Tools
Overview
This section summarizes commonly used single-cell transcriptome utility tools, designed to help researchers conduct various analyses more conveniently.
TIP
How to Read This Section
- This section contains multiple tool modules. It is recommended to use the table of contents on the right side of the page to quickly jump to topics of interest and expand content as needed.
SoupX Ambient RNA Contamination Removal
SoupX is an analysis module designed to remove ambient RNA contamination from single-cell transcriptome data. During droplet-based single-cell sequencing, some cells rupture during dissociation and library preparation, releasing free-floating mRNA into the cell suspension. This free mRNA is co-captured by all droplets, leading to false positive high expression of certain genes in nearly all cells, which interferes with downstream cell clustering, annotation, and differential expression analysis. SoupX utilizes free RNA information from empty droplets, combined with clustering results, to estimate the proportion of ambient RNA contamination in each cell and corrects the expression matrix, yielding a cleaner count matrix that improves the accuracy of downstream analyses.
User Guide
Doublet.calculate Doublet Detection
Doublet.calculate is a module for doublet identification and removal in single-cell data. In droplet-based platforms, occasional encapsulation of multiple cells within a single droplet generates mixed transcriptomes that interfere with downstream analyses. This module supports two algorithms: DoubletFinder (based on clustering structure, results closely match data characteristics) and Scrublet (based on expression matrix, faster processing speed). It automatically simulates doublets and classifies each barcode as doublet or singlet, outputting classification labels, UMAP visualization plots, and filtered clean data. Normal samples typically exhibit doublet rates of approximately 2% to 6%. This module is applicable to scRNA-seq/FFPE/SeekSpace transcriptome data, and filtered data can be directly used for downstream analyses.
User Guide
SpeciesSplit Mixed Species Matrix Splitting
When cells from multiple species are loaded together in the same GEM, the alignment uses a mixed reference genome. After standard analysis, gene names in the expression matrix carry species-specific prefixes (e.g., GRCh38-GAPDH, Sus_scrofa-ALB). SpeciesSplit leverages this feature to automatically detect species prefixes, determine the species origin of each cell, and split them into independent Seurat objects.
User Guide
mut_check Mutation Expression Query
The scFAST analysis pipeline performs single-cell transcriptome upstream analysis based on full-length sequence data, including steps such as data alignment, mutation detection and annotation, filtering, and single-cell level statistics. The standard analysis pipeline applies strict filtering on metrics such as mutation frequency, mutation type, reads/UMI/barcode support, strand bias, and population frequency. Some mutations of interest may be discarded due to not meeting filtering thresholds. The mut_check module performs targeted queries on regions of interest based on existing alignment results and returns detected mutation information for subsequent joint analysis.