Signature-scoring methods developed for bulk samples are not adequate for cancer single-cell RNA sequencing data | eLife

Dropouts in single cell RNA sequencing data are associated with cell states and can affect gene signature scoring if methods do not account for them.

Signature-scoring methods developed for bulk samples are not adequate for cancer single-cell RNA sequencing data | eLife Version of Record March 11, 2022 Accepted Manuscript February 25, 2022 Download Cite Share Comment Open annotations (there are currently 0 annotations on this page). 13,851 views 845 downloads 62 citations Altmetric provides a collated score for online attention across various platforms and media. See more details Share this article Doi Copy to clipboard Cite this article Nighat Noureen Zhenqing Ye Yidong Chen Xiaojing Wang Siyuan Zheng (2022) Signature-scoring methods devel

saved by

• Hannah Le

related reading

• A survey of best practices for RNA-seq data analysisgenomebiology.biomedcentral.com
• Identifying and mitigating batch effects in whole genome sequencing databmcbioinformatics.biomedcentral.com
• GitHub - nf-core/rnaseq: RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.github.com
• Quantifying the effect of experimental perturbations at single-cell resolutionnature.com
• So where are we with deep learning for biochem?ladanuzhna.xyz
• scGen predicts single-cell perturbation responsesnature.com
• 10. Feature selection — Single-cell best practicessc-best-practices.org
• Current best practices in single‐cell RNA‐seq analysis: a tutorial | Molecular Systems Biology | Springer Nature Linkembopress.org
• Chapter 3 Feature selection | Basics of Single-Cell Analysis with Bioconductorbioconductor.org
• PREDICTING SINGLE-CELL PERTURBATION RESPONSES FOR UNSEEN DRUGSarxiv.org
• Gap Mapgap-map.org
• Somatic mutation landscapes at single-molecule resolutionnature.com