MAGERI: Computational pipeline for molecular-barcoded targeted resequencing
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14740%2F17%3A00100339" target="_blank" >RIV/00216224:14740/17:00100339 - isvavai.cz</a>
Result on the web
<a href="http://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005480&type=printable" target="_blank" >http://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005480&type=printable</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1371/journal.pcbi.1005480" target="_blank" >10.1371/journal.pcbi.1005480</a>
Alternative languages
Result language
angličtina
Original language name
MAGERI: Computational pipeline for molecular-barcoded targeted resequencing
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10609 - Biochemical research methods
Result continuities
Project
<a href="/en/project/LQ1601" target="_blank" >LQ1601: CEITEC 2020</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
PLoS Computational Biology
ISSN
1553-734X
e-ISSN
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Volume of the periodical
13
Issue of the periodical within the volume
5
Country of publishing house
US - UNITED STATES
Number of pages
17
Pages from-to
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UT code for WoS article
000402889500008
EID of the result in the Scopus database
2-s2.0-85020126470