Evidence map›Paper›PMID 31099384›Full record

ArticleBioinformatics (Oxford, England)2019

NGSEP3: accurate variant calling across species and sequencing protocols.

Daniel Tello, Juanita Gil, Cristian D Loaiza, John J Riascos, Nicolás Cardozo, Jorge Duitama

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

51 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Daniel TelloSystems and Computing Engineering Department, Universidad de los Andes, Bogotá 111711, Colombia.
Juanita GilSystems and Computing Engineering Department, Universidad de los Andes, Bogotá 111711, Colombia.
Cristian D LoaizaBiotechnology lab, Centro de Investigación de la caña de azúcar de Colombia, CENICAÑA, Cali 760046, Colombia.
John J RiascosBiotechnology lab, Centro de Investigación de la caña de azúcar de Colombia, CENICAÑA, Cali 760046, Colombia.
Nicolás CardozoSystems and Computing Engineering Department, Universidad de los Andes, Bogotá 111711, Colombia.
Jorge DuitamaSystems and Computing Engineering Department, Universidad de los Andes, Bogotá 111711, Colombia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationAccurate detection, genotyping and downstream analysis of genomic variants from high-throughput sequencing data are fundamental features in modern production pipelines for genetic-based diagnosis in medicine or genomic selection in plant and animal breeding. Our research group maintains the Next-Generation Sequencing Experience Platform (NGSEP) as a precise, efficient and easy-to-use software solution for these features.

resultsUnderstanding that incorrect alignments around short tandem repeats are an important source of genotyping errors, we implemented in NGSEP new algorithms for realignment and haplotype clustering of reads spanning indels and short tandem repeats. We performed extensive benchmark experiments comparing NGSEP to state-of-the-art software using real data from three sequencing protocols and four species with different distributions of repetitive elements. NGSEP consistently shows comparative accuracy and better efficiency compared to the existing solutions. We expect that this work will contribute to the continuous improvement of quality in variant calling needed for modern applications in medicine and agriculture. AVAILABILITY AND IMPLEMENTATION: NGSEP is available as open source software at http://ngsep.sf.net. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

High-Throughput Nucleotide SequencingSoftwareAlgorithmsGenomicsINDEL MutationSequence Analysis, DNA

Identifiers

PMID31099384
PMCPMC6853766

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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.