snv.bench: snv.bench

In mrrichowen/snv.predict: snv.predict uses true and false positives to improve snvs called from single cell RNA-seq data.

Description

This is a convenience function that takes the output files from nuseq-sc and combines them with a list of data frames with annotated snvs for input into other snv.predict functions. It will output a single snv.summary file concatenating all results and a vector of the low correlating classifiers recommended for subsequent analysis.

Usage

snv.bench(nuseq_classifiers, truths, training_set = FALSE)

Arguments

nuseq_classifiers	List of named data frames as output from nuseq-sc.
truths	List of data.frames with snv information. Easiest to use the convenience function 'convert_to_pos' and add a fifth column ('labels') with snvs annotated as true_positive (1), false_positive (0) and unknown (NA).
training_set	If TRUE, only snvs with ground truth data will be output. This is useful if this data is to be used for training a model to be applied to a different dataset with snv.cross.predict.

Examples

snv.bench(nuseq_classifiers,truths,training_set=FALSE)

mrrichowen/snv.predict documentation built on May 14, 2019, 5:27 p.m.