Deep learning tackles single-cell analysis—a survey of deep learning for scRNA-seq analysis

Discriminating mild from critical COVID-19 by innate and adaptive immune single-cell profiling of bronchoalveolar lavages

(2021) Els Wauters et al.   CELL RESEARCH

Prediction and Interpretation of Cancer Survival Using Graph Convolution Neural Networks

(2021) Ricardo Ramirez et al.   METHODS

Probabilistic harmonization and annotation of single‐cell transcriptomics data with deep generative models

(2021) Chenling Xu et al.   Molecular Systems Biology

Application of single-cell sequencing technologies in pancreatic cancer

(2021) Mastan Mannarapu et al.   MOLECULAR AND CELLULAR BIOCHEMISTRY

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

(2021) Juexin Wang et al.   Nature Communications

DEEPsc: A Deep Learning-Based Map Connecting Single-Cell Transcriptomics and Spatial Imaging Data

(2021) Floyd Maseda et al.   Frontiers in Genetics

Surface protein imputation from single cell transcriptomes by deep neural networks

(2020) Zilu Zhou et al.   Nature Communications

Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks

(2020) Mohamed Marouf et al.   Nature Communications

Interpretable factor models of single-cell RNA-seq via variational autoencoders

(2020) Valentine Svensson et al.   BIOINFORMATICS

scVAE: Variational auto-encoders for single-cell gene expression data

(2020) Christopher Heje Grønbech et al.   BIOINFORMATICS

Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients

(2020) Pierre Bost et al.   CELL

Single-cell RNA-seq analysis software providers scramble to offer solutions

(2020) Michael Eisenstein   NATURE BIOTECHNOLOGY

Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis

(2020) Xiangjie Li et al.   Nature Communications

netAE: Semi-supervised dimensionality reduction of single-cell RNA sequencing to facilitate cell labeling

(2020) Zhengyang Dong et al.   BIOINFORMATICS

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

(2020) Yungang Xu et al.   NUCLEIC ACIDS RESEARCH

A Hybrid Deep Clustering Approach for Robust Cell Type Profiling Using Single-cell RNA-seq Data

(2020) Suhas Srinivasan et al.   RNA

Generative adversarial networks

(2020) Ian Goodfellow et al.   COMMUNICATIONS OF THE ACM

scGMAI: a Gaussian mixture model for clustering single-cell RNA-Seq data based on deep autoencoder

(2020) Bin Yu et al.   BRIEFINGS IN BIOINFORMATICS

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

(2019) Gökcen Eraslan et al.   Nature Communications

Fast interpolation-based t-SNE for improved visualization of single-cell RNA-seq data

(2019) George C. Linderman et al.   NATURE METHODS

Scalable analysis of cell-type composition from single-cell transcriptomics using deep recurrent learning

(2019) Yue Deng et al.   NATURE METHODS

A single-cell molecular map of mouse gastrulation and early organogenesis

(2019) Blanca Pijuan-Sala et al.   NATURE

The single-cell transcriptional landscape of mammalian organogenesis

(2019) Junyue Cao et al.   NATURE

Dhaka: variational autoencoder for unmasking tumor heterogeneity from single cell genomic data

(2019) Sabrina Rashid et al.   BIOINFORMATICS

Efficient integration of heterogeneous single-cell transcriptomes using Scanorama

(2019) Brian Hie et al.   NATURE BIOTECHNOLOGY

Deep learning: new computational modelling techniques for genomics

(2019) Gökcen Eraslan et al.   NATURE REVIEWS GENETICS

Single-Cell RNA-Seq Technologies and Related Computational Data Analysis

(2019) Geng Chen et al.   Frontiers in Genetics

Comprehensive Integration of Single-Cell Data

(2019) Tim Stuart et al.   CELL

Single-Cell RNA Sequencing in Cancer: Lessons Learned and Emerging Challenges

(2019) Mario L. Suvà et al.   MOLECULAR CELL

scGen predicts single-cell perturbation responses

(2019) Mohammad Lotfollahi et al.   NATURE METHODS

Single-Cell Transcriptomic Map of the Human and Mouse Bladders

(2019) Zhenyuan Yu et al.   JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY

