Evidence map›Paper›PMID 35804456›Full record

ArticleGenome biology2022

DeCAF: a novel method to identify cell-type specific regulatory variants and their role in cancer risk.

Cynthia A Kalita, Alexander Gusev

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 58% 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

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. eQTL studies: from bulk tissues to single cells.Journal of genetics and genomics = Yi chuan xue bao · 2023
    Review
  2. 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

2 authors at 2 institutions in 1 country.

Cynthia A KalitaDivision of Population Sciences, Dana-Farber Cancer Institute & Harvard Medical School, Boston, USA.ORCID 0000-0002-1561-5644
Alexander GusevDivision of Population Sciences, Dana-Farber Cancer Institute & Harvard Medical School, Boston, USA. alexander_gusev@dfci.harvard.edu.
Broad Institute · USHarvard University · US

Funding

Methods for Genome-wide Association Studies in Admixed PopulationsR01HG006399 · NHGRI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI PRICE, ALKES L · 2011 to 2024
$6.3M
Joint genomic and statistical analyses of schizophrenia and bipolar to decipher genetic susceptibilityR01MH115676 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Roel A Ophoff, Bogdan Pasaniuc · 2018 to 2026
$5.9M
SINGLE-CELL MULTI-OMIC APPROACHES TO MECHANISTICALLY CHARACTERIZE PSYCHIATRIC DISORDER RISK LOCI IN THE HUMAN BRAINR01MH125252 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LUO, CHONGYUAN · 2021 to 2025
$3.7M
Characterizing the evolutionary architecture of complex disease within and across diverse populationsR01HG012133 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI MANCUSO, NICHOLAS · 2021 to 2025
$3.6M
(PQ3) A functional genomic approach to identification and interpretation of germline-tumor genetic interactionsR01CA227237 · NCI · DANA-FARBER CANCER INST · PI GUSEV, ALEXANDER, ZAITLEN, NOAH A · 2018 to 2022
$3.5M
Characterizing non-coding somatic and germline variant interactions in ovarian cancerR01CA244569 · NCI · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI GAYTHER, SIMON ANDREW, GUSEV, ALEXANDER · 2020 to 2024
$3.3M
NCI NIH HHS R01 CA227237NCI NIH HHS R01 CA244569NHGRI NIH HHS R01 HG006399NHGRI NIH HHS R01 HG012133NIH HHS R01CA227237NIH HHS R01CA244569NIMH NIH HHS R01 MH115676NIMH NIH HHS R01 MH125252
6 · The paper itself

Abstract

Here, we propose DeCAF (DEconvoluted cell type Allele specific Function), a new method to identify cell-fraction (cf) QTLs in tumors by leveraging both allelic and total expression information. Applying DeCAF to RNA-seq data from TCGA, we identify 3664 genes with cfQTLs (at 10% FDR) in 14 cell types, a 5.63× increase in discovery over conventional interaction-eQTL mapping. cfQTLs replicated in external cell-type-specific eQTL data are more enriched for cancer risk than conventional eQTLs. Our new method, DeCAF, empowers the discovery of biologically meaningful cfQTLs from bulk RNA-seq data in moderately sized studies.

Indexed as

NeoplasmsPolymorphism, Single NucleotideAllelesGenome-Wide Association StudyQuantitative Trait LociRNA-Seq

Identifiers

PMID35804456
PMCPMC9264694
OpenAlexW4284894871

What OpenQuestion holds

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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.