transBrowse {gQTLstats} | R Documentation |
exhibit genotype:genomic feature distributions with a shiny app
transBrowse(tbg, anno, tivcf, se, title = "trans eQTL") transBrowse2(tbga, annovec, tivcf, se, title = "trans eQTL", maxrank=3)
tbg |
filtered output of |
tbga |
filtered output of |
anno |
a vector with 'feature symbols' (e.g.,, gene symbols) as values and
'feature names' (elements of rownames of |
annovec |
a vector with 'feature symbols' (e.g.,, gene symbols) as values and
'feature names' (elements of rownames of |
tivcf |
reference to Tabix-indexed VCF |
se |
SummarizedExperiment instance with rowname coincident with
|
title |
optional string for title panel |
maxrank |
transBrowse2 works with the tsByRankAccum function that collects scores down to a specified rank. This parameter specifies the boundary. |
This function is under development. The intention is to allow convenient visualization of off-chromosome genotype-feature relationships. AllAssoc collects association scores SNP-wise, and saves the largest "K" scores obtained, along with feature identity and location metadata. The largest score obtained for a given SNP is the rank 1 association, the next largest is rank 2, and so on.
## Not run: # consider the following filtering utility tbfilt = function(tbg, seqnames.="17", minMAF=.1, minabsodist = 1e7, nrec=1000) { tbg = tbg[ which(as.character(seqnames(tbg)) %in% seqnames.) ] tbg = tbg[ which(tbg$MAF > minMAF & abs(tbg$obsdist) > minabsodist) ] tbg[ order(tbg$scores, decreasing=TRUE) ][1:nrec] } # registerDoSEQ() library(geuvStore2) r17 = g17transRegistry() g17 = TransStore(list(r17)) tbg = tbfilt(tsByRankAccum(g17, 3, mcol2keep=c("REF", "snp", "MAF"))) # 1000 records tf17 = ldblock::s3_1kg("17") # uses S3 bucket require(geuvPack) require(shiny) if (!exists("geuFPKM")) data(geuFPKM) if (!exists("gencodeV12")) data(gencodeV12) data(gen2sym) transBrowse2( tbg, gen2sym, tf17, geuFPKM, title="trans GEUV chr17") ## End(Not run) # end dontrun