AutoGeneS: Automatic gene selection using multi-objective optimization for RNA-seq deconvolution
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
AutoGeneS: Automatic gene selection using multi-objective optimization for RNA-seq deconvolution
Authors
Keywords
bulk deconvolution, bulk RNA-seq, single-cell RNA-seq, multi-objective optimization, feature selection, marker genes
Journal
Cell Systems
Volume 12, Issue 7, Pages 706-715.e4
Publisher
Elsevier BV
Online
2021-06-07
DOI
10.1016/j.cels.2021.05.006
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- SciPy 1.0: fundamental algorithms for scientific computing in Python
- (2020) Pauli Virtanen et al. NATURE METHODS
- Construction of a human cell landscape at single-cell level
- (2020) Xiaoping Han et al. NATURE
- Bulk tissue cell type deconvolution with multi-subject single-cell expression reference
- (2019) Xuran Wang et al. Nature Communications
- RNA-Seq Signatures Normalized by mRNA Abundance Allow Absolute Deconvolution of Human Immune Cell Types
- (2019) Gianni Monaco et al. Cell Reports
- Cell composition analysis of bulk genomics using single-cell data
- (2019) Amit Frishberg et al. NATURE METHODS
- Determining cell type abundance and expression from bulk tissues with digital cytometry
- (2019) Aaron M. Newman et al. NATURE BIOTECHNOLOGY
- deconvSeq: Deconvolution of Cell Mixture Distribution in Sequencing Data
- (2019) Rose Du et al. BIOINFORMATICS
- Comprehensive Integration of Single-Cell Data
- (2019) Tim Stuart et al. CELL
- Complete deconvolution of cellular mixtures based on linearity of transcriptional signatures
- (2019) Konstantin Zaitsev et al. Nature Communications
- Integrating single-cell transcriptomic data across different conditions, technologies, and species
- (2018) Andrew Butler et al. NATURE BIOTECHNOLOGY
- Allergic inflammatory memory in human respiratory epithelial progenitor cells
- (2018) Jose Ordovas-Montanes et al. NATURE
- dtangle: accurate and robust cell type deconvolution
- (2018) Gregory J Hunt et al. BIOINFORMATICS
- A test metric for assessing single-cell RNA-seq batch correction
- (2018) Maren Büttner et al. NATURE METHODS
- Leveraging heterogeneity across multiple datasets increases cell-mixture deconvolution accuracy and reduces biological and technical biases
- (2018) Francesco Vallania et al. Nature Communications
- Estimation of immune cell content in tumour tissue using single-cell RNA-seq data
- (2017) Max Schelker et al. Nature Communications
- Complex heatmaps reveal patterns and correlations in multidimensional genomic data
- (2016) Zuguang Gu et al. BIOINFORMATICS
- Single-Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes
- (2016) Åsa Segerstolpe et al. Cell Metabolism
- A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure
- (2016) Maayan Baron et al. Cell Systems
- Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells
- (2015) Allon M. Klein et al. CELL
- Single Mammalian Cells Compensate for Differences in Cellular Volume and DNA Copy Number through Independent Global Transcriptional Mechanisms
- (2015) Olivia Padovan-Merhar et al. MOLECULAR CELL
- Respiratory epithelial cells orchestrate pulmonary innate immunity
- (2015) Jeffrey A Whitsett et al. NATURE IMMUNOLOGY
- Robust enumeration of cell subsets from tissue expression profiles
- (2015) Aaron M Newman et al. NATURE METHODS
- Computational deconvolution: extracting cell type-specific information from heterogeneous samples
- (2013) Shai S Shen-Orr et al. CURRENT OPINION IN IMMUNOLOGY
- Accounting for technical noise in single-cell RNA-seq experiments
- (2013) Philip Brennecke et al. NATURE METHODS
- Cell population-specific expression analysis of human cerebellum
- (2012) Alexandre Kuhn et al. BMC GENOMICS
- Collinearity: a review of methods to deal with it and a simulation study evaluating their performance
- (2012) Carsten F. Dormann et al. ECOGRAPHY
- LIBSVM
- (2012) Chih-Chung Chang et al. ACM Transactions on Intelligent Systems and Technology
- Population-specific expression analysis (PSEA) reveals molecular changes in diseased brain
- (2011) Alexandre Kuhn et al. NATURE METHODS
- Applying unmixing to gene expression data for tumor phylogeny inference
- (2010) Russell Schwartz et al. BMC BIOINFORMATICS
- Cell type–specific gene expression differences in complex tissues
- (2010) Shai S Shen-Orr et al. NATURE METHODS
- Fast unfolding of communities in large networks
- (2008) Vincent D Blondel et al. JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now