Evidence map›Paper›PMID 36993280›Full record

ArticlebioRxiv : the preprint server for biology2023

Accurate estimation of rare cell type fractions from tissue omics data via hierarchical deconvolution.

Penghui Huang, Manqi Cai, Xinghua Lu, Chris McKennan, Jiebiao Wang

Abstract readPreprint
PubMed Full text at PMC Publisher
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

5 authors.

Penghui HuangDeparment of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.
Manqi CaiDeparment of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.
Xinghua LuDepartment of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA.
Chris McKennanDeparment of Statistics, University of Pittsburgh, Pittsburgh, PA, USA.
Jiebiao WangDeparment of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.

Funding

FRAMINGHAM HEART STUDY - YEAR 5 EXAM75N92019D00031 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · 2019 to 2024
$29.8M
Methods for single-cell CRISPR screens and multiomic data: constructing powerful well-calibrated tests, circumventing unmeasured confounding, and accounting for denoising and imputationR01MH123184 · NIMH · CARNEGIE-MELLON UNIVERSITY · PI KATHRYN M ROEDER · 2020 to 2026
$3.8M
Statistical methods for population-level cell-type-specific analyses of tissue omics data for Alzheimer's diseaseR01AG080590 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Christopher McKennan, Jiebiao Wang · 2023 to 2026
$1.5M
Integration of GTEx and HuBMAP data to gain population-level cell-type-specific insightsR03OD034501 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI WANG, JIEBIAO, YAN, QI · 2022 to 2022
$315k
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
–
NHLBI NIH HHS 75N92019D00031NHLBI NIH HHS HHSN268201500001CNHLBI NIH HHS HHSN268201500001INHLBI NIH HHS N01 HC025195NIA NIH HHS R01 AG080590NIH HHS R03 OD034501NIMH NIH HHS R01 MH123184
6 · The paper itself

Abstract

Bulk transcriptomics in tissue samples reflects the average expression levels across different cell types and is highly influenced by cellular fractions. As such, it is critical to estimate cellular fractions to both deconfound differential expression analyses and infer cell type-specific differential expression. Since experimentally counting cells is infeasible in most tissues and studies,

Indexed as

Cellular deconvolutionHierarchical treePenalized regressionRNA sequencingSingle-cell data

Identifiers

PMID36993280
PMCPMC10055056

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.