Evidence map›Paper›PMID 35789587›Full record

ArticleHGG advances2022

Quality control of large genome datasets.

Max Robinson, Arpita Joshi, Ansh Vidyarthi, Mary Maccoun, Sanjay Rangavajjhala, Gustavo Glusman

Abstract read
In one paragraph

Article in HGG advances, 2022. 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.

No citing paper in PubMed yet.

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

6 authors.

Max RobinsonInstitute for Systems Biology, 401 Terry Avenue N, Seattle, WA 98109, USA.
Arpita JoshiInstitute for Systems Biology, 401 Terry Avenue N, Seattle, WA 98109, USA.
Ansh VidyarthiInstitute for Systems Biology, 401 Terry Avenue N, Seattle, WA 98109, USA.
Mary MaccounInstitute for Systems Biology, 401 Terry Avenue N, Seattle, WA 98109, USA.
Sanjay RangavajjhalaInstitute for Systems Biology, 401 Terry Avenue N, Seattle, WA 98109, USA.
Gustavo GlusmanInstitute for Systems Biology, 401 Terry Avenue N, Seattle, WA 98109, USA.

Funding

Systems BiologyU19AG023122 · NIA · TRANSLATIONAL GENOMICS RESEARCH INST · PI FRED H GAGE · 2004 to 2026
$102.6M
TrainingU54EB020406 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TOGA, ARTHUR W · 2014 to 2018
$12.5M
NIA NIH HHS U19 AG023122NIBIB NIH HHS U54 EB020406
6 · The paper itself

Abstract

The 1000 Genomes Project (TGP) is a foundational resource that serves the biomedical community as a standard reference cohort for human genetic variation. There are now seven public versions of these genomes. The TGP Consortium produced the first by mapping its final data release against human reference sequence GRCh37, then "lifted over" these genomes to the improved reference sequence (GRCh38) when it was released, and remapped the original data to GRCh38 with two similar pipelines. As best-practice quality validation, the pipelines that generated these versions were benchmarked against the Genome In A Bottle Consortium's "platinum quality" genome (NA12878). The New York Genome Center recently released the results of independently resequencing the cohort at greater depth (30×), a phased version informed by the inclusion of related individuals, and independently remapped the original variant calls to GRCh38. We performed a cross-comparison evaluation of all seven versions using genome fingerprinting, which supports ultrafast genome comparison even across reference versions. We noted multiple issues, including discrepancies in cohort membership, disagreement on the overall level of variation, evidence of substandard pipeline performance on specific genomes and in specific regions of the genome, cryptic relationships between individuals, inconsistent phasing, and annotation distortions caused by the history of the reference genome itself. We therefore recommend global quality assessment by rapid genome comparisons, alongside benchmarking as part of best-practice quality assessment of large genome datasets. Our observations also help inform the decision of which version to use, to support analyses by individual researchers.

Indexed as

comparative analysisgold-standard quality benchmarkinghuman genetic variationquality assessment strategiesreference genome sequence

Identifiers

PMID35789587
PMCPMC9250042

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.