TagDigger: User-Friendly Extraction of Read Counts from GBS and RAD-seq Data

In genotyping-by-sequencing (GBS) and restriction site-associated DNA sequencing (RAD-seq), read depth is important for assessing the quality of genotype calls and estimating allele dosage in polyploids.  However, existing pipelines for GBS and RAD-seq do not provide read counts in formats that are both accurate and easy to access.  Additionally, although existing pipelines allow previously-mined SNPs to be genotyped on new samples, they do not allow the user to manually specify a subset of loci to examine.  We created the software TagDigger, which includes three scripts for analyzing GBS and RAD-seq data.  The first script, tagdigger_interactive, rapidly extracts read counts and genotypes from FASTQ files using user-supplied sets of barcodes and tags.  Input and output is in CSV format so that it can be opened by spreadsheet software.  Tag sequences can also be imported from the Stacks, TASSEL-GBSv2, or TASSEL-UNEAK pipelines, and a separate file can be imported listing the names of markers to retain.  A second script, tag_manager, consolidates marker names and sequences across multiple projects.  A third script, barcode_splitter, assists with preparing FASTQ data for NCBI/EMBL-EBI/DDBJ and generates md5 checksums for FASTQ files.  TagDigger is written in Python 3, will run on a laptop with any operating system, can process ~100 million FASTQ reads per hour, does not consume hard drive space with intermediate files, and does not require programming skill to use.  The software is available at https://github.com/lvclark/tagdigger.