find_all_markers: Gene expression markers for all identity classes
In paodan/studySeu: Seurat : R toolkit for single cell genomics

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)