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SeqOthello: querying RNA-seq experiments at scale
We present SeqOthello, an ultra-fast and memory-efficient indexing structure to support arbitrary sequence query against large collections of RNA-seq experiments. It takes SeqOthello only 5 min and 19.1 GB memory to conduct a global survey of 11,658 fusion events against 10,113 TCGA Pan-Cancer RNA-s...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6194578/ https://www.ncbi.nlm.nih.gov/pubmed/30340508 http://dx.doi.org/10.1186/s13059-018-1535-9 |
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author | Yu, Ye Liu, Jinpeng Liu, Xinan Zhang, Yi Magner, Eamonn Lehnert, Erik Qian, Chen Liu, Jinze |
author_facet | Yu, Ye Liu, Jinpeng Liu, Xinan Zhang, Yi Magner, Eamonn Lehnert, Erik Qian, Chen Liu, Jinze |
author_sort | Yu, Ye |
collection | PubMed |
description | We present SeqOthello, an ultra-fast and memory-efficient indexing structure to support arbitrary sequence query against large collections of RNA-seq experiments. It takes SeqOthello only 5 min and 19.1 GB memory to conduct a global survey of 11,658 fusion events against 10,113 TCGA Pan-Cancer RNA-seq datasets. The query recovers 92.7% of tier-1 fusions curated by TCGA Fusion Gene Database and reveals 270 novel occurrences, all of which are present as tumor-specific. By providing a reference-free, alignment-free, and parameter-free sequence search system, SeqOthello will enable large-scale integrative studies using sequence-level data, an undertaking not previously practicable for many individual labs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-018-1535-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6194578 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61945782018-10-25 SeqOthello: querying RNA-seq experiments at scale Yu, Ye Liu, Jinpeng Liu, Xinan Zhang, Yi Magner, Eamonn Lehnert, Erik Qian, Chen Liu, Jinze Genome Biol Method We present SeqOthello, an ultra-fast and memory-efficient indexing structure to support arbitrary sequence query against large collections of RNA-seq experiments. It takes SeqOthello only 5 min and 19.1 GB memory to conduct a global survey of 11,658 fusion events against 10,113 TCGA Pan-Cancer RNA-seq datasets. The query recovers 92.7% of tier-1 fusions curated by TCGA Fusion Gene Database and reveals 270 novel occurrences, all of which are present as tumor-specific. By providing a reference-free, alignment-free, and parameter-free sequence search system, SeqOthello will enable large-scale integrative studies using sequence-level data, an undertaking not previously practicable for many individual labs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-018-1535-9) contains supplementary material, which is available to authorized users. BioMed Central 2018-10-19 /pmc/articles/PMC6194578/ /pubmed/30340508 http://dx.doi.org/10.1186/s13059-018-1535-9 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Method Yu, Ye Liu, Jinpeng Liu, Xinan Zhang, Yi Magner, Eamonn Lehnert, Erik Qian, Chen Liu, Jinze SeqOthello: querying RNA-seq experiments at scale |
title | SeqOthello: querying RNA-seq experiments at scale |
title_full | SeqOthello: querying RNA-seq experiments at scale |
title_fullStr | SeqOthello: querying RNA-seq experiments at scale |
title_full_unstemmed | SeqOthello: querying RNA-seq experiments at scale |
title_short | SeqOthello: querying RNA-seq experiments at scale |
title_sort | seqothello: querying rna-seq experiments at scale |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6194578/ https://www.ncbi.nlm.nih.gov/pubmed/30340508 http://dx.doi.org/10.1186/s13059-018-1535-9 |
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