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

Andermann, Tobias (author): Gothenburg University,Göteborgs universitet,Institutionen för biologi och miljövetenskap,Department of Biological and Environmental Sciences

Cano, A. (author)

Zizka, Alexander, 1986 (author): Gothenburg University,Göteborgs universitet,Institutionen för biologi och miljövetenskap,Department of Biological and Environmental Sciences

Bacon, Christine D. (author): Gothenburg University,Göteborgs universitet,Institutionen för biologi och miljövetenskap,Department of Biological and Environmental Sciences

Antonelli, Alexandre, 1978 (author): Gothenburg University,Göteborgs universitet,Institutionen för biologi och miljövetenskap,Department of Biological and Environmental Sciences

(creator_code:org_t)

Related links:: https://doi.org/10.7...; show more...; https://gup.ub.gu.se...; https://doi.org/10.7...; show less...

Abstract Subject headings

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.

NATURVETENSKAP -- Geovetenskap och miljövetenskap -- Miljövetenskap (hsv//swe)
NATURAL SCIENCES -- Earth and Related Environmental Sciences -- Environmental Sciences (hsv//eng)

By the author/editor: Andermann, Tobia ...; Cano, A.; Zizka, Alexander ...; Bacon, Christine ...; Antonelli, Alexa ...

About the subject

NATURAL SCIENCES: NATURAL SCIENCES; and Earth and Relate ...; and Environmental Sc ...

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