Managing access to imputed chromatin states for a set of cell types
I have retrieved a modest number of roadmap bed files with ChromImpute mnemonic labeling of chromatin by states. These can be managed with an ErmaSet instance, a trivial extension of GenomicFiles class. The cellTypes method yields a character vector. The colData component has full metadata on the cell lines available.
ermaset = makeErmaSet()
## NOTE: input data had non-ASCII characters replaced by ' '.
ermaset
## ErmaSet object with 0 ranges and 31 files:
## files: E002_25_imputed12marks_mnemonics.bed.gz, E003_25_imputed12marks_mnemonics.bed.gz, ..., E088_25_imputed12marks_mnemonics.bed.gz, E096_25_imputed12marks_mnemonics.bed.gz
## detail: use files(), rowRanges(), colData(), ...
cellTypes(ermaset)[1:5]
## [1] "ES-WA7 Cells"
## [2] "H1 Cells"
## [3] "iPS DF 6.9 Cells"
## [4] "Primary B cells from peripheral blood"
## [5] "Primary T cells from cord blood"
datatable(as.data.frame(colData(ermaset)[,kpc]))
Enumerating states in the vicinity of a gene, across cell types
We form a GRanges representing 50kb upstream of IL33.
uil33 = flank(resize(range(genemodel("IL33")), 1), width=50000)
uil33
## GRanges object with 1 range and 0 metadata columns:
## seqnames ranges strand
## <Rle> <IRanges> <Rle>
## [1] chr9 [6165786, 6215785] +
## -------
## seqinfo: 1 sequence from hg19 genome
Bind this to the ErmaSet instance.
rowRanges(ermaset) = uil33
ermaset
## ErmaSet object with 1 ranges and 31 files:
## files: E002_25_imputed12marks_mnemonics.bed.gz, E003_25_imputed12marks_mnemonics.bed.gz, ..., E088_25_imputed12marks_mnemonics.bed.gz, E096_25_imputed12marks_mnemonics.bed.gz
## detail: use files(), rowRanges(), colData(), ...
Now query the files for cell-specific states in this interval.
library(BiocParallel)
register(MulticoreParam(workers=2)) # reduce will be done according to registered bpparam; lapply just extracts
suppressWarnings({
csstates = lapply(reduceByFile(ermaset, MAP=function(range, file) {
imp = import(file, which=range, genome=genome(range)[1])
seqlevels(imp) = seqlevels(range)
imp$rgb = erma:::rgbByState(imp$name)
imp
}), "[[", 1)
})
tys = cellTypes(ermaset) # need to label with cell types
csstates = lapply(1:length(csstates), function(x) {
csstates[[x]]$celltype = tys[x]
csstates[[x]]
})
csstates[1:2]
## [[1]]
## GRanges object with 15 ranges and 3 metadata columns:
## seqnames ranges strand | name rgb
## <Rle> <IRanges> <Rle> | <character> <character>
## [1] chr9 [6161801, 6166600] * | 25_Quies #FEFEFE
## [2] chr9 [6166601, 6166800] * | 17_EnhW2 #FEFE00
## [3] chr9 [6166801, 6171200] * | 25_Quies #FEFEFE
## [4] chr9 [6171201, 6171800] * | 17_EnhW2 #FEFE00
## [5] chr9 [6171801, 6172000] * | 16_EnhW1 #FEFE00
## ... ... ... ... ... ... ...
## [11] chr9 [6183401, 6197400] * | 25_Quies #FEFEFE
## [12] chr9 [6197401, 6197600] * | 19_DNase #FEFE66
## [13] chr9 [6197601, 6208800] * | 25_Quies #FEFEFE
## [14] chr9 [6208801, 6211000] * | 21_Het #8990CF
## [15] chr9 [6211001, 6217800] * | 25_Quies #FEFEFE
## celltype
## <character>
## [1] ES-WA7 Cells
## [2] ES-WA7 Cells
## [3] ES-WA7 Cells
## [4] ES-WA7 Cells
## [5] ES-WA7 Cells
## ... ...
## [11] ES-WA7 Cells
## [12] ES-WA7 Cells
## [13] ES-WA7 Cells
## [14] ES-WA7 Cells
## [15] ES-WA7 Cells
## -------
## seqinfo: 1 sequence from hg19 genome
##
## [[2]]
## GRanges object with 14 ranges and 3 metadata columns:
## seqnames ranges strand | name rgb
## <Rle> <IRanges> <Rle> | <character> <character>
## [1] chr9 [6161801, 6166600] * | 25_Quies #FEFEFE
## [2] chr9 [6166601, 6166800] * | 17_EnhW2 #FEFE00
## [3] chr9 [6166801, 6171200] * | 25_Quies #FEFEFE
## [4] chr9 [6171201, 6173000] * | 17_EnhW2 #FEFE00
## [5] chr9 [6173001, 6175400] * | 21_Het #8990CF
## ... ... ... ... ... ... ...
## [10] chr9 [6183401, 6197400] * | 25_Quies #FEFEFE
## [11] chr9 [6197401, 6197600] * | 19_DNase #FEFE66
## [12] chr9 [6197601, 6209000] * | 25_Quies #FEFEFE
## [13] chr9 [6209001, 6211000] * | 21_Het #8990CF
## [14] chr9 [6211001, 6218200] * | 25_Quies #FEFEFE
## celltype
## <character>
## [1] H1 Cells
## [2] H1 Cells
## [3] H1 Cells
## [4] H1 Cells
## [5] H1 Cells
## ... ...
## [10] H1 Cells
## [11] H1 Cells
## [12] H1 Cells
## [13] H1 Cells
## [14] H1 Cells
## -------
## seqinfo: 1 sequence from hg19 genome
This sort of code underlies the csProfile utility to visualize variation in state assignments in promoter regions for various genes.
csProfile(ermaset[,1:5], symbol="CD28", useShiny=FALSE)
## 'select()' returned 1:many mapping between keys and columns
## Warning: executing %dopar% sequentially: no parallel backend registered
## Scale for 'y' is already present. Adding another scale for 'y', which will replace the existing scale.
Set useShiny to TRUE to permit interactive selection of region to visualize.
