Medical Sciences Commons^™

Red Panda: A Novel Method For Detecting Variants In Single-Cell Rna Sequencing, Adam Cornish, Shrabasti Roychoudhury, Krishna Sarma, Suravi Pramanik, Kishor Bhakat, A T. Dudley, Nitish K. Mishra, Chittibabu Guda

Journal Articles: Genetics, Cell Biology & Anatomy

BACKGROUND: Single-cell sequencing enables us to better understand genetic diseases, such as cancer or autoimmune disorders, which are often affected by changes in rare cells. Currently, no existing software is aimed at identifying single nucleotide variations or micro (1-50 bp) insertions and deletions in single-cell RNA sequencing (scRNA-seq) data. Generating high-quality variant data is vital to the study of the aforementioned diseases, among others.

RESULTS: In this study, we report the design and implementation of Red Panda, a novel method to accurately identify variants in scRNA-seq data. Variants were called on scRNA-seq data from human articular chondrocytes, mouse embryonic fibroblasts …