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4 hours ago by

logFC is the fold change on the log scale. One uses the log to make changes symmetric around zero, example:

> 70/30; 30/70; log2(70/30); log2(30/70)
[1] 2.333333
[1] 0.4285714
[1] 1.222392
[1] -1.222392

Without the log FCs smaller one would be compressed between zero and 0.9999999, while positive ones go from one to infinity. The log compensates for this.

logCPM is the average expression of all samples for that particular gene across all samples on the log-scale expressed in counts per million (cpm, as calculated by edgeR after normalization). It is kind of a reflection of the base level of the gene in the sample population you are testing, generally longer or more highly-expressed genes have higher logCPM and vice versa. Generally, statistical power rises the higher this value is.

F is the F-statistic from the quasi-likelihood F-test.

PValue is the nominal p-value derived from F without any multiple testing correction and FDR is the PValue after (by default) Benjamini-Hochberg correction.

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