MAPseq: highly efficient k-mer search with confidence estimates, for rRNA sequence analysis | Zendy

João F. Matias Rodrigues | Zendy; Thomas Schmidt | Zendy; Janko Tackmann | Zendy; Christian von Mering | Zendy

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MAPseq: highly efficient k-mer search with confidence estimates, for rRNA sequence analysis

Author(s) -

João F. Matias Rodrigues,

Thomas Schmidt,

Janko Tackmann,

Christian von Mering

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx517

Subject(s) - amplicon , computer science , ribosomal rna , sequence analysis , shotgun sequencing , computational biology , sequence (biology) , data mining , information retrieval , biology , dna sequencing , genetics , polymerase chain reaction , dna , gene

Ribosomal RNA profiling has become crucial to studying microbial communities, but meaningful taxonomic analysis and inter-comparison of such data are still hampered by technical limitations, between-study design variability and inconsistencies between taxonomies used.

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