scIMC: a platform for benchmarking comparison and visualization analysis of scRNA-seq data imputation methods

Deep learning shapes single-cell data analysis

(2022) Qin Ma et al.   NATURE REVIEWS MOLECULAR CELL BIOLOGY

scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses

(2021) Juexin Wang et al.   Nature Communications

Imputing single-cell RNA-seq data by combining graph convolution and autoencoder neural networks

(2021) Jiahua Rao et al.   iScience

SDImpute: A statistical block imputation method based on cell-level and gene-level information for dropouts in single-cell RNA-seq data

(2021) Jing Qi et al.   PLoS Computational Biology

scTSSR: gene expression recovery for single-cell RNA sequencing using two-side sparse self-representation

(2020) Ke Jin et al.   BIOINFORMATICS

netNMF-sc: leveraging gene–gene interactions for imputation and dimensionality reduction in single-cell expression analysis

(2020) Rebecca Elyanow et al.   GENOME RESEARCH

scIGANs: single-cell RNA-seq imputation using generative adversarial networks

(2020) Yungang Xu et al.   NUCLEIC ACIDS RESEARCH

Imputing missing RNA-sequencing data from DNA methylation by using a transfer learning–based neural network

(2020) Xiang Zhou et al.   GigaScience

Impact of data preprocessing on cell-type clustering based on single-cell RNA-seq data

(2020) Chunxiang Wang et al.   BMC BIOINFORMATICS

Single-cell RNA-seq denoising using a deep count autoencoder

(2019) Gökcen Eraslan et al.   Nature Communications

scNPF: an integrative framework assisted by network propagation and network fusion for preprocessing of single-cell RNA-seq data

(2019) Wenbin Ye et al.   BMC GENOMICS

Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM

(2019) Huidong Chen et al.   Nature Communications

Single-cell RNA-Seq: a next generation sequencing tool for a high-resolution view of the individual cell

(2019) Kevin Stevenson et al.   JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS

DrImpute: imputing dropout events in single cell RNA sequencing data

(2018) Wuming Gong et al.   BMC BIOINFORMATICS

Recovering Gene Interactions from Single-Cell Data Using Data Diffusion

(2018) David van Dijk et al.   CELL

Opportunities and obstacles for deep learning in biology and medicine

(2018) Travers Ching et al.   Journal of the Royal Society Interface

Identifying cell populations with scRNASeq

(2018) Tallulah S. Andrews et al.   MOLECULAR ASPECTS OF MEDICINE

SAVER: gene expression recovery for single-cell RNA sequencing

(2018) Mo Huang et al.   NATURE METHODS

An accurate and robust imputation method scImpute for single-cell RNA-seq data

(2018) Wei Vivian Li et al.   Nature Communications

Uncovering pseudotemporal trajectories with covariates from single cell and bulk expression data

(2018) Kieran R Campbell et al.   Nature Communications

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data

(2018) Travers Ching et al.   PLoS Computational Biology

Dimensionality reduction for visualizing single-cell data using UMAP

(2018) Etienne Becht et al.   NATURE BIOTECHNOLOGY

Deep generative modeling for single-cell transcriptomics

(2018) Romain Lopez et al.   NATURE METHODS

AutoImpute: Autoencoder based imputation of single-cell RNA-seq data

(2018) Divyanshu Talwar et al.   Scientific Reports

Reversed graph embedding resolves complex single-cell trajectories

(2017) Xiaojie Qiu et al.   NATURE METHODS

Accounting for technical noise in differential expression analysis of single-cell RNA sequencing data

(2017) Cheng Jia et al.   NUCLEIC ACIDS RESEARCH

Advances in single-cell RNA sequencing and its applications in cancer research

(2017) Sibo Zhu et al.   Oncotarget

Revealing the vectors of cellular identity with single-cell genomics

(2016) Allon Wagner et al.   NATURE BIOTECHNOLOGY

Wishbone identifies bifurcating developmental trajectories from single-cell data

(2016) Manu Setty et al.   NATURE BIOTECHNOLOGY

Diffusion pseudotime robustly reconstructs lineage branching

(2016) Laleh Haghverdi et al.   NATURE METHODS

TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis

(2016) Zhicheng Ji et al.   NUCLEIC ACIDS RESEARCH

Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons

(2016) Naomi Habib et al.   SCIENCE

Condensing Raman spectrum for single-cell phenotype analysis

(2015) Shiwei Sun et al.   BMC BIOINFORMATICS

Single-Cell RNA-Seq with Waterfall Reveals Molecular Cascades underlying Adult Neurogenesis

(2015) Jaehoon Shin et al.   Cell Stem Cell

Computational and analytical challenges in single-cell transcriptomics

(2015) Oliver Stegle et al.   NATURE REVIEWS GENETICS

Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B Cell Development

(2014) Sean C. Bendall et al.   CELL

Bayesian approach to single-cell differential expression analysis

(2014) Peter V Kharchenko et al.   NATURE METHODS

Bifurcation analysis of single-cell gene expression data reveals epigenetic landscape

(2014) Eugenio Marco et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

An estimation of the number of cells in the human body

(2013) Eva Bianconi et al.   ANNALS OF HUMAN BIOLOGY

From single-cell to cell-pool transcriptomes: Stochasticity in gene expression and RNA splicing

(2013) G. K. Marinov et al.   GENOME RESEARCH

Quantitative single-cell RNA-seq with unique molecular identifiers

(2013) Saiful Islam et al.   NATURE METHODS

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

(2009) M. D. Robinson et al.   BIOINFORMATICS