| SHUGAY, Mikhail, A.R. ZARETSKY, D.A. SHAGIN, I.A. SHAGINA, I.A. VOLCHENKOV, A.A. SHELENKOV, Mikhail LEBEDIN, D.V. BAGAEV, S. LUKYANOV and Dmitriy CHUDAKOV. MAGERI: Computational pipeline for molecular-barcoded targeted resequencing. PLoS Computational Biology. SAN FRANCISCO: PUBLIC LIBRARY SCIENCE, 2017, vol. 13, No 5, p. nestránkováno, 17 pp. ISSN 1553-734X. Available from: https://dx.doi.org/10.1371/journal.pcbi.1005480. |
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@article{1411034,
author = {Shugay, Mikhail and Zaretsky, A.R. and Shagin, D.A. and Shagina, I.A. and Volchenkov, I.A. and Shelenkov, A.A. and Lebedin, Mikhail and Bagaev, D.V. and Lukyanov, S. and Chudakov, Dmitriy},
article_location = {SAN FRANCISCO},
article_number = {5},
doi = {http://dx.doi.org/10.1371/journal.pcbi.1005480},
keywords = {CIRCULATING TUMOR DNA; THERAPEUTIC RESPONSE; IMMUNE REPERTOIRES; COLORECTAL-CANCER; SOMATIC MUTATION; SEQUENCING ERROR; RARE MUTATIONS; SOLID TUMORS; GENOME; PLASMA},
language = {eng},
issn = {1553-734X},
journal = {PLoS Computational Biology},
title = {MAGERI: Computational pipeline for molecular-barcoded targeted resequencing},
url = {http://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005480&type=printable},
volume = {13},
year = {2017}
}
TY - JOUR
ID - 1411034
AU - Shugay, Mikhail - Zaretsky, A.R. - Shagin, D.A. - Shagina, I.A. - Volchenkov, I.A. - Shelenkov, A.A. - Lebedin, Mikhail - Bagaev, D.V. - Lukyanov, S. - Chudakov, Dmitriy
PY - 2017
TI - MAGERI: Computational pipeline for molecular-barcoded targeted resequencing
JF - PLoS Computational Biology
VL - 13
IS - 5
SP - nestránkováno
EP - nestránkováno
PB - PUBLIC LIBRARY SCIENCE
SN - 1553734X
KW - CIRCULATING TUMOR DNA
KW - THERAPEUTIC RESPONSE
KW - IMMUNE REPERTOIRES
KW - COLORECTAL-CANCER
KW - SOMATIC MUTATION
KW - SEQUENCING ERROR
KW - RARE MUTATIONS
KW - SOLID TUMORS
KW - GENOME
KW - PLASMA
UR - http://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005480&type=printable
L2 - http://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005480&type=printable
N2 - Unique molecular identifiers (UMIs) show outstanding performance in targeted high-throughput resequencing, being the most promising approach for the accurate identification of rare variants in complex DNA samples. This approach has application in multiple areas, including cancer diagnostics, thus demanding dedicated software and algorithms. Here we introduce MAGERI, a computational pipeline that efficiently handles all caveats of UMI-based analysis to obtain high-fidelity mutation profiles and call ultra-rare variants. Using an extensive set of benchmark datasets including gold-standard biological samples with known variant frequencies, cell-free DNA from tumor patient blood samples and publicly available UMI-encoded datasets we demonstrate that our method is both robust and efficient in calling rare variants. The versatility of our software is supported by accurate results obtained for both tumor DNA and viral RNA samples in datasets prepared using three different UMI-based protocols.
ER -
SHUGAY, Mikhail, A.R. ZARETSKY, D.A. SHAGIN, I.A. SHAGINA, I.A. VOLCHENKOV, A.A. SHELENKOV, Mikhail LEBEDIN, D.V. BAGAEV, S. LUKYANOV and Dmitriy CHUDAKOV. MAGERI: Computational pipeline for molecular-barcoded targeted resequencing. \textit{PLoS Computational Biology}. SAN FRANCISCO: PUBLIC LIBRARY SCIENCE, 2017, vol.~13, No~5, p.~nestránkováno, 17 pp. ISSN~1553-734X. Available from: https://dx.doi.org/10.1371/journal.pcbi.1005480.
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