correlate_de_tables | R Documentation |
limma, DEseq2, and EdgeR all make somewhat different assumptions. and choices about what makes a meaningful set of differentially. expressed genes. This seeks to provide a quick and dirty metric describing the degree to which they (dis)agree.
correlate_de_tables(results, annot_df = NULL, extra_contrasts = NULL)
results |
Data from do_pairwise() |
annot_df |
Include annotation data? |
extra_contrasts |
include some extra contrasts when comparing results. |
Invoked by all_pairwise().
Heatmap showing how similar they are along with some correlations betwee the three players.
[limma_pairwise()] [edger_pairwise()] [deseq_pairwise()]
## Not run:
l = limma_pairwise(expt)
d = deseq_pairwise(expt)
e = edger_pairwise(expt)
fun = compare_led_tables(limma = l, deseq = d, edger = e)
## End(Not run)
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