Systematic comparative analysis of single-nucleotide variants detection methods from single-cell RNA sequencing data
|Study ID||Alternative Stable ID||Type|
Study Datasets 1 dataset.
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In this study, we performed systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We generated SMART-seq2 data for 70 CD45- single cells, which were derived from two colorectal cancer patients (P0411 and P0413). The average sequencing depths of these cells were 1.4 million reads per cell. We also generated tumor and ... (Show More)
|Illumina HiSeq 4000||75|