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Bioinformatic analysis of genotype by sequencing (GBS) data with NGSEP

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Title Bioinformatic analysis of genotype by sequencing (GBS) data with NGSEP
 
Creator Perea, Claudia
Hoz, Juan Fernando de la
Cruz, Daniel Felipe
Lobaton, Juan David
Izquierdo, Paulo
Quintero, Juan Camilo
Raatz, Bodo
Duitama, Jorge
 
Subject GENOMICS
BIOINFORMATICS
GENETIC MARKERS
DNA
DATABASE
DATA ANALYSIS
BIOINFORMÁTICA
GENÓMICA
MARCADORES GENÉTICOS
ADN
ANÁLISIS DE DATOS
 
Description Background
Therecent development and availability of different genotype by sequencing (GBS) protocols provided a cost-effective approach to perform high-resolution genomic analysis of entire populations in different species. The central component of all these protocols is the digestion of the initial DNA with known restriction enzymes, to generate sequencing fragments at predictable and reproducible sites. This allows to genotype thousands of genetic markers on populations with hundreds of individuals. Because GBS protocols achieve parallel genotyping through high throughput sequencing (HTS), every GBS protocol must include a bioinformatics pipeline for analysis of HTS data. Our bioinformatics group recently developed the Next Generation Sequencing Eclipse Plugin (NGSEP) for accurate, efficient, and user-friendly analysis of HTS data.

Results
Here we present the latest functionalities implemented in NGSEP in the context of the analysis of GBS data. We implemented a one step wizard to perform parallel read alignment, variants identification and genotyping from HTS reads sequenced from entire populations. We added different filters for variants, samples and genotype calls as well as calculation of summary statistics overall and per sample, and diversity statistics per site. NGSEP includes a module to translate genotype calls to some of the most widely used input formats for integration with several tools to perform downstream analyses such as population structure analysis, construction of genetic maps, genetic mapping of complex traits and phenotype prediction for genomic selection. We assessed the accuracy of NGSEP on two highly heterozygous F1 cassava populations and on an inbred common bean population, and we showed that NGSEP provides similar or better accuracy compared to other widely used software packages for variants detection such as GATK, Samtools and Tassel.

Conclusions
NGSEP is a powerful, accurate and efficient bioinformatics software tool for analysis of HTS data, and also one of the best bioinformatic packages to facilitate the analysis and to maximize the genomic variability information that can be obtained from GBS experiments for population genomics.
Peer Review
 
Date 2016-09-06T16:38:11Z
2016-09-06T16:38:11Z
2016-08-31
 
Type Journal Article
 
Identifier Perea, Claudia; De La Hoz, Juan Fernando; Cruz, Daniel Felipe; Lobaton, Juan David; Izquierdo, Paulo; Quintero, Juan Camilo; Raatz, Bodo; Duitama, Jorge. 2016. Bioinformatic analysis of genotype by sequencing (GBS) data with NGSEP. BMC Genomics . 17(Suppl 5):498.
1471-2164
https://hdl.handle.net/10568/76973
 
Language en
 
Format 17(Suppl 5):498
 
Publisher BioMed Central Ltd.
 
Source BMC Genomics