Evidence map›Paper›PMID 38360541›Full record

ReviewAnnual review of genomics and human genetics2024

RNA Sequencing in Disease Diagnosis.

Craig Smail, Stephen B Montgomery

Open access · hybridAbstract readReview
In one paragraph

Review in Annual review of genomics and human genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
12.5field-weighted citation impact, top 1% of its field
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

25 citing papers in PubMed, 18 citations in OpenAlex.

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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

2 authors at 2 institutions in 1 country.

Craig SmailGenomic Medicine Center, Children's Mercy Research Institute, Children's Mercy Kansas City, Kansas City, Missouri, USA; email: csmail@cmh.edu.
Stephen B MontgomeryDepartment of Biomedical Data Science, Department of Genetics, and Department of Pathology, Stanford University School of Medicine, Stanford, California, USA; email: smontgom@stanford.edu.
Mercy Research · USStanford University · US

Funding

Stanford Mendelian Genomics Research CenterU01HG011762 · NHGRI · STANFORD UNIVERSITY · PI Jonathan Adam Bernstein, Stephen Montgomery · 2021 to 2026
$16.7M
Mapping causal genetic processes in non-Mendelian pediatric rare diseaseR35GM146966 · NIGMS · CHILDREN'S MERCY HOSP (KANSAS CITY, MO) · PI Craig Smail · 2022 to 2026
$1.9M
NHGRI NIH HHS U01 HG011762NIGMS NIH HHS R35 GM146966
6 · The paper itself

Abstract

RNA sequencing (RNA-seq) enables the accurate measurement of multiple transcriptomic phenotypes for modeling the impacts of disease variants. Advances in technologies, experimental protocols, and analysis strategies are rapidly expanding the application of RNA-seq to identify disease biomarkers, tissue- and cell-type-specific impacts, and the spatial localization of disease-associated mechanisms. Ongoing international efforts to construct biobank-scale transcriptomic repositories with matched genomic data across diverse population groups are further increasing the utility of RNA-seq approaches by providing large-scale normative reference resources. The availability of these resources, combined with improved computational analysis pipelines, has enabled the detection of aberrant transcriptomic phenotypes underlying rare diseases. Further expansion of these resources, across both somatic and developmental tissues, is expected to soon provide unprecedented insights to resolve disease origin, mechanism of action, and causal gene contributions, suggesting the continued high utility of RNA-seq in disease diagnosis.

Indexed as

Sequence Analysis, RNAHumansTranscriptomegenetic diseaseRNA sequencingtranscriptomics

Identifiers

PMID38360541
PMCPMC12135028
OpenAlexW4391880292

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.