pRESTO: a toolkit for processing high-throughput sequencing raw reads of lymphocyte receptor repertoires

• Published in: Bioinformatics (Oxford, England) Vol. 30; no. 13; pp. 1930 - 1932
• Main Authors: Vander Heiden, Jason A., Yaari, Gur, Uduman, Mohamed, Stern, Joel N.H., O’Connor, Kevin C., Hafler, David A., Vigneault, Francois, Kleinstein, Steven H.
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.07.2014
• Subjects: Applications Notes; High-Throughput Nucleotide Sequencing - methods; Lymphocytes - immunology; Receptors, Immunologic - chemistry; Receptors, Immunologic - immunology; Sequence Analysis, DNA; Sequence Analysis, RNA; Software
• ISSN: 1367-4803; 1367-4811; 1367-4811
• DOI: 10.1093/bioinformatics/btu138

Driven by dramatic technological improvements, large-scale characterization of lymphocyte receptor repertoires via high-throughput sequencing is now feasible. Although promising, the high germline and somatic diversity, especially of B-cell immunoglobulin repertoires, presents challenges for analysis requiring the development of specialized computational pipelines. We developed the REpertoire Sequencing TOolkit (pRESTO) for processing reads from high-throughput lymphocyte receptor studies. pRESTO processes raw sequences to produce error-corrected, sorted and annotated sequence sets, along with a wealth of metrics at each step. The toolkit supports multiplexed primer pools, single- or paired-end reads and emerging technologies that use single-molecule identifiers. pRESTO has been tested on data generated from Roche and Illumina platforms. It has a built-in capacity to parallelize the work between available processors and is able to efficiently process millions of sequences generated by typical high-throughput projects. Availability and implementation: pRESTO is freely available for academic use. The software package and detailed tutorials may be downloaded from http://clip.med.yale.edu/presto . Contact:  steven.kleinstein@yale.edu Supplementary information:  Supplementary data are available at Bioinformatics online.