Assessing graph-based read mappers against a baseline approach highlights strengths and weaknesses of current methods.
BMC Genomics
; 21(1): 282, 2020 Apr 06.
Article
em En
| MEDLINE
| ID: mdl-32252628
ABSTRACT
BACKGROUND:
Graph-based reference genomes have become popular as they allow read mapping and follow-up analyses in settings where the exact haplotypes underlying a high-throughput sequencing experiment are not precisely known. Two recent papers show that mapping to graph-based reference genomes can improve accuracy as compared to methods using linear references. Both of these methods index the sequences for most paths up to a certain length in the graph in order to enable direct mapping of reads containing common variants. However, the combinatorial explosion of possible paths through nearby variants also leads to a huge search space and an increased chance of false positive alignments to highly variable regions.RESULTS:
We here assess three prominent graph-based read mappers against a hybrid baseline approach that combines an initial path determination with a tuned linear read mapping method. We show, using a previously proposed benchmark, that this simple approach is able to improve overall accuracy of read-mapping to graph-based reference genomes.CONCLUSIONS:
Our method is implemented in a tool Two-step Graph Mapper, which is available at https//github.com/uio-bmi/two_step_graph_mapperalong with data and scripts for reproducing the experiments. Our method highlights characteristics of the current generation of graph-based read mappers and shows potential for improvement for future graph-based read mappers.Palavras-chave
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Biologia Computacional
Limite:
Humans
Idioma:
En
Revista:
BMC Genomics
Assunto da revista:
GENETICA
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Noruega