslme_table = rowRanges(dds_filt)
DFtoplotall=as.data.frame(GRresultslme_table)
colnames(DFtoplotall)[1:3] = c("Chromosome", "chromStart", "chromEnd")
DFtoplotall = DFtoplotall[order(DFtoplotall$Chromosome, DFtoplotall$chromStart),]
DFtoplotall$Chromosome = as.factor(DFtoplotall$Chromosome)
countspergroup <- data.frame(cases=rowSums(cpm[,dds_filt$group =="CD"])/sum(dds_filt$group =="CD"),
controls=rowSums(cpm[,dds_filt$group =="CTRL"])/sum(dds_filt$group =="CTRL"))
DFtoplotall$MeanCD = log2(countspergroup[,"cases"]+1)
DFtoplotall$MeanCTRL = log2(countspergroup[,"controls"]+1)
DFtoplot = DFtoplotall[DFtoplotall$WaldPvalue_groupCD <= cutoff,]
colnames(DFtoplot) = gsub("WaldPvalue", "-log10_P", colnames(DFtoplot))
targetlist=list(inner=c("-log10_P_contraceptivesyes",
"-log10_P_cigday_1","-log10_P_Age"),
outer=c("MeanCD", "MeanCTRL","-log10_P_groupCD"))
svgfile = paste0(Home,"/output/circos_LME_tags.svg")
topindex=rownames(DFtoplotall)[which(res$pvalue %in% sort(res$pvalue, decreasing = F)[1:10])]
plotcircos(plotdata =DFtoplot, targets = targetlist,
labcol="gene",
title="Differentially Methylated Tag",
pvalident = "log10_P", #collabel for pval identification
pvallog=FALSE, # is log transformed
cutoffpval = 8, #after this cutoff will be black
labelsidx=topindex,
filename = svgfile)
RCircos.Core.Components initialized.
Type ?RCircos.Reset.Plot.Parameters to see how to modify the core components.
pdf
2
#plot best hit
# settings Genomic annotation
scheme <- getScheme()
scheme$GdObject$background.panel = "white"
scheme$GdObject$background.title = "white"
scheme$GdObject$fontcolor.title = "black"
scheme$AnnotationTrack$featureAnnotation = NULL
scheme$AnnotationTrack$fill = "gray"
scheme$AnnotationTrack$fontcolor.item = "black"
scheme$AnnotationTrack$cex = 0.5
scheme$DataTrack$col = Dark8
scheme$GeneRegionTrack$fill <- "dodgerblue3"
scheme$GeneRegionTrack$col <- NULL
scheme$GeneRegionTrack$transcriptAnnotation <- NULL
window=2000
index = which(res$pvalue == min(res$pvalue))
subtitel=paste0(DFtoplotall$Chromosome[index],": ", DFtoplotall$chromStart[index])
chr=DFtoplotall$Chromosome[index]
from = DFtoplotall$chromStart[index]-window
to = DFtoplotall$chromEnd[index]+window
targetrange = GRanges(seqnames = chr,
IRanges(from,
to))
tbl.gene = NULL
attempt = 0
while(is.null(tbl.gene) & attempt<10){
print(paste("tbl.gene attempt:", attempt+1))
if (attempt != 0){
Sys.sleep(60)}
try(tbl.gene <- getTable(ucscTableQuery(mySession,
track="refSeqComposite",
range=targetrange,
table="ncbiRefSeq")))
attempt = attempt+1
}
[1] "tbl.gene attempt: 1"
tbl.cpg = NULL
attempt = 0
while(is.null(tbl.cpg) & attempt<10){
print(paste("tbl.cpg attempt:", attempt+1))
if (attempt != 0){
Sys.sleep(60)}
try(tbl.cpg <- getTable(ucscTableQuery(mySession,
track="cpgIslandExt",
range=targetrange,
table="cpgIslandExt")))
attempt = attempt+1
}
[1] "tbl.cpg attempt: 1"
tbl.TFBdg = NULL
attempt = 0
while(is.null(tbl.TFBdg) & attempt<10){
print(paste("tbl.TFBdg attempt:", attempt+1))
if (attempt != 0){
Sys.sleep(60)}
try(tbl.TFBdg <- getTable(ucscTableQuery(mySession,
track="tfbsConsSites",
range=targetrange,
table="tfbsConsSites")))
attempt = attempt+1
}
[1] "tbl.TFBdg attempt: 1"
tbl.gene_GR <- convertUCSCtoGR(tbl.gene, col.start = "txStart",col.end = "txEnd", col.strand = "strand")
tbl.cpg_GR <- convertUCSCtoGR(tbl.cpg)
tbl.TFBdg_GR <- convertUCSCtoGR(tbl.TFBdg)
