makeDESeqDF {ReportingTools} | R Documentation |
Manipulates DESeq output to a data frame of significant observations. Draws corresponding box and whisker plots.
makeDESeqDF(object, countTable, pvalueCutoff, conditions, annotation.db, expName, reportDir, ...)
object |
Output from nbinomTest; see DESeq manual for details |
countTable |
A table of the raw counts, where rows indicate genes and columns are samples |
pvalueCutoff |
A threshold value for what is considered a significantly different gene. Only genes with p-values less than this will be included. |
conditions |
A vector indicating the groupings of the samples, for image purposes. |
annotation.db |
A character string, indicating the species of the samples |
expName |
The name of the experiment |
reportDir |
Directory to which the report (and figures) will be written |
... |
Unused arguments passed in from the publish method |
This function converts DESeq output into a data frame and draws the corresponding images
ret, A data frame with the following values: Entrez Id, Symbol, Gene Name, Image, Log2 Fold Change, P-value and Adjusted p-value.
Jessica Larson
#library(DESeq) #library(lattice) #data(mockRnaSeqData) #conditions <- c(rep("case",3), rep("control", 3)) #cds<-newCountDataSet(mockRnaSeqData, conditions) #cds<-estimateSizeFactors(cds) #cds<-estimateDispersions(cds) #res<-nbinomTest(cds,"control", "case" ) #desReport <- HTMLReport(shortName = 'RNAseq_analysis_with_DESeq', #title = 'RNA-seq analysis of differential expression using DESeq', #reportDirectory = "./reports") #publish(res,desReport,name="df",countTable=mockRnaSeqData, #pvalueCutoff=0.05, ##conditions=conditions,annotation.db="org.Mm.eg.db", #expName="deseq",reportDir="./reports", .modifyDF=makeDESeqDF) #finish(desReport)