{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T12:59:59Z","timestamp":1760101199600,"version":"3.37.3"},"reference-count":31,"publisher":"Oxford University Press (OUP)","issue":"9","license":[{"start":{"date-parts":[[2020,1,30]],"date-time":"2020-01-30T00:00:00Z","timestamp":1580342400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>High-throughput next-generation sequencing can generate huge sequence files, whose analysis requires alignment algorithms that are typically very demanding in terms of memory and computational resources. This is a significant issue, especially for machines with limited hardware capabilities. As the redundancy of the sequences typically increases with coverage, collapsing such files into compact sets of non-redundant reads has the 2-fold advantage of reducing file size and speeding-up the alignment, avoiding to map the same sequence multiple times.<\/jats:p><\/jats:sec><jats:sec><jats:title>Method<\/jats:title><jats:p>BioSeqZip generates compact and sorted lists of alignment-ready non-redundant sequences, keeping track of their occurrences in the raw files as well as of their quality score information. By exploiting a memory-constrained external sorting algorithm, it can be executed on either single- or multi-sample datasets even on computers with medium computational capabilities. On request, it can even re-expand the compacted files to their original state.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Our extensive experiments on RNA-Seq data show that BioSeqZip considerably brings down the computational costs of a standard sequence analysis pipeline, with particular benefits for the alignment procedures that typically have the highest requirements in terms of memory and execution time. In our tests, BioSeqZip was able to compact 2.7 billion of reads into 963 million of unique tags reducing the size of sequence files up to 70% and speeding-up the alignment by 50% at least.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>BioSeqZip is available at https:\/\/github.com\/bioinformatics-polito\/BioSeqZip.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa051","type":"journal-article","created":{"date-parts":[[2020,1,22]],"date-time":"2020-01-22T12:16:51Z","timestamp":1579695411000},"page":"2705-2711","source":"Crossref","is-referenced-by-count":9,"title":["<i>BioSeqZip<\/i>: a collapser of NGS redundant reads for the optimization of sequence analysis"],"prefix":"10.1093","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2672-7593","authenticated-orcid":false,"given":"Gianvito","family":"Urgese","sequence":"first","affiliation":[{"name":"Interuniversity Department of Regional and Urban Studies and Planning , Politecnico di Torino, Torino, Italy"}]},{"given":"Emanuele","family":"Parisi","sequence":"additional","affiliation":[{"name":"Department of Control and Computer Engineering , Politecnico di Torino, Torino, Italy"}]},{"given":"Orazio","family":"Scicolone","sequence":"additional","affiliation":[{"name":"Department of Control and Computer Engineering , Politecnico di Torino, Torino, Italy"}]},{"given":"Santa","family":"Di Cataldo","sequence":"additional","affiliation":[{"name":"Department of Control and Computer Engineering , Politecnico di Torino, Torino, Italy"}]},{"given":"Elisa","family":"Ficarra","sequence":"additional","affiliation":[{"name":"Department of Control and Computer Engineering , Politecnico di Torino, Torino, Italy"}]}],"member":"286","published-online":{"date-parts":[[2020,1,30]]},"reference":[{"key":"2023013110300528100_btaa051-B1","first-page":"21","article-title":"sRNAbench: profiling of small RNAs and its sequence variants in single or multi-species high-throughput experiments","volume":"1","author":"Barturen","year":"2014","journal-title":"Methods Next Gen. Seq"},{"key":"2023013110300528100_btaa051-B2","first-page":"1","article-title":"A survey of best practices for RNA-Seq data analysis","volume":"17","author":"Conesa","year":"2016","journal-title":"Genome Biol"},{"key":"2023013110300528100_btaa051-B3","doi-asserted-by":"crossref","first-page":"D662","DOI":"10.1093\/nar\/gku1010","article-title":"Ensembl 