Benchmarking atlas-level data integration in single-cell genomics

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

(2021) Chenling Xu et al.   Molecular Systems Biology

ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis

(2021) Jeffrey M. Granja et al.   NATURE GENETICS

Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics

(2021) Christoph Muus et al.   NATURE MEDICINE

Flexible comparison of batch correction methods for single-cell RNA-seq using BatchBench

(2021) Ruben Chazarra-Gil et al.   NUCLEIC ACIDS RESEARCH

SciPy 1.0: fundamental algorithms for scientific computing in Python

(2020) Pauli Virtanen et al.   NATURE METHODS

Benchmarking single-cell RNA-sequencing protocols for cell atlas projects

(2020) Elisabetta Mereu et al.   NATURE BIOTECHNOLOGY

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

(2020) Michael Eisenstein   NATURE BIOTECHNOLOGY

A single-cell transcriptomic atlas characterizes ageing tissues in the mouse

(2020)   NATURE

Cells of the adult human heart

(2020) Monika Litviňuková et al.   NATURE

Conditional out-of-distribution generation for unpaired data using transfer VAE

(2020) Mohammad Lotfollahi et al.   BIOINFORMATICS

A multicenter study benchmarking single-cell RNA sequencing technologies using reference samples

(2020) Wanqiu Chen et al.   NATURE BIOTECHNOLOGY

A comparison of single-cell trajectory inference methods

(2019) Wouter Saelens et al.   NATURE BIOTECHNOLOGY

Efficient integration of heterogeneous single-cell transcriptomes using Scanorama

(2019) Brian Hie et al.   NATURE BIOTECHNOLOGY

Deep learning for cellular image analysis

(2019) Erick Moen et al.   NATURE METHODS

Deep learning: new computational modelling techniques for genomics

(2019) Gökcen Eraslan et al.   NATURE REVIEWS GENETICS

Comprehensive Integration of Single-Cell Data

(2019) Tim Stuart et al.   CELL

Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity

(2019) Joshua D. Welch et al.   CELL

Current best practices in single‐cell RNA‐seq analysis: a tutorial

(2019) Malte D Luecken et al.   Molecular Systems Biology

Joint analysis of heterogeneous single-cell RNA-seq dataset collections

(2019) Nikolas Barkas et al.   NATURE METHODS

scGen predicts single-cell perturbation responses

(2019) Mohammad Lotfollahi et al.   NATURE METHODS

BBKNN: fast batch alignment of single cell transcriptomes

(2019) Krzysztof Polański et al.   BIOINFORMATICS

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

Highly multiplexed single-cell RNA-seq by DNA oligonucleotide tagging of cellular proteins

(2019) Jase Gehring et al.   NATURE BIOTECHNOLOGY

Snakemake—a scalable bioinformatics workflow engine

(2018) Johannes Köster et al.   BIOINFORMATICS

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

(2018) Laleh Haghverdi et al.   NATURE BIOTECHNOLOGY

Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database

(2018) Luke Zappia et al.   PLoS Computational Biology

Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data

(2018) Hannah A. Pliner et al.   MOLECULAR CELL

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

Why rankings of biomedical image analysis competitions should be interpreted with care

(2018) Lena Maier-Hein et al.   Nature Communications

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

(2016) I. Tirosh et al.   SCIENCE