fenglin0 / benchmarking_variant_callersLinks
In this study, we perform 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 evaluate the performances of these tools in different read depths, genomic contexts,…
☆16Updated 6 years ago
Alternatives and similar repositories for benchmarking_variant_callers
Users that are interested in benchmarking_variant_callers are comparing it to the libraries listed below
Sorting:
- Repo for generating custom blacklist for reads originating from mitochondrial DNA to nuclear genome☆22Updated 3 years ago
- ☆18Updated last year
- scripts for the integrating ATAC-seq, RNA-seq and CHi-C paper☆25Updated 2 years ago
- Snakemake pipeline for plate scATAC-seq processing☆26Updated last year
- SCASA: Single cell transcript quantification tool☆22Updated last year
- ☆18Updated 5 years ago
- SnapHiC: Single Nucleus Analysis Pipeline for Hi-C Data☆41Updated 2 years ago
- Pipeline for Universal Mapping of ATAC-seq☆25Updated last month
- single-cell Hi-C, scHi-C, Hi-C, 3D genome, nuclear organization, tensor decomposition☆19Updated 2 years ago
- ☆19Updated 2 years ago
- Data analysis pipeline for scNT-seq (single-cell metabolically labeled new RNA tagging sequencing)☆16Updated 2 years ago
- ☆20Updated 2 years ago
- ☆12Updated 6 years ago
- Tool for modelling of mitochondrial heteroplasmy☆19Updated last year
- ☆12Updated 4 years ago
- Bead-based single-cell atac processing☆33Updated 4 years ago
- scover☆24Updated 2 years ago
- A collection of perl scripts for NGS analysis☆16Updated last year
- ☆12Updated 4 years ago
- ☆26Updated 2 years ago
- software for analysis of chromatin feature occupancy profiles from high-throughput sequencing data☆17Updated 5 years ago
- ☆23Updated last year
- Epigenetic cell-type deconvolution from Single-Cell Omic Reference profiles☆32Updated 7 months ago
- Analyzing chromatin accessibility data in R☆18Updated 2 years ago
- ☆18Updated 2 years ago
- ☆25Updated 3 years ago
- Publication Page for the Noack et al. 2021 Nature Neuroscience paper☆10Updated 3 years ago
- A method which leverages scRNA-seq data to achieve two goals: (1) to infer the cell types in which the disease-associated genes manifest …☆26Updated 3 years ago
- Tools for assessing clustering robustness☆28Updated 2 months ago
- ☆51Updated last year