ArticleNature communications2019
De novo compartment deconvolution and weight estimation of tumor samples using DECODER.
Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
- Purity Independent Subtyping of Tumors (PurIST) Pancreatic Cancer Classifier: Analytic Validation of a 16-RNA Expression Signature Distinguishing Basal and Classical Subtypes.The Journal of molecular diagnostics : JMD · 2024Trial
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- REG4 serves as a prognostic biomarker for pancreatic cancer with long-standing diabetes mellitus by modulating chemoresistance.Translational oncology · 2026Article
- Human pancreatic progenitor organoids define genetic and epigenetic barriers to early PDAC transformation.Developmental cell · 2026Article
- DeCAF defines clinical fibroblast subtypes and multidimensional tumor-stroma crosstalk shaping prognosis and immunotherapy response.Cell reports. Medicine · 2026Article
- Comparative evaluation of reference-free transcriptomic deconvolution highlights the importance of biological validation in astrocytes across Alzheimer's disease.Frontiers in bioinformatics · 2026Article
- Cross-platform comparison of gene expression-based cancer molecular subtyping reveals discrepancies with exome capture methods.NPJ precision oncology · 2025Article
- Approaching the holistic transcriptome-convolution and deconvolution in transcriptomics.Briefings in bioinformatics · 2025Review
- Bioinformatics perspectives on transcriptomics: A comprehensive review of bulk and single-cell RNA sequencing analyses.Quantitative biology (Beijing, China) · 2025Review
- Advances and applications in single-cell and spatial genomics.Science China. Life sciences · 2025Review
- Tumor-Intrinsic Kinome Landscape of Pancreatic Cancer Reveals New Therapeutic Approaches.Cancer discovery · 2025Article
- Applications of AI to single-cell and spatial transcriptomics: current state-of-the-art and challenges.Frontiers in bioinformatics · 2025Review
- Single-Cell Transcriptomics Reveals Cellular Heterogeneity and Drivers in Serrated Pathway-Driven Colorectal Cancer Progression.International journal of molecular sciences · 2024Article
- Robust estimation of cancer and immune cell-type proportions from bulk tumor ATAC-Seq data.eLife · 2024Article
- Updates in Molecular Profiling of Pancreatic Ductal Adenocarcinoma.The Surgical clinics of North America · 2024Review
- Mitochondrial genetic variations in leukemia: a comprehensive overview.Blood science (Baltimore, Md.) · 2024Review
- Tumor phylogeography reveals block-shaped spatial heterogeneity and the mode of evolution in Hepatocellular Carcinoma.Nature communications · 2024Article
- Frozen tissue coring and layered histological analysis improves cell type-specific proteogenomic characterization of pancreatic adenocarcinoma.Clinical proteomics · 2024Article
- DECOMICS, a shiny application for unsupervised cell type deconvolution and biological interpretation of bulk omic data.Bioinformatics advances · 2024Article
- Sub-Cluster Identification through Semi-Supervised Optimization of Rare-Cell Silhouettes (SCISSORS) in single-cell RNA-sequencing.Bioinformatics (Oxford, England) · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Tumors are mixtures of different compartments. While global gene expression analysis profiles the average expression of all compartments in a sample, identifying the specific contribution of each compartment remains a challenge. With the increasing recognition of the importance of non-neoplastic components, the ability to breakdown the gene expression contribution of each is critical. Here, we develop DECODER, an integrated framework which performs de novo deconvolution and single-sample compartment weight estimation. We use DECODER to deconvolve 33 TCGA tumor RNA-seq data sets and show that it may be applied to other data types including ATAC-seq. We demonstrate that it can be utilized to reproducibly estimate cellular compartment weights in pancreatic cancer that are clinically meaningful. Application of DECODER across cancer types advances the capability of identifying cellular compartments in an unknown sample and may have implications for identifying the tumor of origin for cancers of unknown primary.
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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.