Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Recently large databases containing profile Hidden Markov Models (pHMMs) emerged. These pHMMs may represent the sequences of antibiotic resistance genes, or allelic variations amongst highly conserved housekeeping genes used for strain typing, etc. The typical application of such a database includes the alignment of contigs to pHMM hoping that the sequence of gene of interest is located within the single contig. Such a condition is often violated for metagenomes preventing the effective use of such databases. We present PathRacer—a novel standalone tool that aligns profile HMM directly to the assembly graph (performing the codon translation on fly for amino acid pHMMs). The tool provides the set of most probable paths traversed by a HMM through the whole assembly graph, regardless whether the sequence of interested is encoded on the single contig or scattered across the set of edges, therefore significantly improving the recovery of sequences of interest even from fragmented metagenome assemblies.
Original language | English |
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Title of host publication | 6th International Conference on Algorithms for Computational Biology |
Editors | Carlos Martín-Vide, Miguel A. Vega-Rodríguez, Ian Holmes |
Publisher | Springer Nature |
Pages | 80-94 |
Number of pages | 15 |
ISBN (Print) | 9783030181734 |
DOIs | |
State | Published - 25 May 2019 |
Event | 6th International Conference on Algorithms for Computational Biology, AlCoB 2019 - Berkeley, United States Duration: 28 May 2019 → 30 May 2019 |
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11488 LNBI |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference | 6th International Conference on Algorithms for Computational Biology, AlCoB 2019 |
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Country/Territory | United States |
City | Berkeley |
Period | 28/05/19 → 30/05/19 |
ID: 42676722