Abstract
Summary: SCReadCounts is a method for a cell-level estimation of the sequencing read counts bearing a particular nucleotide at genomic positions of interest from barcoded scRNA-seq alignments. SCReadCounts generates an array of outputs, including cell-SNV matrices with the absolute variant-harboring read counts, as well as cell-SNV matrices with expressed Variant Allele Fraction (VAFRNA); we demonstrate its application to estimate cell level expression of somatic mutations and RNA-editing on cancer datasets. SCReadCounts is benchmarked against GATK and Samtools and is freely available as a 64-bit self-contained binary distribution (Linux), along with MacOS and Python installation.
Availability: https://github.com/HorvathLab/NGS/tree/master/SCReadCounts
Publisher
Cold Spring Harbor Laboratory
Reference26 articles.
1. Auwera Mauricio O. , G.A.V. der C. et al. (2002) From FastQ Data to High-Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline. Curr. Protoc. Bioinforma.
2. D.,A. et al. (2019) Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. Nat. Immunol.
3. D’Antonio-Chronowska, A. et al. (2019) Association of Human iPSC Gene Signatures and X Chromosome Dosage with Two Distinct Cardiac Differentiation Trajectories. Stem Cell Reports.
4. Dobin, A. et al. (2013) STAR: Ultrafast universal RNA-seq aligner. Bioinformatics.
5. Dong, R. et al. (2020) Single-Cell Characterization of Malignant Phenotypes and Developmental Trajectories of Adrenal Neuroblastoma. Cancer Cell.
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