Evidence map›Paper›PMID 26069264›Full record

ArticleBioinformatics (Oxford, England)2015

A parallel and sensitive software tool for methylation analysis on multicore platforms.

Joaquín Tárraga, Mariano Pérez, Juan M Orduña, José Duato, Ignacio Medina, Joaquín Dopazo

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Joaquín TárragaDepartment of Computational Genomics, Centro de Investigación Príncipe Felipe.
Mariano PérezDepartamento de Informática, Universidad de Valencia and.
Juan M OrduñaDepartamento de Informática, Universidad de Valencia and.
José DuatoDISCA, Universidad Politécnica de Valencia, Valencia, Spain.
Ignacio MedinaDepartment of Computational Genomics, Centro de Investigación Príncipe Felipe.
Joaquín DopazoDepartment of Computational Genomics, Centro de Investigación Príncipe Felipe.
Centro de Investigacion Principe Felipe · ESUniversitat de València · ESUniversitat Politècnica de València · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationDNA methylation analysis suffers from very long processing time, as the advent of Next-Generation Sequencers has shifted the bottleneck of genomic studies from the sequencers that obtain the DNA samples to the software that performs the analysis of these samples. The existing software for methylation analysis does not seem to scale efficiently neither with the size of the dataset nor with the length of the reads to be analyzed. As it is expected that the sequencers will provide longer and longer reads in the near future, efficient and scalable methylation software should be developed.

resultsWe present a new software tool, called HPG-Methyl, which efficiently maps bisulphite sequencing reads on DNA, analyzing DNA methylation. The strategy used by this software consists of leveraging the speed of the Burrows-Wheeler Transform to map a large number of DNA fragments (reads) rapidly, as well as the accuracy of the Smith-Waterman algorithm, which is exclusively employed to deal with the most ambiguous and shortest reads. Experimental results on platforms with Intel multicore processors show that HPG-Methyl significantly outperforms in both execution time and sensitivity state-of-the-art software such as Bismark, BS-Seeker or BSMAP, particularly for long bisulphite reads. AVAILABILITY AND IMPLEMENTATION: Software in the form of C libraries and functions, together with instructions to compile and execute this software. Available by sftp to anonymous@clariano.uv.es (password 'anonymous'). CONTACT: juan.orduna@uv.es or jdopazo@cipf.es.

Indexed as

SoftwareAlgorithmsBase SequenceDatabases, GeneticDNA MethylationGenomeGenomicsHigh-Throughput Nucleotide SequencingHumansMolecular Sequence DataMutationMutation RateSulfitesTime Factorshydrogen sulfiteSulfites

Identifiers

PMID26069264
PMCPMC4679392
OpenAlexW2200334237

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.