Converts from the internal matrices to a DESeq standard object.
Usage
GSEPD_Export_DESeq(G)
Arguments
G
The GSEPD list object to extract a DeseqDataSet from.
Details
Using the given GSEPD object's finalCounts and sampleMeta, a simple DESeqDataSet object is created with the default design matrix. Provided for interoperability with other analysis packages.
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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> library(rgsepd)
Loading required package: DESeq2
Loading required package: S4Vectors
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
rbind, rownames, sapply, setdiff, sort, table, tapply, union,
unique, unsplit
Attaching package: 'S4Vectors'
The following objects are masked from 'package:base':
colMeans, colSums, expand.grid, rowMeans, rowSums
Loading required package: IRanges
Loading required package: GenomicRanges
Loading required package: GenomeInfoDb
Loading required package: SummarizedExperiment
Loading required package: Biobase
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Loading required package: goseq
Loading required package: BiasedUrn
Loading required package: geneLenDataBase
Loading R/GSEPD 1.4.2
Building human gene name caches
'select()' returned 1:1 mapping between keys and columns
'select()' returned 1:1 mapping between keys and columns
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/rgsepd/GSEPD_Export_DESeq.Rd_%03d_medium.png", width=480, height=480)
> ### Name: GSEPD_Export_DESeq
> ### Title: Export DESeqDataSet object
> ### Aliases: GSEPD_Export_DESeq
> ### Keywords: DESeq2
>
> ### ** Examples
>
> data("IlluminaBodymap")
> data("IlluminaBodymapMeta")
> set.seed(1000) #fixed randomness
> isoform_ids <- Name_to_RefSeq(c("HIF1A","EGFR","MYH7","CD33","BRCA2"))
> rows_of_interest <- unique( c( isoform_ids ,
+ sample(rownames(IlluminaBodymap),
+ size=500,replace=FALSE)))
> G <- GSEPD_INIT(Output_Folder="OUT",
+ finalCounts=round(IlluminaBodymap[rows_of_interest , ]),
+ sampleMeta=IlluminaBodymapMeta,
+ COLORS=c("green","black","red"))
Keeping rows with counts (458 of 505)
> G <- GSEPD_ChangeConditions( G, c("A","B")) #set testing groups first!
> dds <- GSEPD_Export_DESeq(G)
converting counts to integer mode
> print(dds)
class: DESeqDataSet
dim: 458 16
metadata(1): version
assays(1): counts
rownames(458): NM_181054 NM_201284 ... NM_001113755 NM_001165414
rowData names(0):
colnames(16): adipose.1 adipose.2 ... skeletal_muscle.3
skeletal_muscle.4
colData names(3): Sample Condition SHORTNAME
>
>
>
>
>
> dev.off()
null device
1
>