MetabolicExprImputation¶
This process imputes the dropout values in scRNA-seq data.
It takes the Seurat object as input and outputs the Seurat object with
imputed expression data.
You can turn off the imputation by setting the noimpute
option
of the process group to True
.
Input¶
infile
: The input file in RDS/qs format of Seurat object
Output¶
outfile
: Default:{{in.infile | stem}}.imputed.qs
.
The output file in RDS format of Seurat object Note that with rmagic and alra, the original default assay will be renamed toRAW
and the imputed RNA assay will be renamed toRNA
and set as default assay.
Environment Variables¶
tool
(choice
): Default:alra
.
Either alra, scimpute or rmagicalra
: Use RunALRA() from Seuratscimpute
: Use scImpute() from scimputermagic
: Use magic() from Rmagic
scimpute_args
(ns
): The arguments for scimputedrop_thre
(type=float
): Default:0.5
.
The dropout thresholdkcluster
(type=int
): Number of clusters to usencores
(type=int
): Default:1
.
Number of cores to userefgene
: Default:""
.
The reference gene file
rmagic_args
(ns
): The arguments for rmagicpython
: Default:python
.
The python path where magic-impute is installed.threshold
(type=float
): Default:0.5
.
The threshold for magic imputation.
Only the genes with dropout rates greater than this threshold (No. of cells with non-zero expression / total number of cells) will be imputed.
alra_args
(type=json
): Default:{}
.
The arguments forRunALRA()
Reference¶
- Linderman, George C., Jun Zhao, and Yuval Kluger. "Zero-preserving imputation of scRNA-seq data using low-rank approximation." BioRxiv (2018): 397588.
- Li, Wei Vivian, and Jingyi Jessica Li. "An accurate and robust imputation method scImpute for single-cell RNA-seq data." Nature communications 9.1 (2018): 997.
- Dijk, David van, et al. "MAGIC: A diffusion-based imputation method reveals gene-gene interactions in single-cell RNA-sequencing data." BioRxiv (2017): 111591.