Evidence map›Paper›PMID 28475621›Full record

ArticlePLoS computational biology2017

MAGERI: Computational pipeline for molecular-barcoded targeted resequencing.

Mikhail Shugay, Andrew R Zaretsky, Dmitriy A Shagin, Irina A Shagina, Ivan A Volchenkov, Andrew A Shelenkov, Mikhail Y Lebedin, Dmitriy V Bagaev, Sergey Lukyanov, Dmitriy M Chudakov

Abstract read
In one paragraph

Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Urinary Nucleic Acid in Tumor: Bioinformatics Approaches.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Review
  20. Rare Event Detection Using Error-corrected DNA and RNA Sequencing.Journal of visualized experiments : JoVE · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Mikhail ShugayShemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.ORCID 0000-0001-7826-7942
Andrew R ZaretskyShemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.ORCID 0000-0002-7778-6617
Dmitriy A ShaginShemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.
Irina A ShaginaShemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.
Ivan A VolchenkovPirogov Russian National Research Medical University, Ostrovityanova 1, Moscow, Russia.
Andrew A ShelenkovPirogov Russian National Research Medical University, Ostrovityanova 1, Moscow, Russia.ORCID 0000-0002-7409-077X
Mikhail Y LebedinShemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.ORCID 0000-0002-3877-7195
Dmitriy V BagaevShemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.
Sergey LukyanovShemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.
Dmitriy M ChudakovShemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.ORCID 0000-0003-0430-790X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

SoftwareBiomarkers, TumorComputational BiologyDatabases, GeneticHigh-Throughput Nucleotide SequencingHumansNeoplasmsRNA, ViralSequence Analysis, DNASequence Analysis, RNABiomarkers, TumorRNA, Viral

Identifiers

PMID28475621
PMCPMC5419444

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.