ArticleNature communications2024
Community assessment of methods to deconvolve cellular composition from bulk gene expression.
Erratum issuedAbstract read
In one paragraph
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 37 papers.
0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
–field-weighted citation impact
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.
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.
Who cites it
37 citing papers in PubMed.
- Article
- PhenoMapR: scalable mapping of sample phenotypes to single-cell, spatial, and bulk transcriptomics data.bioRxiv : the preprint server for biology · 2026Article
- Temporal impact of metritis and systemic antibiotics on immune cell function inferred from the blood leukocyte transcriptome.JDS communications · 2026Article
- DeOPUS: cellular deconvolution via optimized power-transformed unmixing with shrinkage.Briefings in bioinformatics · 2026Article
- Increasing usable reads in RNA-seq protocols.iScience · 2026Article
- Benchmarking cell-type deconvolution in cross-platform transcriptomic data.Genome biology · 2026Article
- Transcriptomics of type 1 diabetes progression: a validation study in newly diagnosed patients.EBioMedicine · 2026Article
- A transcriptional signature of resting mast cells is associated with improved disease outcome in HRGenes and immunity · 2026Article
- Interpretable and scalable spatial gene set activity analysis with GESSO uncovers functional tissue architecture.bioRxiv : the preprint server for biology · 2026Article
- Network medicine and single-cell mapping identify a collagen-rich, fibrosis-associated hub module in Duchenne muscular dystrophy.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Biology-informed risk stratification of glioblastoma by integrating MRI-based intratumoral heterogeneity with clinical features: a multicenter validation study.Experimental hematology & oncology · 2026Article
- A Multiresolution Breast Cancer CIBERSORTx Resource Validated for Accuracy, Interpretive Limits, and Biological and Clinical Coherence in Tumor Microenvironment Deconvolution.Methods and protocols · 2026Article
- Mitotic catastrophe-related six-gene signature predicts prognosis, tumor immune landscape, and therapeutic response in lung adenocarcinoma.BMC medical genomics · 2026Article
- Estimating tumour immune infiltration: methodological convergence across histology and spatial technologies.Briefings in bioinformatics · 2026Review
- A guide to transcriptomic deconvolution in cancer.Nature reviews. Cancer · 2026Review
- omnideconv: a unifying framework for using and benchmarking single-cell-informed deconvolution of bulk RNA-seq data.Genome biology · 2026Article
- Non-negative matrix factorization and deconvolution as a dual simplex problem.Genome biology · 2026Article
- Machine learning prioritization identifies PANX1 as an inflammation-associated candidate regulator in lung adenocarcinoma.Frontiers in genetics · 2026Article
- Comment On: "Identification of Mitochondrial-Related Signature in Allergic Rhinitis: Novel Insights from Bioinformatics and Machine Learning" [Letter].Journal of inflammation research · 2026Article
- A review on in-silico analysis of immune cell trafficking and interactions with the tumour microenvironment.Frontiers in oncology · 2026Review
Corrections and comments
- Erratum issued
Authors and funding
41 authors.
Brian S WhiteSage Bionetworks, Seattle, WA, USA.ORCID 0000-0002-2954-4410
Aurélien de ReynièsCentre de Recherche des Cordeliers, INSERM U1138, Université Paris Cité, Paris, France.
Aaron M NewmanInstitute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA.ORCID 0000-0002-1857-8172
Joshua J WaterfallINSERM U830 and Translational Research Department, Institut Curie, PSL Research University, Paris, France.ORCID 0000-0002-3762-5050
Andrew LambSage Bionetworks, Seattle, WA, USA.
Florent PetitprezProgramme Cartes d'Identité des Tumeurs, Ligue Nationale Contre le Cancer, Paris, France.ORCID 0000-0002-5117-6466
Yating LinXiamen University, Xiamen, Fujian, China.ORCID 0000-0001-5061-5132
Rongshan YuXiamen University, Xiamen, Fujian, China.ORCID 0000-0003-2179-173X
Martin E Guerrero-GimenezInstitute of Biochemistry and Biotechnology, School of Medicine, National University of Cuyo, Mendoza, Argentina.
Sergii DomanskyiMichigan State University, East Lansing, MI, USA.
Gianni MonacoBIOGEM Institute of Molecular Biology and Genetics, Ariano Irpino, AV, Italy.ORCID 0000-0002-7863-4068
Verena ChungSage Bionetworks, Seattle, WA, USA.ORCID 0000-0002-5622-7998
Jineta BanerjeeSage Bionetworks, Seattle, WA, USA.ORCID 0000-0002-1775-3645
Daniel DerrickDepartment of Biomedical Engineering, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA.ORCID 0000-0003-3305-3507
Alberto ValdeolivasHeidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany.