2015","volume":"43","author":"Cunningham","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2023013110300528100_btaa051-B4","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1093\/bioinformatics\/btz675","article-title":"Unification of miRNA and isomiR research: the mirGFF3 format and the mirtop API","volume":"36","author":"Desvignes","year":"2019","journal-title":"Bioinformatics"},{"key":"2023013110300528100_btaa051-B5","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1093\/bioinformatics\/bts635","article-title":"Star: ultrafast universal RNA-Seq aligner","volume":"29","author":"Dobin","year":"2013","journal-title":"Bioinformatics"},{"key":"2023013110300528100_btaa051-B6","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/1471-2105-9-11","article-title":"SeqAn an efficient, generic C++ library for sequence analysis","volume":"9","author":"Doring","year":"2008","journal-title":"BMC Bioinformatics"},{"key":"2023013110300528100_btaa051-B7","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1093\/nar\/gkr688","article-title":"miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades","volume":"40","author":"Friedl\u00e4nder","year":"2012","journal-title":"Nucleic Acids Res"},{"key":"2023013110300528100_btaa051-B7475947","doi-asserted-by":"crossref","first-page":"D132","DOI":"10.1093\/nar\/gkz885","article-title":"MirGeneDB 2.0: the metazoan microRNA complement","volume":"48","author":"Fromm","year":"2020","journal-title":"Nucleic Acids Research"},{"key":"2023013110300528100_btaa051-B8","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1146\/annurev-genet-120213-092023","article-title":"A uniform system for the annotation of vertebrate microRNA genes and the evolution of the human microRNAome","volume":"49","author":"Fromm","year":"2015","journal-title":"Annu. Rev. Genet"},{"key":"2023013110300528100_btaa051-B10","doi-asserted-by":"crossref","first-page":"1451","DOI":"10.1101\/gr.4086505","article-title":"Galaxy: a platform for interactive large-scale genome analysis","volume":"15","author":"Giardine","year":"2005","journal-title":"Genome Res"},{"key":"2023013110300528100_btaa051-B11","doi-asserted-by":"crossref","first-page":"1562","DOI":"10.1093\/bioinformatics\/btw038","article-title":"ParDRe: faster parallel duplicated reads removal tool for sequencing studies","volume":"32","author":"Gonz\u00e1lez-Dom\u00ednguez","year":"2016","journal-title":"Bioinformatics"},{"year":"2010","author":"Gordon","key":"2023013110300528100_btaa051-B12"},{"key":"2023013110300528100_btaa051-B13","doi-asserted-by":"crossref","first-page":"D140","DOI":"10.1093\/nar\/gkj112","article-title":"miRBase: microRNA sequences, targets and gene nomenclature","volume":"34 (Suppl. 1","author":"Griffiths-Jones","year":"2006","journal-title":"Nucleic Acids Res"},{"volume-title":"The Art of Computer Programming: Sorting and Searching","year":"1998","author":"Knuth","key":"2023013110300528100_btaa051-B14"},{"key":"2023013110300528100_btaa051-B15","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1038\/nmeth.1923","article-title":"Fast gapped-read alignment with Bowtie2","volume":"9","author":"Langmead","year":"2012","journal-title":"Nat. Methods"},{"key":"2023013110300528100_btaa051-B16","doi-asserted-by":"crossref","first-page":"1754","DOI":"10.1093\/bioinformatics\/btp324","article-title":"Fast and accurate short read alignment with burrows\u2013wheeler transform","volume":"25","author":"Li","year":"2009","journal-title":"Bioinformatics"},{"key":"2023013110300528100_btaa051-B17","first-page":"61","article-title":"Computational methods for quality check, preprocessing and normalization of RNA-Seq data for systems biology and analysis","volume":"2","author":"Mazzoni","year":"2016","journal-title":"Syst. Biol. Anim. Prod. Health"},{"key":"2023013110300528100_btaa051-B18","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1186\/s13059-016-0917-0","article-title":"The real cost of sequencing: scaling computation to keep pace with data generation","volume":"17","author":"Muir","year":"2016","journal-title":"Genome