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WEDGE: imputation of gene expression values from single-cell RNA-seq datasets using biased matrix decomposition

https://doi.org/10.1101/864488
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What this work says

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

inferredcites →https://doi.org/10.1016/j.cell.2015.04.044openalex-snapshot
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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.cell.2018.05.061openalex-snapshot
Recovering Gene Interactions from Single-Cell Data Using Data Diffusion
inferredcites →https://doi.org/10.1016/j.cell.2019.05.031openalex-snapshot
Comprehensive Integration of Single-Cell Data
inferredcites →https://doi.org/10.1016/j.celrep.2019.04.052openalex-snapshot
Dissecting the Single-Cell Transcriptome Network Underlying Gastric Premalignant Lesions and Early Gastric Cancer
inferredcites →https://doi.org/10.1016/j.cels.2016.08.011openalex-snapshot
A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure
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Genetic programs in human and mouse early embryos revealed by single-cell RNA sequencing
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Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain
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Integrating single-cell transcriptomic data across different conditions, technologies, and species
inferredcites →https://doi.org/10.1038/ni.3724openalex-snapshot
Maintenance of the marginal-zone B cell compartment specifically requires the RNA-binding protein ZFP36L1
inferredcites →https://doi.org/10.1038/nmeth.2930openalex-snapshot
Validation of noise models for single-cell transcriptomics
inferredcites →https://doi.org/10.1038/nmeth.4236openalex-snapshot
SC3: consensus clustering of single-cell RNA-seq data
inferredcites →https://doi.org/10.1038/nrg3833openalex-snapshot
Computational and analytical challenges in single-cell transcriptomics
inferredcites →https://doi.org/10.1038/nri799openalex-snapshot
Marginal-zone B cells
inferredcites →https://doi.org/10.1038/nsmb.2660openalex-snapshot
Single-cell RNA-Seq profiling of human preimplantation embryos and embryonic stem cells
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Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma
inferredcites →https://doi.org/10.1038/s41467-018-03405-7openalex-snapshot
An accurate and robust imputation method scImpute for single-cell RNA-seq data
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Single-cell RNA-seq denoising using a deep count autoencoder
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A human monoclonal antibody blocking SARS-CoV-2 infection
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Single-cell analysis of two severe COVID-19 patients reveals a monocyte-associated and tocilizumab-responding cytokine storm
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Challenges in unsupervised clustering of single-cell RNA-seq data
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Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris
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Lineage tracking reveals dynamic relationships of T cells in colorectal cancer
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Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing
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A single-cell atlas of the peripheral immune response in patients with severe COVID-19
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SAVER: gene expression recovery for single-cell RNA sequencing
inferredcites →https://doi.org/10.1038/s41592-019-0425-8openalex-snapshot
Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments
inferredcites →https://doi.org/10.1038/s41592-019-0537-1openalex-snapshot
Data denoising with transfer learning in single-cell transcriptomics
inferredcites →https://doi.org/10.1101/397588openalex-snapshot
Zero-preserving imputation of scRNA-seq data using low-rank approximation
inferredcites →https://doi.org/10.1101/655365openalex-snapshot
Accurate denoising of single-cell RNA-Seq data using unbiased principal component analysis
inferredcites →https://doi.org/10.1101/gr.251603.119openalex-snapshot
netNMF-sc: leveraging gene–gene interactions for imputation and dimensionality reduction in single-cell expression analysis
inferredcites →https://doi.org/10.1109/icassp.2009.4959890openalex-snapshot
Weighted nonnegative matrix factorization
inferredcites →https://doi.org/10.1109/vetecs.2005.1543265openalex-snapshot
Correlation Matrix Distance, a Meaningful Measure for Evaluation of Non-Stationary MIMO Channels
inferredcites →https://doi.org/10.1126/science.aaa1934openalex-snapshot
Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
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Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain
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Nonnegative Matrix Factorization Based on Alternating Nonnegativity Constrained Least Squares and Active Set Method
inferredcites →https://doi.org/10.1137/1.9781611971217openalex-snapshot
Solving Least Squares Problems
inferredcites →https://doi.org/10.1137/130934271openalex-snapshot
Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion
inferredcites →https://doi.org/10.1186/s13059-017-1305-0openalex-snapshot
Splatter: simulation of single-cell RNA sequencing data
inferredcites →https://doi.org/10.1186/s13059-017-1382-0openalex-snapshot
SCANPY: large-scale single-cell gene expression data analysis
inferredcites →https://doi.org/10.1186/s13059-018-1575-1openalex-snapshot
VIPER: variability-preserving imputation for accurate gene expression recovery in single-cell RNA sequencing studies
inferredcites →https://doi.org/10.1186/s13059-019-1681-8openalex-snapshot
SCRABBLE: single-cell RNA-seq imputation constrained by bulk RNA-seq data
inferredcites →https://doi.org/10.1186/s13059-020-02132-xopenalex-snapshot
A systematic evaluation of single-cell RNA-sequencing imputation methods
inferredcites →https://doi.org/10.3389/fimmu.2015.00030openalex-snapshot
Distinct Transcriptomic Features are Associated with Transitional and Mature B-Cell Populations in the Mouse Spleen

What points at this work

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

inferred← citeshttps://doi.org/10.1038/s41592-022-01480-9openalex-snapshot
Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution prediction and cell type deconvolution
inferred← citeshttps://doi.org/10.1038/s41592-024-02429-wopenalex-snapshot
Benchmarking algorithms for single-cell multi-omics prediction and integration
inferred← citeshttps://doi.org/10.1038/s41598-022-25524-4openalex-snapshot
A tensor decomposition-based integrated analysis applicable to multiple gene expression profiles without sample matching
inferred← citeshttps://doi.org/10.1039/d3na00342fopenalex-snapshot
Post COVID-19 complications and follow up biomarkers
inferred← citeshttps://doi.org/10.1049/nbt2.12115openalex-snapshot
scRNA‐seq data analysis method to improve analysis performance
inferred← citeshttps://doi.org/10.1093/bib/bbaa222openalex-snapshot
A review of computational strategies for denoising and imputation of single-cell transcriptomic data
inferred← citeshttps://doi.org/10.1093/bib/bbad040openalex-snapshot
scGGAN: single-cell RNA-seq imputation by graph-based generative adversarial network
inferred← citeshttps://doi.org/10.22266/ijies2022.1031.12openalex-snapshot
Psoriasis Identification from Gene Expression Analysis Using Relative Entropy Fuzzy Score Normalization, Genetic Weighted K-Nearest Neighbors Imputation and Hybrid Machine Learning Classifier
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