Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
PathRacer : Racing Profile HMM Paths on Assembly Graph. / Shlemov, Alexander; Korobeynikov, Anton.
6th International Conference on Algorithms for Computational Biology. ред. / Carlos Martín-Vide; Miguel A. Vega-Rodríguez; Ian Holmes. Springer Nature, 2019. стр. 80-94 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 11488 LNBI).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - PathRacer
T2 - 6th International Conference on Algorithms for Computational Biology, AlCoB 2019
AU - Shlemov, Alexander
AU - Korobeynikov, Anton
PY - 2019/5/25
Y1 - 2019/5/25
N2 - 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.
AB - 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.
KW - Graph alignment
KW - Profile HMM
KW - Set of most probable paths
UR - http://www.scopus.com/inward/record.url?scp=85066111513&partnerID=8YFLogxK
UR - http://www.mendeley.com/research/pathracer-racing-profile-hmm-paths-assembly-graph
U2 - 10.1007/978-3-030-18174-1_6
DO - 10.1007/978-3-030-18174-1_6
M3 - Conference contribution
AN - SCOPUS:85066111513
SN - 9783030181734
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 80
EP - 94
BT - 6th International Conference on Algorithms for Computational Biology
A2 - Martín-Vide, Carlos
A2 - Vega-Rodríguez, Miguel A.
A2 - Holmes, Ian
PB - Springer Nature
Y2 - 28 May 2019 through 30 May 2019
ER -
ID: 42676722