Systematic comparative analysis of single-nucleotide variant detection methods from single-cell RNA sequencing data

Dataset ID Technology Samples
EGAD00001005373 Illumina HiSeq 4000 75

Dataset Description

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 adjacent normal bulk WES data, as well as tumor bulk RNA-seq data for these patients.

Data Use Conditions


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Label Code Version Modifier
obsolete research use only DUO:0000014 2019-01-07
publication required DUO:0000019 2019-01-07
user specific restriction DUO:0000026 2019-01-07
institution specific restriction DUO:0000028 2019-01-07
health or medical or biomedical research DUO:0000006 2019-01-07