Ultraplex: A rapid, flexible, all-in-one fastq demultiplexer [version 1; peer review: 2 approved]
Background: The first step of virtually all next generation sequencing analysis involves the splitting of the raw sequencing data into separate files using sample-specific barcodes, a process known as “demultiplexing”. However, we found that existing software for this purpose was either too inflexib...
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doaj-38169a00edf141d49a888e774d21ac9a2021-07-19T09:30:09ZengWellcomeWellcome Open Research2398-502X2021-06-01610.12688/wellcomeopenres.16791.118522Ultraplex: A rapid, flexible, all-in-one fastq demultiplexer [version 1; peer review: 2 approved]Oscar G Wilkins0Charlotte Capitanchik1Nicholas M. Luscombe2Jernej Ule3The Francis Crick Institute, London, UKThe Francis Crick Institute, London, UKOkinawa Institute of Science & Technology Graduate University, Okinawa, JapanThe Francis Crick Institute, London, UKBackground: The first step of virtually all next generation sequencing analysis involves the splitting of the raw sequencing data into separate files using sample-specific barcodes, a process known as “demultiplexing”. However, we found that existing software for this purpose was either too inflexible or too computationally intensive for fast, streamlined processing of raw, single end fastq files containing combinatorial barcodes. Results: Here, we introduce a fast and uniquely flexible demultiplexer, named Ultraplex, which splits a raw FASTQ file containing barcodes either at a single end or at both 5’ and 3’ ends of reads, trims the sequencing adaptors and low-quality bases, and moves unique molecular identifiers (UMIs) into the read header, allowing subsequent removal of PCR duplicates. Ultraplex is able to perform such single or combinatorial demultiplexing on both single- and paired-end sequencing data, and can process an entire Illumina HiSeq lane, consisting of nearly 500 million reads, in less than 20 minutes. Conclusions: Ultraplex greatly reduces computational burden and pipeline complexity for the demultiplexing of complex sequencing libraries, such as those produced by various CLIP and ribosome profiling protocols, and is also very user friendly, enabling streamlined, robust data processing. Ultraplex is available on PyPi and Conda and via Github.https://wellcomeopenresearch.org/articles/6-141/v1 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Oscar G Wilkins Charlotte Capitanchik Nicholas M. Luscombe Jernej Ule |
spellingShingle |
Oscar G Wilkins Charlotte Capitanchik Nicholas M. Luscombe Jernej Ule Ultraplex: A rapid, flexible, all-in-one fastq demultiplexer [version 1; peer review: 2 approved] Wellcome Open Research |
author_facet |
Oscar G Wilkins Charlotte Capitanchik Nicholas M. Luscombe Jernej Ule |
author_sort |
Oscar G Wilkins |
title |
Ultraplex: A rapid, flexible, all-in-one fastq demultiplexer [version 1; peer review: 2 approved] |
title_short |
Ultraplex: A rapid, flexible, all-in-one fastq demultiplexer [version 1; peer review: 2 approved] |
title_full |
Ultraplex: A rapid, flexible, all-in-one fastq demultiplexer [version 1; peer review: 2 approved] |
title_fullStr |
Ultraplex: A rapid, flexible, all-in-one fastq demultiplexer [version 1; peer review: 2 approved] |
title_full_unstemmed |
Ultraplex: A rapid, flexible, all-in-one fastq demultiplexer [version 1; peer review: 2 approved] |
title_sort |
ultraplex: a rapid, flexible, all-in-one fastq demultiplexer [version 1; peer review: 2 approved] |
publisher |
Wellcome |
series |
Wellcome Open Research |
issn |
2398-502X |
publishDate |
2021-06-01 |
description |
Background: The first step of virtually all next generation sequencing analysis involves the splitting of the raw sequencing data into separate files using sample-specific barcodes, a process known as “demultiplexing”. However, we found that existing software for this purpose was either too inflexible or too computationally intensive for fast, streamlined processing of raw, single end fastq files containing combinatorial barcodes. Results: Here, we introduce a fast and uniquely flexible demultiplexer, named Ultraplex, which splits a raw FASTQ file containing barcodes either at a single end or at both 5’ and 3’ ends of reads, trims the sequencing adaptors and low-quality bases, and moves unique molecular identifiers (UMIs) into the read header, allowing subsequent removal of PCR duplicates. Ultraplex is able to perform such single or combinatorial demultiplexing on both single- and paired-end sequencing data, and can process an entire Illumina HiSeq lane, consisting of nearly 500 million reads, in less than 20 minutes. Conclusions: Ultraplex greatly reduces computational burden and pipeline complexity for the demultiplexing of complex sequencing libraries, such as those produced by various CLIP and ribosome profiling protocols, and is also very user friendly, enabling streamlined, robust data processing. Ultraplex is available on PyPi and Conda and via Github. |
url |
https://wellcomeopenresearch.org/articles/6-141/v1 |
work_keys_str_mv |
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