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Ultraplex: A rapid, flexible, all-in-one fastq demultiplexer
- Source :
- Wellcome Open Research
- Publication Year :
- 2021
- Publisher :
- F1000 Research Limited, 2021.
-
Abstract
- 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.
- Subjects :
- FASTQ format
Demultiplexer
Computer science
iCLIP
Medicine (miscellaneous)
General Biochemistry, Genetics and Molecular Biology
DNA sequencing
03 medical and health sciences
0302 clinical medicine
Software
fastq
Header
Demultiplexing
Ribosome profiling
030304 developmental biology
ribosome profiling
0303 health sciences
business.industry
Software Tool Article
Articles
UMI
Pipeline (software)
Identifier
030220 oncology & carcinogenesis
business
Computer hardware
Subjects
Details
- Language :
- English
- ISSN :
- 2398502X
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- Wellcome Open Research
- Accession number :
- edsair.doi.dedup.....9f9abb5dcec7c695a0758b0baec76e43