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A novel computational complete deconvolution method using RNA-seq data

https://doi.org/10.1101/496596
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/path.4287openalex-snapshot
Towards the introduction of the ‘Immunoscore’ in the classification of malignant tumours
inferredcites →https://doi.org/10.1016/j.cell.2017.05.035openalex-snapshot
Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing
inferredcites →https://doi.org/10.1016/j.coi.2013.09.015openalex-snapshot
Computational deconvolution: extracting cell type-specific information from heterogeneous samples
inferredcites →https://doi.org/10.1016/j.immuni.2016.02.025openalex-snapshot
Integrative Analyses of Colorectal Cancer Show Immunoscore Is a Stronger Predictor of Patient Survival Than Microsatellite Instability
inferredcites →https://doi.org/10.1016/j.meegid.2011.08.014openalex-snapshot
Semi-supervised Nonnegative Matrix Factorization for gene expression deconvolution: A case study
inferredcites →https://doi.org/10.1016/j.tig.2012.07.003openalex-snapshot
Coordinating genome expression with cell size
inferredcites →https://doi.org/10.1038/ng.3225openalex-snapshot
Stromal gene expression defines poor-prognosis subtypes in colorectal cancer
inferredcites →https://doi.org/10.1038/nm.3909openalex-snapshot
The prognostic landscape of genes and infiltrating immune cells across human cancers
inferredcites →https://doi.org/10.1038/nm.3915openalex-snapshot
Toward understanding and exploiting tumor heterogeneity
inferredcites →https://doi.org/10.1038/nmeth.1439openalex-snapshot
Cell type–specific gene expression differences in complex tissues
inferredcites →https://doi.org/10.1038/nmeth.1710openalex-snapshot
Population-specific expression analysis (PSEA) reveals molecular changes in diseased brain
inferredcites →https://doi.org/10.1038/nmeth.1830openalex-snapshot
Gene expression deconvolution in linear space
inferredcites →https://doi.org/10.1038/nmeth.3337openalex-snapshot
Robust enumeration of cell subsets from tissue expression profiles
inferredcites →https://doi.org/10.1038/nmeth.4292openalex-snapshot
Normalizing single-cell RNA sequencing data: challenges and opportunities
inferredcites →https://doi.org/10.1038/nrg.2015.16openalex-snapshot
Single-cell genome sequencing: current state of the science
inferredcites →https://doi.org/10.1038/nrg.2016.67openalex-snapshot
Computational genomics tools for dissecting tumour–immune cell interactions
inferredcites →https://doi.org/10.1073/pnas.0307752101openalex-snapshot
Finding scientific topics
inferredcites →https://doi.org/10.1073/pnas.1832361100openalex-snapshot
Expression deconvolution: A reinterpretation of DNA microarray data reveals dynamic changes in cell populations
inferredcites →https://doi.org/10.1093/bioinformatics/17.suppl_1.s279openalex-snapshot
Separation of samples into their constituents using gene expression data
inferredcites →https://doi.org/10.1093/bioinformatics/btp378openalex-snapshot
ISOLATE: a computational strategy for identifying the primary origin of cancers using high-throughput sequencing
inferredcites →https://doi.org/10.1093/bioinformatics/btq406openalex-snapshot
Probabilistic analysis of gene expression measurements from heterogeneous tissues
inferredcites →https://doi.org/10.1093/bioinformatics/btt090openalex-snapshot
DeconRNASeq: a statistical framework for deconvolution of heterogeneous tissue samples based on mRNA-Seq data
inferredcites →https://doi.org/10.1093/bioinformatics/bty019openalex-snapshot
Computational deconvolution of transcriptomics data from mixed cell populations
inferredcites →https://doi.org/10.1137/1.9780898717754openalex-snapshot
Assignment Problems
inferredcites →https://doi.org/10.1162/089976600300015565openalex-snapshot
New Support Vector Algorithms
inferredcites →https://doi.org/10.1162/jmlr.2003.3.4-5.993openalex-snapshot
10.1162/jmlr.2003.3.4-5.993
inferredcites →https://doi.org/10.1186/1471-2105-14-89openalex-snapshot
Digital sorting of complex tissues for cell type-specific gene expression profiles
inferredcites →https://doi.org/10.1186/1471-2105-14-s1-s11openalex-snapshot
Accurate prediction of protein enzymatic class by N-to-1 Neural Networks
inferredcites →https://doi.org/10.1186/1471-2105-14-s5-s11openalex-snapshot
A mixture model for expression deconvolution from RNA-seq in heterogeneous tissues
inferredcites →https://doi.org/10.1186/gm433openalex-snapshot
Computational purification of individual tumor gene expression profiles leads to significant improvements in prognostic prediction
inferredcites →https://doi.org/10.1186/s13059-016-1028-7openalex-snapshot
Comprehensive analyses of tumor immunity: implications for cancer immunotherapy
inferredcites →https://doi.org/10.1186/s13059-017-1256-5openalex-snapshot
Revisit linear regression-based deconvolution methods for tumor gene expression data
inferredcites →https://doi.org/10.1371/journal.pcbi.1002838openalex-snapshot
PERT: A Method for Expression Deconvolution of Human Blood Samples from Varied Microenvironmental and Developmental Conditions
inferredcites →https://doi.org/10.2307/2291091openalex-snapshot
Bayes Factors
inferredcites →https://doi.org/10.5555/944919.944937openalex-snapshot
Latent dirichlet allocation

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1016/j.cels.2021.05.006openalex-snapshot
AutoGeneS: Automatic gene selection using multi-objective optimization for RNA-seq deconvolution
inferred← citeshttps://doi.org/10.1038/s41467-021-23949-5openalex-snapshot
Single cell derived mRNA signals across human kidney tumors
inferred← citeshttps://doi.org/10.1101/2020.03.19.998815openalex-snapshot
Single cell derived mRNA signals across human kidney tumors
inferred← citeshttps://doi.org/10.1186/s13059-020-1942-6openalex-snapshot
A framework for transcriptome-wide association studies in breast cancer in diverse study populations
inferred← citeshttps://doi.org/10.1186/s13059-025-03897-9openalex-snapshot
A robust workflow to benchmark deconvolution of multi-omic data
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