Data_imputation: Data imputation by SAVER.

In bm2-lab/MASCOT: Model-based Understanding of SIngle-cell CRISPR screening

Data imputation by SAVER.

Description

To improve the quality of single cell CRISPR screening data, MUSIC performed data imputation by SAVER.

Usage

Data_imputation(expression_profile, perturb_information, cpu_num = 4, split = 2)

Arguments

expression_profile	A dataframe showing the expression profile after performing cell quality control,that is, the function of "Cell_qc()" in this package.
perturb_information	A character vector showing the information of sample after performing the function of "Cell_qc()" in this package.
cpu_num	The cpu number for parallel computation. The default is 4. Parallel computation is strongly recommeneded to use because this step may take long time without parallel computation.
split	The number of data block. The default is 2. When the data is too big for your computer, you can divide the data into multiple blocks and then calculate. The more blocks, the more space is saved and the longer time will take.

Value

expression_profile	The expression profile after performing this step.
perturb_information	The information (perturbation names and sample names) of cells retained after performing this step.

Author(s)

Bin Duan

References

Huang, M. et al. SAVER: gene expression recovery for single-cell RNA sequencing. Nature methods 15, 539-542 (2018).

bm2-lab/MASCOT documentation built on April 19, 2024, 4:35 p.m.