countTable_regions {ORFik} | R Documentation |
By default will make count tables over mRNA, leaders, cds and trailers for all libraries in experiment. region
countTable_regions( df, out.dir = dirname(df$filepath[1]), longestPerGene = FALSE, geneOrTxNames = "tx", regions = c("mrna", "leaders", "cds", "trailers"), type = "count", lib.type = "ofst", weight = "score", rel.dir = "QC_STATS", forceRemake = FALSE, BPPARAM = bpparam() )
df |
an ORFik |
out.dir |
optional output directory, default:
|
longestPerGene |
a logical (default FALSE), if FALSE all transcript isoforms per gene. Ignored if "region" is not a character of either: "mRNA","tx", "cds", "leaders" or "trailers". |
geneOrTxNames |
a character vector (default "tx"), should row names keep trancript names ("tx") or change to gene names ("gene") |
regions |
a character vector, default: c("mrna", "leaders", "cds", "trailers"), make raw count matrices of whole regions specified. Can also be a custom GRangesList of for example uORFs or a subset of cds etc. |
type |
default: "count" (raw counts matrix), alternative is "fpkm", "log2fpkm" or "log10fpkm" |
lib.type |
a character(default: "default"), load files in experiment or some precomputed variant, either "ofst", "bedo", "bedoc" or "pshifted". These are made with ORFik:::convertLibs() or shiftFootprintsByExperiment(). Can also be custom user made folders inside the experiments bam folder. |
weight |
numeric or character, a column to score overlaps by. Default "score", will check for a metacolumn called "score" in libraries. If not found, will not use weights. |
rel.dir |
relative output directory for out.dir, default: "QC_STATS". For pshifted, write "pshifted". |
forceRemake |
logical, default FALSE. If TRUE, will not look for existing file. |
BPPARAM |
how many cores/threads to use? default: bpparam() |
a list of data.table, 1 data.table per region. The regions will be the names the list elements.
Other countTable:
countTable()
##Make experiment df <- ORFik.template.experiment() ## Create count tables for all default regions # countTable_regions(df) ## Pshifted reads (first create pshiftead libs) # countTable_regions(df, lib.type = "pshifted", rel.dir = "pshifted")