Evidence map›Paper›PMID 38045311›Full record

ArticlebioRxiv : the preprint server for biology2023

Genome-wide detection of somatic mosaicism at short tandem repeats.

Aarushi Sehgal, Helyaneh Ziaei-Jam, Andrew Shen, Melissa Gymrek

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Aarushi SehgalDepartment of Computer Science and Engineering, University of California San Diego, La Jolla, USA.
Helyaneh Ziaei-JamDepartment of Computer Science and Engineering, University of California San Diego, La Jolla, USA.
Andrew ShenDepartment of Computer Science and Engineering, University of California San Diego, La Jolla, USA.
Melissa GymrekDepartment of Computer Science and Engineering, University of California San Diego, La Jolla, USA.
University of California San Diego · US

Funding

Refining Mendelian disease analysis via detection of clinically relevant repeat variantsR01HG010149 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Vineet Bafna, Vikas Bansal · 2018 to 2026
$4.5M
NHGRI NIH HHS R01 HG010149
6 · The paper itself

Abstract

Motivation: Somatic mosaicism, in which a mutation occurs post-zygotically, has been implicated in several developmental disorders, cancers, and other diseases. Short tandem repeats (STRs) consist of repeated sequences of 1-6bp and comprise more than 1 million loci in the human genome. Somatic mosaicism at STRs is known to play a key role in the pathogenicity of loci implicated in repeat expansion disorders and is highly prevalent in cancers exhibiting microsatellite instability. While a variety of tools have been developed to genotype germline variation at STRs, a method for systematically identifying mosaic STRs (mSTRs) is lacking. Results: We introduce prancSTR, a novel method for detecting mSTRs from individual high-throughput sequencing datasets. Unlike many existing mosaicism detection methods for other variant types, prancSTR does not require a matched control sample as input. We show that prancSTR accurately identifies mSTRs in simulated data and demonstrate its feasibility by identifying candidate mSTRs in whole genome sequencing (WGS) data derived from lymphoblastoid cell lines for individuals sequenced by the 1000 Genomes Project. Our analysis identified an average of 76 and 577 non-homopolymer and homopolymer mSTRs respectively per cell line as well as multiple cell lines with outlier mSTR counts more than 6 times the population average, suggesting a subset of cell lines have particularly high STR instability rates. Availability: prancSTR is freely available at https://github.com/gymrek-lab/trtools. Documentation: Detailed documentation is available at https://trtools.readthedocs.io/.

Identifiers

PMID38045311
PMCPMC10690266
OpenAlexW4388946501

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.