Description Usage Arguments Value
Finds markers (differentially expressed genes) for each of the identity classes in a dataset
1 2 3 | find_all_markers(object, thresh.test = 1, test.use = "bimod",
return.thresh = 0.01, do.print = FALSE, min.pct = 0, print.bar = TRUE,
only.pos = FALSE)
|
object |
Seurat object |
thresh.test |
Limit testing to genes which show, on average, at least X-fold difference (log-scale) between cells in an identity class, and all other cells. |
test.use |
Denotes which test to use. Seurat currently implements "bimod" (likelihood-ratio test for single cell gene expression, McDavid et al., Bioinformatics, 2011, default), "roc" (standard AUC classifier), "t" (Students t-test), and "tobit" (Tobit-test for differential gene expression, as in Trapnell et al., Nature Biotech, 2014) |
return.thresh |
Only return markers that have a p-value < return.thresh, or a power > return.thresh (if the test is ROC) |
do.print |
FALSE by default. If TRUE, outputs updates on progress. |
min.pct |
- only test genes that are detected in a minimum fraction of min.pct cells in either of the two populations. Meant to speed up the function by not testing genes that are very infrequently expression |
print.bar |
Print a progress bar once expression testing begins (uses pbapply to do this) |
only.pos |
Only return positive markers (FALSE by default) |
Matrix containing a ranked list of putative markers, and associated statistics (p-values, ROC score, etc.)
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