itrack <- IdeogramTrack(genome = "hg19", chromosome = as.character(DFtoplotall$Chromosome[index]))
atrack <- GenomeAxisTrack()
dataplot=subsetByOverlaps(GRresultslme_table, targetrange)
indexreads=findOverlaps(GRresultslme_table, targetrange)
if(length(indexreads)>1){
targetcpm=log2_cpm[indexreads@from,]
tmp = dataplot
values(tmp)=targetcpm} else {
targetcpm=t(as.dataframe(log2_cpm[indexreads@from,]))
tmp = dataplot
values(tmp)=targetcpm
}
addScheme(scheme, "myScheme")
options(Gviz.scheme = "myScheme")
ptrack <- DataTrack(dataplot, data = -log10(dataplot$WaldPvalue_groupCD), baseline=0,
name = "P_group", type=c("histogram"), fill="black", col = "black",
col.baseline = "grey")
dtrack <- DataTrack(tmp, groups=Patdata$group,
name = "mean log2(cpm) [SD])", c("heatmap"))
displayPars(dtrack) <- list(type=c("a","confint"))
tbl.gene_GR$symbol = tbl.gene_GR$name2
genotrack <- GeneRegionTrack(tbl.gene_GR, name = "genes", transcriptAnnotation="symbol")
tbl.cpg_GR$symbol = tbl.cpg_GR$name
cpgtrack <- GeneRegionTrack(tbl.cpg_GR, name = "GpG", transcriptAnnotation = "symbol")
displayPars(cpgtrack)<- list(col="white", fill =Dark8[5])
values(tbl.TFBdg_GR)$symbol = tbl.TFBdg_GR$name
tfbtrack <- GeneRegionTrack(tbl.TFBdg_GR, name = "TF-Sites", transcriptAnnotation = "symbol")
displayPars(tfbtrack)<- list(col="white", fill =Dark8[6])
ncols <- 2
nrows <- 1
grid.newpage()
pushViewport(viewport(layout = grid.layout(nrows, ncols, widths=c(1,2))))
pushViewport(viewport(layout.pos.col = 2,layout.pos.row = 1))
p2 = plotTracks(list(itrack,atrack, genotrack, dtrack, ptrack, cpgtrack, tfbtrack), from = from, to = to, sizes=c(1,1,1,4,2,1,4), add=TRUE)
upViewport()
pushViewport(viewport(layout.pos.col = 1,layout.pos.row = 1))
tmp = data.frame(log2_cpm = log2_cpm[index, ], group=Patdata$group)
p1 = ggplot(tmp, aes(x=group, y=log2_cpm, fill=group)) + geom_boxplot(show.legend=T, aes(fill=group)) +
geom_point(position=position_jitterdodge(jitter.width=0.5, dodge.width = 0.3))+scale_fill_manual(values = c("CTRL" = Dark8[1],"CD"=Dark8[2]))
grid.draw(as.grob(p1))
upViewport()
grid.export(paste0(Home,"/output/LME_tophit.svg"))
Warning in grabDL(warn, wrap, wrap.grobs, ...): one or more grobs overwritten
(grab WILL not be faithful; try 'wrap.grobs = TRUE')
Warning in svgStyleAttributes(style, svgdev): Removing non-SVG style attribute
name(s): subscripts, group.number, group.value, span, degree, family, evaluation
Warning in svgStyleAttributes(style, svgdev): Removing non-SVG style attribute
name(s): subscripts, group.number, group.value, span, degree, family, evaluation
DFtoplotall = resultsdmr_table
colnames(DFtoplotall)[1:3] = c("Chromosome", "chromStart", "chromEnd")
DFtoplotall = DFtoplotall[order(DFtoplotall$Chromosome, DFtoplotall$chromStart),]
DFtoplotall$Chromosome = as.factor(DFtoplotall$Chromosome)
DFtoplot = DFtoplotall[(DFtoplotall$p.value<=cutoff | DFtoplotall$p.valueArea<cutoff), ]
targetlist=list(inner=c("p.value",
"p.valueArea"),
outer=c("clusterL"))
svgfile = paste0(Home,"/output/circos_DMR_tags.svg")
topindex=rownames(DFtoplot)[which(DFtoplot$p.value %in% sort(DFtoplot$p.value, decreasing = F)[1:10])]
plotcircos(plotdata =DFtoplot, targets = targetlist,
labcol="name",
title="Differentially Methylated Regions",
pvalident = "p.value", #collabel for pval identification
pvallog=FALSE, # is log transfromed
cutoffpval = 8, #after this cutoff will be black
labelsidx=topindex,
filename = svgfile)
RCircos.Core.Components initialized.