Haojun LiXiamen University, Xiamen, Fujian, China.
Xu XiaoXiamen University, Xiamen, Fujian, China.ORCID 0000-0003-3743-3582
Shun WangDepartment of Pathology, Cancer Hospital, Chinese Aacdemy of Medical Science, Beijing, China.ORCID 0000-0003-1592-9587
Frank ZhengAmoyDx, Xiamen, Fujian, China.
Wenxian YangAginome Scientific, Xiamen, Fujian, China.ORCID 0000-0002-5349-9680
Carlos A CataniaLaboratory of Intelligent Systems (LABSIN), Engineering School, National University of Cuyo, Mendoza, Argentina.
Benjamin J LangDepartment of Radiation Oncology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-2205-8591
Thomas J BertusMichigan State University, East Lansing, MI, USA.
Carlo PiermarocchiMichigan State University, East Lansing, MI, USA.
Francesca P CarusoBIOGEM Institute of Molecular Biology and Genetics, Ariano Irpino, AV, Italy.ORCID 0000-0002-2206-1459
Michele CeccarelliBIOGEM Institute of Molecular Biology and Genetics, Ariano Irpino, AV, Italy.ORCID 0000-0002-4702-6617
Thomas YuSage Bionetworks, Seattle, WA, USA.
Xindi GuoSage Bionetworks, Seattle, WA, USA.
Julie BletzSage Bionetworks, Seattle, WA, USA.
John CollerStanford Functional Genomics Facility, Stanford University School of Medicine, Stanford, CA, USA.
Holden MaeckerInstitute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0003-0795-9946
Caroline DuaultInstitute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0003-2742-1668
Vida ShokoohiStanford Functional Genomics Facility, Stanford University School of Medicine, Stanford, CA, USA.
Shailja PatelTranslational Applications Service Center, Stanford University School of Medicine, Stanford, CA, USA.
Joanna E LilientalTranslational Applications Service Center, Stanford University School of Medicine, Stanford, CA, USA.
Stockard SimonSage Bionetworks, Seattle, WA, USA.
Tumor Deconvolution DREAM Challenge consortium
Julio Saez-RodriguezHeidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany.ORCID 0000-0002-8552-8976
Laura M HeiserDepartment of Biomedical Engineering, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA.ORCID 0000-0003-3330-0950
Justin GuinneySage Bionetworks, Seattle, WA, USA.
Andrew J GentlesDepartment of Biomedical Data Science, Stanford University, Stanford, CA, USA. andrewg@stanford.edu.ORCID 0000-0002-0941-9858
Funding
Stanford Cancer Immune Monitoring and Analysis Center (CIMAC)U24CA224309 · NCI · STANFORD UNIVERSITY · PI Sean Curtis Bendall, Holden T. Maecker · 2017 to 2026
$19.9MSpatial-Genomic Integrative Multi-Species Analysis of Lymph Node MetastasisU54CA209971 · NCI · STANFORD UNIVERSITY · PI NOLAN, GARRY P, PLEVRITIS, SYLVIA KATINA · 2016 to 2021
$11.0MUnderstanding the Impact of Microscale and Nanoscale Heterogeneity and ResistanceU54CA209988 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI DEMIR, EMEK, HEISER, LAURA MADELINE · 2017 to 2021
$10.3MCoordination Center for Open Collaboration in Systems BiologyU24CA209923 · NCI · SAGE BIONETWORKS · PI BLETZ, JULIE ANN · 2016 to 2021
$7.4MData-driven models of hematological cell fate decision and differentiationR01GM122085 · NIGMS · MICHIGAN STATE UNIVERSITY · PI PIERMAROCCHI, CARLO · 2016 to 2020
$1.8MNetwork models of differentiation landscapes for angiogenesis and hematopoiesisR35GM149261 · NIGMS · MICHIGAN STATE UNIVERSITY · PI Carlo Piermarocchi · 2023 to 2026
$1.5MNCI NIH HHS U24 CA209923NCI NIH HHS U24 CA224309NCI NIH HHS U54 CA209971NCI NIH HHS U54 CA209988NIGMS NIH HHS R01 GM122085NIGMS NIH HHS R35 GM149261U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01GM122085U.S. Department of Health & Human Services | National Institutes of Health (NIH) U24CA224309U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) CA209923U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) CA209971U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) CA209988
Abstract
We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.
Indexed as
CD4-Positive T-LymphocytesCD8-Positive T-LymphocytesNeoplasmsComputational BiologyDeep LearningGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLymphocytes, Tumor-InfiltratingTranscriptome
Identifiers
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.