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pRESTO: a toolkit for processing high-throughput sequencing raw reads of lymphocyte receptor repertoires
Jason A Vander Heiden1, Gur Yaari2, Mohamed Uduman2
1Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USA.
Unlabelled:
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.