Type ?RCircos.Reset.Plot.Parameters to see how to modify the core components.
pdf
2
window=2000
index = which.min(resultsdmr_table$p.value)
chr=resultsdmr_table$chr[index]
from = resultsdmr_table$start[index]-window
to = resultsdmr_table$end[index]+window
targetrange = GRanges(seqnames = chr,
IRanges(from,
to))
tbl.gene <- getTable(ucscTableQuery(mySession, track="refSeqComposite",range=targetrange, table="ncbiRefSeq"))
tbl.cpg <- getTable(ucscTableQuery(mySession, track="cpgIslandExt",range=targetrange, table="cpgIslandExt"))
tbl.TFBdg <- getTable(ucscTableQuery(mySession, track="tfbsConsSites",range=targetrange, table="tfbsConsSites"))
tbl.gene_GR <- convertUCSCtoGR(tbl.gene, col.start = "txStart",col.end = "txEnd", col.strand = "strand")
tbl.cpg_GR <- convertUCSCtoGR(tbl.cpg)
tbl.TFBdg_GR <- convertUCSCtoGR(tbl.TFBdg)
itrack <- IdeogramTrack(genome = "hg19", chromosome = as.character(chr))
atrack <- GenomeAxisTrack()
dataplot=subsetByOverlaps(GRresultslme_table, targetrange)
indexreads=findOverlaps(GRresultslme_table, targetrange)
selected = which.min(as.data.frame(GRresultslme_table)[indexreads@from, "WaldPvalue_groupCD"])
if(length(indexreads)>1){
targetcpm=log2_cpm[indexreads@from,]
tmp = dataplot
values(tmp)=targetcpm} else {
targetcpm=t(as.dataframe(log2_cpm[indexreads@from,]))
tmp = dataplot
values(tmp)=targetcpm
}
ptrack <- DataTrack(dataplot, data = -log10(dataplot$WaldPvalue_groupCD), baseline=0,
name = "P_group", type=c("histogram"), fill="black", col = "black",
col.baseline = "grey")
dtrack <- DataTrack(tmp, groups=Patdata$group,
name = "mean log2(cpm) [SD])", c("heatmap"))
displayPars(dtrack) <- list(type=c("a","confint"))
tbl.gene_GR$symbol = tbl.gene_GR$name2
genotrack <- GeneRegionTrack(tbl.gene_GR, name = "genes", transcriptAnnotation="symbol")
tbl.cpg_GR$symbol = tbl.cpg_GR$name
cpgtrack <- GeneRegionTrack(tbl.cpg_GR, name = "GpG", transcriptAnnotation = "symbol")
displayPars(cpgtrack)<- list(col="white", fill =Dark8[5])
values(tbl.TFBdg_GR)$symbol = tbl.TFBdg_GR$name
tfbtrack <- GeneRegionTrack(tbl.TFBdg_GR, name = "TF-Sites", transcriptAnnotation = "symbol")
displayPars(tfbtrack)<- list(col="white", fill =Dark8[6])
ncols <- 2
nrows <- 1
grid.newpage()
pushViewport(viewport(layout = grid.layout(nrows, ncols, widths=c(1,2))))
pushViewport(viewport(layout.pos.col = 2,layout.pos.row = 1))
p2 = plotTracks(list(itrack,atrack, genotrack, dtrack, ptrack, cpgtrack, tfbtrack),
from = from, to = to, sizes=c(1,2,2,4,2,1,4), add=T)
upViewport()
pushViewport(viewport(layout.pos.col = 1,layout.pos.row = 1))
tmp = data.frame(log2_cpm = log2_cpm[indexreads@from[selected],], group=Patdata$group)
p1 = ggplot(tmp, aes(x=group, y=log2_cpm, fill=group)) + geom_boxplot(show.legend=T, aes(fill=group)) +
geom_point(position=position_jitterdodge(jitter.width=0.5, dodge.width = 0.3))+scale_fill_manual(values = c("CTRL" = Dark8[1],"CD"=Dark8[2]))
grid.draw(as.grob(p1))
upViewport()
sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)
Matrix products: default
locale:
