IVA: accurate de novo assembly of RNA virus genomes
| Autor: | Jacqui Brener, Jacqueline A. Keane, Philip J. R. Goulder, Bridget Ferns, Martin Hunt, Thomas D. Otto, Swee Hoe Ong, Astrid Gall, Eleni Nastouli, Paul Kellam |
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| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Technology
viruses Sequence assembly HIV Infections SEQUENCE DATA Biochemistry Genome Polymerase Chain Reaction Genetics education.field_of_study biology High-Throughput Nucleotide Sequencing 3. Good health Computer Science Applications Computational Mathematics Computational Theory and Mathematics Influenza A virus Physical Sciences Computer Science Interdisciplinary Applications Life Sciences & Biomedicine Statistics and Probability Biochemistry & Molecular Biology Sequence analysis Bioinformatics Statistics & Probability Population Genome Viral Virus Biochemical Research Methods Influenza Human Humans RNA Viruses education Molecular Biology 01 Mathematical Sciences Whole genome sequencing Science & Technology RNA RNA virus Sequence Analysis DNA 06 Biological Sciences biology.organism_classification Genome Analysis Applications Notes Influenza B virus Biotechnology & Applied Microbiology Computer Science HIV-1 Mathematical & Computational Biology 08 Information and Computing Sciences sense organs Mathematics Software |
| Zdroj: | Bioinformatics |
| ISSN: | 1367-4811 |
| Popis: | Motivation: An accurate genome assembly from short read sequencing data is critical for downstream analysis, for example allowing investigation of variants within a sequenced population. However, assembling sequencing data from virus samples, especially RNA viruses, into a genome sequence is challenging due to the combination of viral population diversity and extremely uneven read depth caused by amplification bias in the inevitable reverse transcription and polymerase chain reaction amplification process of current methods. Results: We developed a new de novo assembler called IVA (Iterative Virus Assembler) designed specifically for read pairs sequenced at highly variable depth from RNA virus samples. We tested IVA on datasets from 140 sequenced samples from human immunodeficiency virus-1 or influenza-virus-infected people and demonstrated that IVA outperforms all other virus de novo assemblers. Availability and implementation: The software runs under Linux, has the GPLv3 licence and is freely available from http://sanger-pathogens.github.io/iva Contact: iva@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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