SECAPR-a bioinformatics pipeline for the rapid and user-friendly processing of targeted enriched Illumina sequences, from raw reads to alignments

PeerJ. 2018 Jul 13:6:e5175. doi: 10.7717/peerj.5175. eCollection 2018.


Evolutionary biology has entered an era of unprecedented amounts of DNA sequence data, as new sequencing technologies such as Massive Parallel Sequencing (MPS) can generate billions of nucleotides within less than a day. The current bottleneck is how to efficiently handle, process, and analyze such large amounts of data in an automated and reproducible way. To tackle these challenges we introduce the Sequence Capture Processor (SECAPR) pipeline for processing raw sequencing data into multiple sequence alignments for downstream phylogenetic and phylogeographic analyses. SECAPR is user-friendly and we provide an exhaustive empirical data tutorial intended for users with no prior experience with analyzing MPS output. SECAPR is particularly useful for the processing of sequence capture (synonyms: target or hybrid enrichment) datasets for non-model organisms, as we demonstrate using an empirical sequence capture dataset of the palm genus Geonoma (Arecaceae). Various quality control and plotting functions help the user to decide on the most suitable settings for even challenging datasets. SECAPR is an easy-to-use, free, and versatile pipeline, aimed to enable efficient and reproducible processing of MPS data for many samples in parallel.

Keywords: Allele phasing; Assembly; BAM; Contig; Exon capture; FASTQ; Next generation sequencing (NGS); Phylogenetics; Phylogeography; Target capture.

Grants and funding

This work was supported by the Swedish Research Council (B0569601), the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013, ERC Grant Agreement n. 331024), the Swedish Foundation for Strategic Research, the Faculty of Science at the University of Gothenburg, the David Rockefeller Center for Latin American Studies at Harvard University, and a Wallenberg Academy Fellowship to Alexandre Antonelli; and a SciLifeLab Bioinformatics Long-term Support from the Wallenberg Advanced Bioinformatics Infrastructure to Alexandre Antonelli and Bengt Oxelman. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.