REINDEER: efficient indexing of k-mer presence and abundance in sequencing datasets.
Bioinformatics
; 36(Suppl_1): i177-i185, 2020 07 01.
Article
em En
| MEDLINE
| ID: mdl-32657392
ABSTRACT
MOTIVATION In this work we present REINDEER, a novel computational method that performs indexing of sequences and records their abundances across a collection of datasets. To the best of our knowledge, other indexing methods have so far been unable to record abundances efficiently across large datasets. RESULTS:
We used REINDEER to index the abundances of sequences within 2585 human RNA-seq experiments in 45 h using only 56 GB of RAM. This makes REINDEER the first method able to record abundances at the scale of â¼4 billion distinct k-mers across 2585 datasets. REINDEER also supports exact presence/absence queries of k-mers. Briefly, REINDEER constructs the compacted de Bruijn graph of each dataset, then conceptually merges those de Bruijn graphs into a single global one. Then, REINDEER constructs and indexes monotigs, which in a nutshell are groups of k-mers of similar abundances. AVAILABILITY AND IMPLEMENTATION https//github.com/kamimrcht/REINDEER. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Software
/
Análise de Sequência de DNA
Limite:
Humans
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article