Common Mitochondrial Deletions in RNA-Seq: Evaluation of Bulk, Single-Cell and Spatial Transcriptomic Datasets
This repository contains code accompanying the following paper:
Omidsalar et al. "Common Mitochondrial Deletions in RNA-Seq: Evaluation of Bulk, Single-Cell, and Spatial Transcriptomic Datasets" [Link TBA]
In the paper, Common Mitochondrial Deletions in RNA-Seq: Evaluation of Bulk, Single-Cell and Spatial Transcriptomic Datasets, we evaluated a variety of RNA-Seq datasets for common mitochondrial DNA (mtDNA) deletions using the bioinformatics tool Splice-Break2. The scripts within this repository were used for processing our data in conjunction with Splice-Break2.
We have also included RNA-Seq_SpliceBreak2_BestPractices.pdf to help guide users with workflow and command lines for running Splice-Break2 on RNA-Seq data.
Each directory contains README files with additional information and usage instructions.
This directory contains references to the studies used in this paper and their corresponding accession information.
This directory contains two command-line scripts can be used to convert fastq files downloaded from GEO using default settings into a format that is suitable for Splice-Break2, and will run Splice-Break2 when executed. ProcessSE_SRR_for_SB.sh can be run on single-end fastq files and ProcessPE_SRR_for_SB.sh can be run on paired-end fastq files.
This directory contains two scripts that can be used to search for and isolate reads that contain the 8471-13449 mtDNA "Common Deletion" and the 6335-13999 mtDNA deletion, respectively.
This directory contains two scripts: one that can be used to split 10x Genomics bam files into cluster-specific bam files and another to extract barcodes from reads containing a 6335-13999 or 8471-13449 deletion.
This directory contains the R scripts used for Seurat clustering and tissue image annotation.
Audrey Omidsalar: aomidsal@usc.edu
Brooke Hjelm: bhjelm@usc.edu