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Last data update: 2014.03.03

R: Initialization

GSEPD_INIT

R Documentation

Initialization

Description

Initializes the system, here you will pass in the count dataset and the sample metadata, before any GSEPD processing. Return value is a named list holding configurable parameters.

Usage

GSEPD_INIT(Output_Folder = "OUT", finalCounts = NULL, sampleMeta = NULL,
DESeqDataSet = NULL,
  COLORS = c("green", "gray", "red"),
  C2T = "x" )

Arguments

`Output_Folder`	Specify the subdirectory to hold output/generated files. Defaults to "OUT".
`finalCounts`	This must be a matrix of count data, rows are transcript IDs and columns are samples.
`sampleMeta`	The sampleMeta matrix must be passed here. It is a data frame with a row for each sample in the finalCounts matrix. Some required columns are SHORTNAME= sample nicknames; Condition= treatment group for differential expression; and Sample are the column names of finalCounts. Other columns are permitted to facilitate subsetting (not automatically supported).
`DESeqDataSet`	Data may also be included in the format of a DESeqDataSet object, this is mutually exclusive of the finalCounts/sampleMeta scheme.
`COLORS`	A three element vector of colors to make the heatmaps, the first element is the under-expressed genes, and the third element is the over-expressed genes. Defaults to green-red through gray.
`C2T`	This symbol is used in the filenames to delimit sample groups.

Details

This function sets up the master parameter object, and therefore must be called first. This object includes all configurable parameters you can change before running the pipeline. Count data should be provided in the finalCounts matrix, with phenotype and sample data in the sampleMeta matrix. Optionally, these data may be packages in a DESeqDataSet instead. Rows with no expression are dropped at the point of loading.

Value

Returns the GSEPD named list master object, to be used in subsequent function calls.

Examples

  data("IlluminaBodymap")
  data("IlluminaBodymapMeta")
  isoform_ids <- Name_to_RefSeq(c("HIF1A","EGFR","MYH7","CD33","BRCA2"))
  rows_of_interest <- unique( c( isoform_ids ,
                                 sample(rownames(IlluminaBodymap),
                                        size=1000,replace=FALSE)))
  G <- GSEPD_INIT(Output_Folder="OUT",
                finalCounts=round(IlluminaBodymap[rows_of_interest , ]),
                sampleMeta=IlluminaBodymapMeta,
                COLORS=c("green","black","red"))   
  #now ready to run:
  # G<-GSEPD_ProcessAll(G);

Results


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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Type 'demo()' for some demos, 'help()' for on-line help, or
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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_INIT.Rd_%03d_medium.png", width=480, height=480)
> ### Name: GSEPD_INIT
> ### Title: Initialization
> ### Aliases: GSEPD_INIT
> 
> ### ** Examples
> 
>   data("IlluminaBodymap")
>   data("IlluminaBodymapMeta")
>   isoform_ids <- Name_to_RefSeq(c("HIF1A","EGFR","MYH7","CD33","BRCA2"))
>   rows_of_interest <- unique( c( isoform_ids ,
+                                  sample(rownames(IlluminaBodymap),
+                                         size=1000,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 (907 of 1005)
>   #now ready to run:
>   # G<-GSEPD_ProcessAll(G);
>   
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>