scmageck_lr {scMAGeCK} | R Documentation |
echo "Use linear regression to test the association of gene knockout with all possible genes"
scmageck_lr(BARCODE, RDS, NEGCTRL, SELECT_GENE=NULL, LABEL = NULL, PERMUTATION = NULL, SAVEPATH = "./",LAMBDA=0.01,GENE_FRAC=0.01)
BARCODE |
A txt file to include cell identity information, generated from the cell identity collection step. |
RDS |
A Seurat object or local RDS file path that contains the scRNA-seq dataset. Note that the dataset has to be normalized and scaled. |
NEGCTRL |
The name of the genes (separated by ",") served as negative controls. |
SELECT_GENE |
The list of genes for regression. By default, all genes in the table are subject to regression. |
LABEL |
The label of the output file. |
PERMUTATION |
The number of permutations for p value calculation. |
SAVEPATH |
The save path of result. Default save path is the current working directory. If you don't need save the result, set SAVEPATH as NULL. |
LAMBDA |
A paramter for the LR model for ridge regression. Default: 0.01. |
GENE_FRAC |
A paramter for filtering low expressed genes. By default, only genes that have expressions in at least that fractions of cells are kept. Default: 0.01. |
The result for object RDS
### BARCODE file contains cell identity information, generated from the cell identity collection step BARCODE <- system.file("extdata","barcode_rec.txt",package = "scMAGeCK") ### RDS can be a Seurat object or local RDS file path that contains the scRNA-seq dataset RDS <- system.file("extdata","singles_dox_mki67_v3.RDS",package = "scMAGeCK") lr_result <- scmageck_lr(BARCODE=BARCODE, RDS=RDS, LABEL='dox_scmageck_lr', NEGCTRL = 'NonTargetingControlGuideForHuman', PERMUTATION = 1000, SAVEPATH=NULL, LAMBDA=0.01) lr_score <- lr_result[1] lr_score_pval <- lr_result[2] head(lr_score_pval)