00-2015[review purdue]A Critical Survey of Deconvolution Methods for Separating cell-types in Complex Tissues.pdf
00-2016[review Newman]High-throughput genomic profiling of tumor-infiltrating leukocytes.pdf
00-2016[review nature]Computational genomics tools for dissecting tumour–immune cell interactions.pdf
00-2016[review short]Digitally deconvolving the tumor microenvironment.pdf
00-2017[review]Cell-type deconvolution in epigenome-wide association studies a review and recommmendations.pdf
00-2018[review FF]Quantifying tumor-infiltrating immune cells from transcriptomics data.pdf
00-2018[review belgium]Computational deconvolution of transcriptomics data from mixed cell populations.pdf
00-2018[review frontiers]Quantitative Analyses of the Tumor Microenvironment Composition and Orientation in the Era of Precision Medicine.pdf
00-2019[review]Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology.pdf
00-2020[review BIB]Computational principles and practice for decoding immune contexture in the tumor microenvironment.pdf
00-2020[review brain]Comprehensive evaluation of human brain gene expression deconvolution methods.pdf
2004[ssKL]Metagenes and molecular pattern discovery using matrix factorization.pdf
2009[Abba]Deconvolution of blood microarray data identifies cellular activation patterns in systemic lupus erythematosus.PDF
2010[DSection]Probabilistic analysis of gene expression measurements from heterogeneous tissues.pdf
2010[ccSAM]Cell type–specific gene expression differences in complex tissues.pdf
2010[decof]Biomarker discovery in heterogeneous tissue samples taking the in silico deconfounding approach.pdf
2010[ssGSEA]Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1.pdf
2011[PSEA]Population-specific expression analysis (PSEA) reveals molecular changes in diseased brain.pdf
2011[SPEC]Cell subset prediction for blood genomic studies.pdf
2011[collapseRows]Strategies for aggregating gene expression data the collapseRows R function.pdf
2012[ABSOLUTE]Absolute quantification of somatic DNA alterations in human cancer.pdf
2012[CTen]CTen a web-based platform for identifying enriched cell types from heterogeneous microarray data.pdf
2012[PERT]PERT A Method for Expression Deconvoluition of Human Blood Samples from Varied Microenvironmental and Developmental Conditions.PDF
2012[methyISpectrum]DNA methylation arrays as surrogate measures of cell mixture distribution.pdf
2012[qpure]qpure A tool to estimate tumor cellularity from genome-wide single-nucleotide polymorphism profiles.PDF
2012[ssNMF]Semi-supervised Nonnegative Matrix Factorization for gene expression deconvolution a case study.pdf
2013[CellMix]CellMix a comprehensive toolbox for gene expression deconvolution.pdf
2013[DSA]Digital sorting of complex tissues for cell type-specific gene expression profiles.pdf
2013[DeMix]DeMix deconvolution for mixed cancer transcriptomes using raw measured data.pdf
2013[DeconRNASeq] DeconRNASeq a statistical framework for deconvolution of heterogeneous tissue samples based on mRNA-Seq data.pdf
2013[DeconRNASeq]DeconRNASeq(old bioinformatics2013).pdf
2013[ESTIMATE]Inferring tumour purity and stromal and immune cell admixture from expression data.pdf
2013[GSVA]GSVA gene set variation analysis for microarray and RNA-Seq data.pdf
2013[IOSpure]Computational purification of individual tumor gene expression profiles leads to significant improvements in prognostic prediction.pdf
2014[MMAD]MMAD microarray microdissection with analysis of differences is a computational tool for deconvoluting cell type-specific contributions from tissue samples.pdf
2016[BSEQ-sc]A single-cell transcriptomic map of the human and mouse pancreas reveals inter- and intra-cell population structure.pdf
2016[EDec]Epigenomic deconvolution of breast tumors reveals metabolic coupling between constituent cell types.pdf
2016[ImmQuant]ImmQuant a user-friendly tool for inferring immune cell-type composition from gene-expression data.pdf
2016[MCP-counter]Estimating the population abundance of tissue-infiltrating immune and stromal cell population using gene expression.pdf
2016[ccRcc]Tumor immune microenvironment characterization in clear cell renal cell carcinoma identifies prognostic and immunotherapeutically relevant messenger RNA signatures.pdf
2017[Enumerateblood]Enumerateblood an R package to estimate the cellular composition of whole blood from Affymetrix Gene ST gene expression profiles.pdf