Data denoising with transfer learning in single-cell transcriptomics

(2019) Jingshu Wang et al.   NATURE METHODS

Exploring single-cell data with deep multitasking neural networks

(2019) Matthew Amodio et al.   NATURE METHODS

Fast, sensitive and accurate integration of single-cell data with Harmony

(2019) Ilya Korsunsky et al.   NATURE METHODS

Digitaldlsorter: Deep-Learning on scRNA-Seq to Deconvolute Gene Expression Data

(2019) Carlos Torroja et al.   Frontiers in Genetics

Deep learning for inferring gene relationships from single-cell expression data

(2019) Ye Yuan et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

DEsingle for detecting three types of differential expression in single-cell RNA-seq data

(2018) Zhun Miao et al.   BIOINFORMATICS

Recovering Gene Interactions from Single-Cell Data Using Data Diffusion

(2018) David van Dijk et al.   CELL

Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment

(2018) Elham Azizi et al.   CELL

Mapping the Mouse Cell Atlas by Microwell-Seq

(2018) Xiaoping Han et al.   CELL

Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors

(2018) Laleh Haghverdi et al.   NATURE BIOTECHNOLOGY

Integrating single-cell transcriptomic data across different conditions, technologies, and species

(2018) Andrew Butler et al.   NATURE BIOTECHNOLOGY

SAVER: gene expression recovery for single-cell RNA sequencing

(2018) Mo Huang et al.   NATURE METHODS

Human embryonic stem cells extracellular vesicles and their effects on immortalized human retinal Müller cells

(2018) Yingqian Peng et al.   PLoS One

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

(2018) Wei Vivian Li et al.   Nature Communications

Interpretable dimensionality reduction of single cell transcriptome data with deep generative models

(2018) Jiarui Ding et al.   Nature Communications

Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor

(2018) Megan Crow et al.   Nature Communications

Population snapshots predict early haematopoietic and erythroid hierarchies

(2018) Betsabeh Khoramian Tusi et al.   NATURE

CaSTLe – Classification of single cells by transfer learning: Harnessing the power of publicly available single cell RNA sequencing experiments to annotate new experiments

(2018) Yuval Lieberman et al.   PLoS One

Gene expression variability across cells and species shapes innate immunity

(2018) Tzachi Hagai et al.   NATURE

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

A test metric for assessing single-cell RNA-seq batch correction

(2018) Maren Büttner et al.   NATURE METHODS

A web server for comparative analysis of single-cell RNA-seq data

(2018) Amir Alavi et al.   Nature Communications

VASC: Dimension Reduction and Visualization of Single-cell RNA-seq Data by Deep Variational Autoencoder

(2018) Dongfang Wang et al.   GENOMICS PROTEOMICS & BIOINFORMATICS

A single-cell survey of the small intestinal epithelium

(2017) Adam L. Haber et al.   NATURE

Multilineage communication regulates human liver bud development from pluripotency

(2017) J. Gray Camp et al.   NATURE

Multiplexed droplet single-cell RNA-sequencing using natural genetic variation

(2017) Hyun Min Kang et al.   NATURE BIOTECHNOLOGY

Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors

(2017) Huipeng Li et al.   NATURE GENETICS

Simultaneous epitope and transcriptome measurement in single cells

(2017) Marlon Stoeckius et al.   NATURE METHODS

Sequencing thousands of single-cell genomes with combinatorial indexing

(2017) Sarah A Vitak et al.   NATURE METHODS

Scalable whole-genome single-cell library preparation without preamplification

(2017) Hans Zahn et al.   NATURE METHODS

Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning

(2017) Bo Wang et al.   NATURE METHODS

Reversed graph embedding resolves complex single-cell trajectories

(2017) Xiaojie Qiu et al.   NATURE METHODS

Single-cell analysis of experience-dependent transcriptomic states in the mouse visual cortex

