RSEM-RUN-EBSEQ(1) | User Contributed Perl Documentation | RSEM-RUN-EBSEQ(1) |
rsem-run-ebseq - Wrapper for EBSeq to perform differential expression analysis.
rsem-run-ebseq [options] data_matrix_file conditions output_file
This program is a wrapper over EBSeq. It performs differential expression analysis and can work on two or more conditions. All genes/transcripts and their associated statistcs are reported in one output file. This program does not control false discovery rate and call differential expressed genes/transcripts. Please use 'rsem-control-fdr' to control false discovery rate after this program is finished.
If there are only 2 different conditions among the samples, four statistics (columns) will be reported for each gene/transcript. They are "PPEE", "PPDE", "PostFC" and "RealFC". "PPEE" is the posterior probability (estimated by EBSeq) that a gene/transcript is equally expressed. "PPDE" is the posterior probability that a gene/transcript is differentially expressed. "PostFC" is the posterior fold change (condition 1 over condition2) for a gene/transcript. It is defined as the ratio between posterior mean expression estimates of the gene/transcript for each condition. "RealFC" is the real fold change (condition 1 over condition2) for a gene/transcript. It is the ratio of the normalized within condition 1 mean count over normalized within condition 2 mean count for the gene/transcript. Fold changes are calculated using EBSeq's 'PostFC' function. The genes/transcripts are reported in descending order of their "PPDE" values.
If there are more than 2 different conditions among the samples, the output format is different. For differential expression analysis with more than 2 conditions, EBSeq will enumerate all possible expression patterns (on which conditions are equally expressed and which conditions are not). Suppose there are k different patterns, the first k columns of the output file give the posterior probability of each expression pattern is true. Patterns are defined in a separate file, 'output_file.pattern'. The k+1 column gives the maximum a posteriori (MAP) expression pattern for each gene/transcript. The k+2 column gives the posterior probability that not all conditions are equally expressed (column name "PPDE"). The genes/transcripts are reported in descending order of their "PPDE" column values. For details on how EBSeq works for more than 2 conditions, please refer to EBSeq's manual.
1) We're interested in isoform-level differential expression analysis and there are two conditions. Each condition has 5 replicates. We have already collected the data matrix as 'IsoMat.txt' and generated ngvector as 'ngvector.ngvec':
rsem-run-ebseq --ngvector ngvector.ngvec IsoMat.txt 5,5 IsoMat.results
The results will be in 'IsoMat.results' and 'IsoMat.results.normalized_data_matrix' contains the normalized data matrix.
2) We're interested in gene-level analysis and there are 3 conditions. The first condition has 3 replicates and the other two has 4 replicates each. The data matrix is named as 'GeneMat.txt':
rsem-run-ebseq GeneMat.txt 3,4,4 GeneMat.results
Four files, 'GeneMat.results', 'GeneMat.results.normalized_data_matrix', 'GeneMat.results.pattern', and 'GeneMat.results.condmeans', will be generated.
2020-02-17 | perl v5.30.0 |