GSEPD_ChangeOutput

Description

Update the stored output folder designation, and create it if necessary. This is useful if you want to change some LIMIT parameters and re-run the pipeline. Don't forget to GSEPD_Process() after changing settings.

Usage

GSEPD_ChangeOutput(GSEPD, newFolder)

Arguments

Value

Returns the updated GSEPD parameter object.

Author(s)

karl.stamm@gmail.com

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"))
  G <- GSEPD_ChangeConditions( G, c("A","B")) #set testing groups first!           

  G<- GSEPD_ChangeOutput(G, "Output2")
  #G <- GSEPD_Process( G ) #would output to folder Output2
  #now tweak some settings and re-do
  G$LIMIT$LFC <- 0.25 #lower than default log-fold-change limit
  G<- GSEPD_ChangeOutput(G, "Output-Low")
  #G <- GSEPD_Process( G ) #would output to folder Output-Low

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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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_ChangeOutput.Rd_%03d_medium.png", width=480, height=480)
> ### Name: GSEPD_ChangeOutput
> ### Title: GSEPD_ChangeOutput
> ### Aliases: GSEPD_ChangeOutput
> 
> ### ** 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!           
> 
>   G<- GSEPD_ChangeOutput(G, "Output2")
>   #G <- GSEPD_Process( G ) #would output to folder Output2
>   #now tweak some settings and re-do
>   G$LIMIT$LFC <- 0.25 #lower than default log-fold-change limit
>   G<- GSEPD_ChangeOutput(G, "Output-Low")
>   #G <- GSEPD_Process( G ) #would output to folder Output-Low
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>