Best practices for single-cell analysis across modalities
Recent advances in single-cell technologies have enabled high-throughput molecular
profiling of cells across modalities and locations. Single-cell transcriptomics data can now …
profiling of cells across modalities and locations. Single-cell transcriptomics data can now …
The triumphs and limitations of computational methods for scRNA-seq
PV Kharchenko - Nature methods, 2021 - nature.com
The rapid progress of protocols for sequencing single-cell transcriptomes over the past
decade has been accompanied by equally impressive advances in the computational …
decade has been accompanied by equally impressive advances in the computational …
Mapping single-cell data to reference atlases by transfer learning
Large single-cell atlases are now routinely generated to serve as references for analysis of
smaller-scale studies. Yet learning from reference data is complicated by batch effects …
smaller-scale studies. Yet learning from reference data is complicated by batch effects …
Benchmarking atlas-level data integration in single-cell genomics
Single-cell atlases often include samples that span locations, laboratories and conditions,
leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets …
leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets …
Construction of a human cell landscape at single-cell level
Single-cell analysis is a valuable tool for dissecting cellular heterogeneity in complex
systems. However, a comprehensive single-cell atlas has not been achieved for humans …
systems. However, a comprehensive single-cell atlas has not been achieved for humans …
A human liver cell atlas reveals heterogeneity and epithelial progenitors
The human liver is an essential multifunctional organ. The incidence of liver diseases is
rising and there are limited treatment options. However, the cellular composition of the liver …
rising and there are limited treatment options. However, the cellular composition of the liver …
Fast, sensitive and accurate integration of single-cell data with Harmony
The emerging diversity of single-cell RNA-seq datasets allows for the full transcriptional
characterization of cell types across a wide variety of biological and clinical conditions …
characterization of cell types across a wide variety of biological and clinical conditions …
Efficient integration of heterogeneous single-cell transcriptomes using Scanorama
Integration of single-cell RNA sequencing (scRNA-seq) data from multiple experiments,
laboratories and technologies can uncover biological insights, but current methods for …
laboratories and technologies can uncover biological insights, but current methods for …
Challenges in unsupervised clustering of single-cell RNA-seq data
Single-cell RNA sequencing (scRNA-seq) allows researchers to collect large catalogues
detailing the transcriptomes of individual cells. Unsupervised clustering is of central …
detailing the transcriptomes of individual cells. Unsupervised clustering is of central …
Single-cell transcriptional diversity is a hallmark of developmental potential
GS Gulati, SS Sikandar, DJ Wesche, A Manjunath… - Science, 2020 - science.org
Single-cell RNA sequencing (scRNA-seq) is a powerful approach for reconstructing cellular
differentiation trajectories. However, inferring both the state and direction of differentiation is …
differentiation trajectories. However, inferring both the state and direction of differentiation is …