ArticlePLoS computational biology2013
A self-directed method for cell-type identification and separation of gene expression microarrays.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Transcriptomic Evidence for Alterations in Astrocytes and Parvalbumin Interneurons in Subjects With Bipolar Disorder and Schizophrenia.Biological psychiatry · 2018Pooled it
- Computationally resolved neuroprogenitor cell biomarkers associate with human disorders.Stem cell reports · 2025Article
- Tumor microenvironment: barrier or opportunity towards effective cancer therapy.Journal of biomedical science · 2022Review
- SCISSOR™: a single-cell inferred site-specific omics resource for tumor microenvironment association study.NAR cancer · 2021Article
- Data-driven detection of subtype-specific differentially expressed genes.Scientific reports · 2021Article
- Whole-Tissue Deconvolution and scRNAseq Analysis Identify Altered Endometrial Cellular Compositions and Functionality Associated With Endometriosis.Frontiers in immunology · 2021Article
- Identification and transfer of spatial transcriptomics signatures for cancer diagnosis.Breast cancer research : BCR · 2020Article
- An Efficient and Flexible Method for Deconvoluting Bulk RNA-Seq Data with Single-Cell RNA-Seq Data.Cells · 2019Article
- Polled Digital Cell Sorter (p-DCS): Automatic identification of hematological cell types from single cell RNA-sequencing clusters.BMC bioinformatics · 2019Article
- Systems biology: perspectives on multiscale modeling in research on endocrine-related cancers.Endocrine-related cancer · 2019Review
- Cell Identity Codes: Understanding Cell Identity from Gene Expression Profiles using Deep Neural Networks.Scientific reports · 2019Article
- BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation reference.Genome biology · 2018Article
- Variation among intact tissue samples reveals the core transcriptional features of human CNS cell classes.Nature neuroscience · 2018Article
- High-throughput genomic profiling of tumor-infiltrating leukocytes.Current opinion in immunology · 2016Review
- Mathematical modelling of transcriptional heterogeneity identifies novel markers and subpopulations in complex tissues.Scientific reports · 2016Article
- Robust enumeration of cell subsets from tissue expression profiles.Nature methods · 2015Article
- Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patterns.BMC bioinformatics · 2014Article
- Article
- Computational deconvolution: extracting cell type-specific information from heterogeneous samples.Current opinion in immunology · 2013Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Gene expression analysis is generally performed on heterogeneous tissue samples consisting of multiple cell types. Current methods developed to separate heterogeneous gene expression rely on prior knowledge of the cell-type composition and/or signatures--these are not available in most public datasets. We present a novel method to identify the cell-type composition, signatures and proportions per sample without need for a-priori information. The method was successfully tested on controlled and semi-controlled datasets and performed as accurately as current methods that do require additional information. As such, this method enables the analysis of cell-type specific gene expression using existing large pools of publically available microarray datasets.
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Registered trials
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