Evidence map›Paper›PMID 36747667›Full record

ArticlebioRxiv : the preprint server for biology2023

HAT:

Jeffrey K Ng, Tychele N Turner

Abstract 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.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Jeffrey K NgDepartment of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA.
Tychele N TurnerDepartment of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA.

Funding

Noncoding mutations in neurodevelopmental disordersR01MH126933 · NIMH · WASHINGTON UNIVERSITY · PI Tychele Naomi Turner · 2022 to 2026
$3.6M
Nature and contribution of noncoding, regulatory mutations in neurodevelopmental disordersR00MH117165 · NIMH · WASHINGTON UNIVERSITY · PI TURNER, TYCHELE NAOMI · 2019 to 2021
$743k
NIMH NIH HHS R00 MH117165NIMH NIH HHS R01 MH126933
6 · The paper itself

Abstract

Motivation: Results: HAT is a workflow to detect DNVs from short-read and long read sequencing data. This workflow begins with aligned read data (i.e., CRAM or BAM) from a parent-child sequenced trio and outputs DNVs. HAT detects high-quality DNVs from short-read whole-exome sequencing, short-read whole-genome sequencing, and highly accurate long-read sequencing data.

Identifiers

PMID36747667
PMCPMC9900919

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.