rep_de: DESeq2 Analysis of Resampled Subsets
In Coraline66/Deseq: DESeq2 Gene Differential Analysis

Description Usage Arguments Details Value Examples

This function performs DESeq2 differential analysis to a group of subsets of the samples to investigate the effect of replicates.

1	rep_de(n, sam, samp, datatype)

`n`	integer. The number of samples for subsequent analysis. Note that n equals 2 times the number of columns of matrix samp for datatype "luad" & "brca", while it equals the number of columns of matrix samp(element of samp if it is a list) for datatype "sarc".
`sam`	matrix obtained from first-step resampling which indicates the new truth sets.
`samp`	matrix or a list of matrices obtained from second-step resampling. It consists of the indices of subsets generated from the new truth sets.
`datatype`	character indicating which type of data is involved. "luad", "brca" or "sarc".

Note that the length of exported list should be equal to the number of rows of matrix sam times the number of rows of matrix samp(element of samp if it is a list). The results for the subsets of the first new truth set are stored in "rep_de(n, sam, samp, datatype)[[k]], k=1, 2, ..., dim(samp[[1]])[1]", i.e., the first "dim(samp[[1]])[1]" elements of the returned result of function "rep_de()". Similarly, "rep_de(n, sam, samp, datatype)[[k]], k=dim(samp[[1]])[1]+1, ..., 2*(dim(samp[[1]])[1])" contains the information corresponding to the second new truth set, etc.

a list that is composed of the results of subgroup DESeq2 analysis. A criterion of abs(log2-FoldChange) > 1 and adjusted P-value < 0.05 is utilized during the filtering process.