(2017) Sinisa Hrvatin et al.   NATURE NEUROSCIENCE

Using neural networks for reducing the dimensions of single-cell RNA-Seq data

(2017) Chieh Lin et al.   NUCLEIC ACIDS RESEARCH

The Reactome Pathway Knowledgebase

(2017) Antonio Fabregat et al.   NUCLEIC ACIDS RESEARCH

Comprehensive single-cell transcriptional profiling of a multicellular organism

(2017) Junyue Cao et al.   SCIENCE

Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer

(2017) Woosung Chung et al.   Nature Communications

Massively parallel digital transcriptional profiling of single cells

(2017) Grace X. Y. Zheng et al.   Nature Communications

The Human Cell Atlas

(2017) Aviv Regev et al.   eLife

Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data

(2017) Julien Racle et al.   eLife

A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation

(2016) S. Nestorowa et al.   BLOOD

Molecular Diversity of Midbrain Development in Mouse, Human, and Stem Cells

(2016) Gioele La Manno et al.   CELL

Heterogeneity in Oct4 and Sox2 Targets Biases Cell Fate in 4-Cell Mouse Embryos

(2016) Mubeen Goolam et al.   CELL

Comprehensive Classification of Retinal Bipolar Neurons by Single-Cell Transcriptomics

(2016) Karthik Shekhar et al.   CELL

RNA Sequencing of Single Human Islet Cells Reveals Type 2 Diabetes Genes

(2016) Yurong Xin et al.   Cell Metabolism

Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma

(2016) Itay Tirosh et al.   NATURE

Wishbone identifies bifurcating developmental trajectories from single-cell data

(2016) Manu Setty et al.   NATURE BIOTECHNOLOGY

GTRD: a database of transcription factor binding sites identified by ChIP-seq experiments

(2016) Ivan Yevshin et al.   NUCLEIC ACIDS RESEARCH

KEGG: new perspectives on genomes, pathways, diseases and drugs

(2016) Minoru Kanehisa et al.   NUCLEIC ACIDS RESEARCH

Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq

(2016) I. Tirosh et al.   SCIENCE

Single-Cell Transcriptomics Reveals that Differentiation and Spatial Signatures Shape Epidermal and Hair Follicle Heterogeneity

(2016) Simon Joost et al.   Cell Systems

A Single-Cell Transcriptome Atlas of the Human Pancreas

(2016) Mauro J. Muraro et al.   Cell Systems

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

Transcriptional Heterogeneity and Lineage Commitment in Myeloid Progenitors

(2015) Franziska Paul et al.   CELL

Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis

(2015) Jacob H. Levine et al.   CELL

Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets

(2015) Evan Z. Macosko et al.   CELL

The first five years of single-cell cancer genomics and beyond

(2015) Nicholas E. Navin   GENOME RESEARCH

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells

(2015) Florian Buettner et al.   NATURE BIOTECHNOLOGY

A survey of human brain transcriptome diversity at the single cell level

(2015) Spyros Darmanis et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq

(2015) A. Zeisel et al.   SCIENCE

Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression

(2015) Jong Kyoung Kim et al.   Nature Communications

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data

(2015) Catalina A. Vallejos et al.   PLoS Computational Biology

Cell fate inclination within 2-cell and 4-cell mouse embryos revealed by single-cell RNA sequencing

(2014) Fernando H. Biase et al.   GENOME RESEARCH

Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex

(2014) Alex A Pollen et al.   NATURE BIOTECHNOLOGY

Bayesian approach to single-cell differential expression analysis

(2014) Peter V Kharchenko et al.   NATURE METHODS

Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing

(2014) Dmitry Usoskin et al.   NATURE NEUROSCIENCE

Gene coexpression measures in large heterogeneous samples using count statistics

(2014) Y. X. Rachel Wang et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma

(2014) A. P. Patel et al.   SCIENCE

Single-Cell RNA-Seq Reveals Dynamic, Random Monoallelic Gene Expression in Mammalian Cells

(2014) Q. Deng et al.   SCIENCE

Conditional density-based analysis of T cell signaling in single-cell data

(2014) S. Krishnaswamy et al.   SCIENCE

Smart-seq2 for sensitive full-length transcriptome profiling in single cells

(2013) Simone Picelli et al.   NATURE METHODS

Single-cell RNA-Seq profiling of human preimplantation embryos and embryonic stem cells

(2013) Liying Yan et al.   NATURE STRUCTURAL & MOLECULAR BIOLOGY

Inferring tumour purity and stromal and immune cell admixture from expression data

(2013) Kosuke Yoshihara et al.   Nature Communications

Unfolding communities in large complex networks: Combining defensive and offensive label propagation for core extraction

(2011) Lovro Šubelj et al.   PHYSICAL REVIEW E

Inferring Regulatory Networks from Expression Data Using Tree-Based Methods

(2010) Vân Anh Huynh-Thu et al.   PLoS One