VDJPipe: a pipelined tool for pre-processing immune repertoire sequencing data

• Main Authors: Scott Christley, Mikhail K. Levin, Inimary T. Toby, John M. Fonner, Nancy L. Monson, William H. Rounds, Florian Rubelt, Walter Scarborough, Richard H. Scheuermann, Lindsay G. Cowell
• Format: Article
• Language: English
• Published: BMC 2017-10-01
• Series: BMC Bioinformatics
• Subjects: Rep-seq; Immune repertoire analysis; Bioinformatics
• Online Access: http://link.springer.com/article/10.1186/s12859-017-1853-z

Abstract Background Pre-processing of high-throughput sequencing data for immune repertoire profiling is essential to insure high quality input for downstream analysis. VDJPipe is a flexible, high-performance tool that can perform multiple pre-processing tasks with just a single pass over the data files. Results Processing tasks provided by VDJPipe include base composition statistics calculation, read quality statistics calculation, quality filtering, homopolymer filtering, length and nucleotide filtering, paired-read merging, barcode demultiplexing, 5′ and 3′ PCR primer matching, and duplicate reads collapsing. VDJPipe utilizes a pipeline approach whereby multiple processing steps are performed in a sequential workflow, with the output of each step passed as input to the next step automatically. The workflow is flexible enough to handle the complex barcoding schemes used in many immunosequencing experiments. Because VDJPipe is designed for computational efficiency, we evaluated this by comparing execution times with those of pRESTO, a widely-used pre-processing tool for immune repertoire sequencing data. We found that VDJPipe requires <10% of the run time required by pRESTO. Conclusions VDJPipe is a high-performance tool that is optimized for pre-processing large immune repertoire sequencing data sets.