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A deconvolution framework that uses single-cell sequencing plus a small benchmark data set for accurate analysis of cell type ratios in complex tissue samples

Genome Research(2024)10.1101/gr.278822.123Source: DataRank Database

A deconvolution framework that uses single-cell sequencing plus a small benchmark data set for accurate analysis of cell type ratios in complex tissue samples is a research paper published in Genome Research (2024). On theSindex it has a DataRank of 0.213. It has been cited 3 times, with 2 citing works in its 1-hop citation network.

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0.213DataRank · unranked

Scored on demand from live citation data

Deposits data Open Access3 citations · 2 citing works in its network

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Data availability

Repositories this paper deposited data in (declared in PubMed).

GEOGSE175937

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (27 grants)OA: bronzeTopics (17)IDs (PubMed, PMC, OpenAlex)Annotations (2)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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DataRank Breakdown

Base Score 98%Citation Network 2%

Base Score Contribution

0.208

From this paper's citation signal

Citation Network Contribution

4.75 × 10⁻³

From 1 citing papers with measurable signal

Learn more about DataRank methodology →

Top 2 citers driving the network score

Ranked by each citer's contribution to N(p) — log1p(C_q) divided by its reference count — out of 2 citers.

DOLPHIN advances single-cell transcriptomics beyond gene level by leveraging exon and junction reads
Nature Communications20251 citations124 referencesContributes 0.006
Platform Biological Divergence: quantifying gene-level differences between bulk and single-cell transcriptomics in breast cancer
bioRxiv (Cold Spring Harbor Laboratory)20260 citations37 referencesContributes 0.000

Authors (19)

Xiaoqian Liu ORCID,Xuesen Cheng ORCID,Yujie Jiang ORCID,Shuangxi Ji ORCID,Qingnan Liang ORCID

Live enrichment

PubMed:39586714 PMC:PMC11789644 OpenAlex:https://openalex.org/W4404687960

DoD

Grant: PC210079

DoD

Grant: P30CA016672

National Institutes of Health

Grant: R01CA239342

National Institutes of Health

Grant: 5T32CA096520-15

National Institutes of Health

Grant: K22CA234406

National Institutes of Health

Grant: CA125123

National Institutes of Health

Grant: RR024574

National Institutes of Health

Grant: S10OD018033

National Institutes of Health

Grant: S10OD023469

National Institutes of Health

Grant: S10OD025240

National Institutes of Health

Grant: P30CA125123

National Institutes of Health

Grant: P30EY002520

Human Cell Atlas Seed Network-Retina, Chan Zuckerberg Institute

Grant: CZF2019-02425

National Eye Institute

Grant: R01EY022356

National Eye Institute

Grant: R01EY018571

Human Cell Atlas Seed Network-Retina, Chan Zuckerberg Institute, NIH

Grant: R01CA268380

CPRIT

Grant: RP180684

CPRIT Core Facility Support Award

Grant: CPRIT-RP180672

CPRIT Comprehensive Cancer Epigenomics Core Facility

Grant: RP200504

NCI NIH HHS

Grant: T32 CA096520

NCRR NIH HHS

Grant: S10 RR024574

U.S. Department of Defense

CPRIT

Retinal Research Foundation

Baylor College of Medicine

Human Cell Atlas Seed Network-Breast, Chan Zuckerberg Institute, MD Anderson Colorectal Cancer

Cancer Prevention and Research Institute of Texas

bronzeLicense: cc-by-nc

journalhttps://genome.cshlp.org/content/early/2024/11/22/gr.278822.123.full.pdf

publisherhttps://genome.cshlp.org/content/early/2024/11/22/gr.278822.123.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/gr.278822.123

journalhttps://doi.org/10.1101/gr.278822.123

repositoryhttps://pubmed.ncbi.nlm.nih.gov/39586714

Fields of Study

Single-cell and spatial transcriptomics

MeSH Terms

RNA-SeqFemaleHumansMacular DegenerationOvarian NeoplasmsRetinaSequence Analysis, RNABenchmarkingSingle-Cell Analysis

Keywords

DeconvolutionBenchmark (surveying)BiologyComputer scienceComputational biologyData miningAlgorithm

Sustainable Development Goals

SDG 0: Partnerships for the goals

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A deconvolution framework that uses single-cell sequencing plus a small benchmark data set for accurate analysis of cell type ratios in complex tissue samples

FAIR Checklist

DataRank Breakdown

Top 2 citers driving the network score

Authors (19)

Funding (27 grants)

Open Access

Topics

Annotations (Europe PMC)

Related Papers (10)