2017[ImmuCC]Inference of immune cell composition on the expression profiles of mouse tissue.pdf
2017[Oncotarget]Data-driven analysis of immune infiltrate in a large cohort of breast cancer and its association with disease progression, ER activity, and genomic complexity.pdf
2017[SMC]A sequential Monte Carlo approach to gene expression deconvolution.pdf
2017[TIminer]TIminer NGS data mining pipeline for cancer immunology and immunotherapy.pdf
2017[infino]Infino a Batesuab hierarchical model improves estimates of immune.pdf
2017[quanTIseq-v2]Molecular and pharmacological modulators of the tumor immune contexture revealed by.pdf
2017[quanTIseq] quanTIseq quantifying immune contexture of human tumors.pdf
2017[rGEPs]Estimation of immune cell content in tumour tissue using single-cell RNA-seq data.pdf
2017[xCell]xCell digitally portraying the tissue cellualr heterogeneity landscape.pdf
2018[BRETIGEA]Brain Cell Type Specific Gene Expression and Co-expression Network Architectures.pdf
2018[CellDistinguisher]Computational de novo discovery of distinguishing genes for biological processes and cell types in complex tissues.pdf
2018[DeMixT]Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration.pdf
2018[Deblender]Deblender a semi- unsupervised multi-operational computational method for complete deconvolution of expression data from heterogeneous samples.pdf
2018[ICeD-T]ICeD-T Provides Accurate Estimates of Immune Cell Abundance in Tumor Samples by Allowing for aberrant Gene Expression Patterns.pdf
2018[ImmuCC]seq-immunCC Cell-Centric View of Tissue Transcriptome Measuring Cellular compositions of Immune Microenvironment From Mouse RNA-Seq Data.pdf
2018[MySort]A gene profiling deconvolution approach to estimating immune cell composition from complex tissues.pdf
2019[ABIS]RNA-Seq Signatures Normalized by mRNA Abundance Allow Absolute Deconvolution of Human Immune Cell Types.pdf
2019[CIBERSORTx]Determining cell type abundance and expression.pdf
2019[CPM]Cell composition analysis of bulk genomics using single-cell data.pdf
2019[CPM]Cell composition analysis of bulk genomics using single-cell data_S.pdf
2019[ConsesusTME]Comprehensive Benchmarking and integration of Tumor Microenvironment Cell Estimation Methods.pdf
2019[DECODER]De novo compartment deconvolution and weight estimation of tumor samples using DECODER.pdf
2019[Digitaldlsorter]Deep-learning on scRNA-seq to deconvolute gene expression data.pdf
2019[FARDEEP]Fast and robust deconvolution of tumor infiltrating lymphocyte from expression profiles using least trimmed squares.pdf
2019[MIXTURE]MIXTURE an improved algorithm for immune tumor microenvironment estimation based on gene expression data.pdf
2019[MuSiC]Bulk tissue cell type deconvolution with multi-subject single-cell expression reference.pdf
2019[NITUMID]Nonnegative Matrix Factorization-based Immune-TUmor MIcroenvironment Deconvolution.pdf
2019[SCDC]Bulk Gene Expression Deconvolution by Multiple Single-Cell RNA Sequencing Reference.pdf
2019[TOAST]TOAST improving reference-free cell composition estimation by cross-cell type differential analysis.pdf
2019[immunedeconv]Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology.pdf
2019[immunoStates]Leveraging heterogeneity across multiple datasets increases cell-mixture deconvolution accuracy and reduces biological and technical biases.pdf
2019[linseed]Complete deconvolution of cellular mixtures based on linearity of transcriptional signatures.pdf
2020[Bisque]Accurate estimation of cell composition in bulk expression through robust integration of single-cell information.pdf
2020[DAISM-DNN]Highly accurate cell type proportion estimation with in silico data augmentation and deep neural networks.pdf
2020[Scaden]Deep learning-based cell composition analysis from tissue expression profiles.pdf
2020[TED]Bayesian Inference of Cell Composition and Gene Expression Reveals Tumor-Microenvironment Interactions.pdf
2021[CDSeqR]fast complete deconvolution for gene expression data from bulk tissues.pdf
2022[CODEFACS]Deconvolving clinically relevant cellular immune cross-talk from bulk gene expression using CODEFASC and LIRICS stratifies patients with melanoma to anti-PD-1 therapy.pdf
2022[Kassandra]Precise reconstruction of the TME using bulk RNA-seq and a machine learning algorithm trained on artificial transcriptomes.pdf
2023[DeconV]Probabilistic cell type deconvolution from bulk RNA-sequencing data.pdf
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