Batch_adjust: Adjusting batch effect.

Description Usage Arguments Value Author(s) References

View source: R/MASCOT.R

Description

Most single cell CRISPR screening data are generated without batch effect. If the data were generated by different batches, this function should be performed to check if there is batch effect and then adjust it.

Usage

1
Batch_adjust(expression_profile, sample_info_batch, sample_info_gene, plot = TRUE, plot_path = "~/batch_check.pdf")

Arguments

expression_profile

A dataframe showing the expression profile after performing cell quality control.

sample_info_batch

A character vector showing the batch of each sample. The vector's column name is the sample name.

sample_info_gene

A character vector showing the knockout gene of each sample. The vector's column name is the sample name.

plot

FALSE by default. If TURE, plot the graph showing batch effect.

plot_path

The path of the graph you plot. It works only when the parameter "plot" is TRUE.

Value

You will get the expression profile after batch effect adjusting.

Author(s)

Bin Duan

References

Manimaran S, Selby HM, Okrah K, Ruberman C, Leek JT, Quackenbush J, Haibe-Kains B, Bravo HC and Johnson WE(2016). <e2><80><9c>BatchQC: interactive software for evaluating sample and batch effects in genomic data.<e2><80><9d>_Bioinformatics_. doi: 10.1093/bioinformatics/btw538 Jeffrey T. Leek, W. Evan Johnson, Hilary S. Parker, Elana J. Fertig, Andrew E. Jaffe and John D. Storey (2016). sva: Surrogate Variable Analysis. R package version 3.22.0.


BinDuan/MASCOT documentation built on May 23, 2019, 2:42 p.m.