Biol"},{"key":"2023013110300528100_btaa051-B19","doi-asserted-by":"crossref","first-page":"4033","DOI":"10.1093\/bioinformatics\/btw575","article-title":"Rail-RNA: scalable analysis of RNA-Seq splicing and coverage","volume":"33","author":"Nellore","year":"2017","journal-title":"Bioinformatics"},{"key":"2023013110300528100_btaa051-B20","doi-asserted-by":"crossref","first-page":"D628","DOI":"10.1093\/nar\/gkj137","article-title":"BodyMap-Xs: anatomical breakdown of 17 million animal ESTs for cross-species comparison of gene expression","volume":"34","author":"Ogasawara","year":"2006","journal-title":"Nucleic Acids Res"},{"key":"2023013110300528100_btaa051-B21","doi-asserted-by":"crossref","first-page":"e34","DOI":"10.1093\/nar\/gkp1127","article-title":"SeqBuster, a bioinformatic tool for the processing and analysis of small RNAs datasets, reveals ubiquitous miRNA modifications in human embryonic cells","volume":"38","author":"Pantano","year":"2010","journal-title":"Nucleic Acids Res"},{"key":"2023013110300528100_btaa051-B22","doi-asserted-by":"crossref","first-page":"3202","DOI":"10.1093\/bioinformatics\/btr527","article-title":"A non-biased framework for the annotation and classification of the non-miRNA small RNA transcriptome","volume":"27","author":"Pantano","year":"2011","journal-title":"Bioinformatics"},{"first-page":"491","year":"2015","author":"Petersen","key":"2023013110300528100_btaa051-B23"},{"key":"2023013110300528100_btaa051-B24","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.jbiotec.2017.07.017","article-title":"The SeqAn C++ template library for efficient sequence analysis: a resource for programmers","volume":"261","author":"Reinert","year":"2017","journal-title":"J. Biotechnol"},{"key":"2023013110300528100_btaa051-B25","article-title":"Towards best practice in cancer mutation detection with whole genome and whole-exome sequencing","author":"Scherer","year":"2019","journal-title":"Nat. Biotechnol"},{"year":"2015","author":"Siragusa","key":"2023013110300528100_btaa051-B26"},{"key":"2023013110300528100_btaa051-B27","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1016\/0196-8858(81)90046-4","article-title":"Comparison of biosequences","volume":"2","author":"Smith","year":"1981","journal-title":"Adv. Appl. Math"},{"first-page":"1347","year":"2014","author":"Urgese","key":"2023013110300528100_btaa051-B28"},{"key":"2023013110300528100_btaa051-B29","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1186\/s12859-016-0958-0","article-title":"isomiR-SEA: an RNA-Seq analysis tool for miRNAs\/isomiRs expression level profiling and miRNA-mRNA interaction sites evaluation","volume":"17","author":"Urgese","year":"2016","journal-title":"BMC Bioinformatics"},{"key":"2023013110300528100_btaa051-B30","doi-asserted-by":"crossref","first-page":"e52249","DOI":"10.1371\/journal.pone.0052249","article-title":"FastUniq: a fast de novo duplicates removal tool for paired short reads","volume":"7","author":"Xu","year":"2012","journal-title":"PLoS One"},{"key":"2023013110300528100_btaa051-B31","doi-asserted-by":"crossref","DOI":"10.1093\/database\/bau110","article-title":"piRBase: a web resource assisting piRNA functional study","volume":"2014","author":"Zhang","year":"2014","journal-title":"Database"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btaa051\/32648964\/btaa051.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/9\/2705\/48985134\/bioinformatics_36_9_2705.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/9\/2705\/48985134\/bioinformatics_36_9_2705.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,25]],"date-time":"2023-09-25T13:31:53Z","timestamp":1695648713000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/36\/9\/2705\/5717961"}},"subtitle":[],"editor":[{"given":"Alfonso","family":"Valencia","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2020,1,30]]},"references-count":31,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2020,5,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btaa051","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"type":"print","value":"1367-4803"},{"type":"electronic","value":"1367-4811"}],"subject":[],"published-other":{"date-parts":[[2020,5,1]]},"published":{"date-parts":[[2020,1,30]]}}}