[1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252
[3] LC_MONETARY=German_Germany.1252 LC_NUMERIC=C
[5] LC_TIME=German_Germany.1252
attached base packages:
[1] grid parallel stats4 stats graphics grDevices utils
[8] datasets methods base
other attached packages:
[1] scales_1.1.1 compareGroups_4.4.6
[3] forcats_0.5.0 stringr_1.4.0
[5] dplyr_1.0.2 purrr_0.3.4
[7] readr_1.4.0 tidyr_1.1.2
[9] tibble_3.0.4 ggplot2_3.3.3
[11] tidyverse_1.3.0 kableExtra_1.3.1
[13] gridSVG_1.7-2 ggplotify_0.0.5
[15] rtracklayer_1.49.5 Gviz_1.34.0
[17] RColorBrewer_1.1-2 beeswarm_0.2.3
[19] RCircos_1.2.1 DESeq2_1.30.0
[21] SummarizedExperiment_1.20.0 Biobase_2.50.0
[23] MatrixGenerics_1.2.0 matrixStats_0.57.0
[25] GenomicRanges_1.42.0 GenomeInfoDb_1.26.2
[27] IRanges_2.24.1 S4Vectors_0.28.1
[29] BiocGenerics_0.36.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] uuid_0.1-4 readxl_1.3.1 backports_1.2.0
[4] Hmisc_4.4-2 systemfonts_0.3.2 BiocFileCache_1.14.0
[7] lazyeval_0.2.2 splines_4.0.3 BiocParallel_1.24.1
[10] digest_0.6.27 ensembldb_2.14.0 htmltools_0.5.1.1
[13] fansi_0.4.1 Rsolnp_1.16 magrittr_2.0.1
[16] checkmate_2.0.0 memoise_2.0.0 BSgenome_1.58.0
[19] cluster_2.1.0 Biostrings_2.58.0 annotate_1.68.0
[22] modelr_0.1.8 officer_0.3.16 askpass_1.1
[25] prettyunits_1.1.1 jpeg_0.1-8.1 colorspace_2.0-0
[28] blob_1.2.1 rvest_0.3.6 rappdirs_0.3.1
[31] haven_2.3.1 xfun_0.20 crayon_1.3.4
[34] RCurl_1.98-1.2 jsonlite_1.7.2 genefilter_1.72.0
[37] survival_3.2-7 VariantAnnotation_1.36.0 glue_1.4.2
[40] gtable_0.3.0 zlibbioc_1.36.0 XVector_0.30.0
[43] webshot_0.5.2 DelayedArray_0.16.0 DBI_1.1.1
[46] Rcpp_1.0.5 viridisLite_0.3.0 xtable_1.8-4
[49] progress_1.2.2 htmlTable_2.1.0 gridGraphics_0.5-1
[52] foreign_0.8-81 bit_4.0.4 Formula_1.2-4
[55] truncnorm_1.0-8 htmlwidgets_1.5.3 httr_1.4.2
[58] ellipsis_0.3.1 mice_3.12.0 farver_2.0.3
[61] pkgconfig_2.0.3 XML_3.99-0.5 nnet_7.3-15
[64] dbplyr_2.0.0 locfit_1.5-9.4 labeling_0.4.2
[67] tidyselect_1.1.0 rlang_0.4.10 later_1.1.0.1
[70] AnnotationDbi_1.52.0 cellranger_1.1.0 munsell_0.5.0
[73] tools_4.0.3 cachem_1.0.1 cli_2.2.0
[76] generics_0.1.0 RSQLite_2.2.2 broom_0.7.3
[79] evaluate_0.14 fastmap_1.1.0 yaml_2.2.1
[82] knitr_1.30 bit64_4.0.5 fs_1.5.0
[85] zip_2.1.1 AnnotationFilter_1.14.0 whisker_0.4
[88] xml2_1.3.2 biomaRt_2.46.2 compiler_4.0.3
[91] rstudioapi_0.13 curl_4.3 png_0.1-7
[94] reprex_1.0.0 geneplotter_1.68.0 HardyWeinberg_1.7.1
[97] stringi_1.5.3 ps_1.5.0 GenomicFeatures_1.42.1
[100] gdtools_0.2.3 lattice_0.20-41 ProtGenerics_1.22.0
[103] Matrix_1.2-18 vctrs_0.3.6 pillar_1.4.7
[106] lifecycle_0.2.0 BiocManager_1.30.10 flextable_0.6.2
[109] data.table_1.13.6 bitops_1.0-6 httpuv_1.5.5
[112] R6_2.5.0 latticeExtra_0.6-29 promises_1.1.1
[115] gridExtra_2.3 writexl_1.3.1 dichromat_2.0-0
[118] assertthat_0.2.1 chron_2.3-56 openssl_1.4.3
[121] rprojroot_2.0.2 withr_2.4.1 GenomicAlignments_1.26.0
[124] Rsamtools_2.6.0 GenomeInfoDbData_1.2.4 hms_1.0.0
[127] rpart_4.1-15 rmarkdown_2.6 rvcheck_0.1.8
[130] git2r_0.28.0 biovizBase_1.38.0 lubridate_1.7.9.2
[133] base64enc_0.1-3