Maximizing statistical power to detect differentially abundant cell states with scPOST-Reference-Cited by-同舟云学术

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Maximizing statistical power to detect differentially abundant cell states with scPOST

Published:2021-12 Issue:8 Volume:1 Page:100120
ISSN:2667-2375
Container-title:Cell Reports Methods
language:en
Short-container-title:Cell Reports Methods

Author:

Millard Nghia^ORCID,Korsunsky Ilya,Weinand Kathryn^ORCID,Fonseka Chamith Y.,Nathan Aparna,Kang Joyce B.,Raychaudhuri Soumya^ORCID

Funder

National Institutes of Health

National Institute of Allergy and Infectious Diseases

Publisher

Elsevier BV

Subject

General Medicine

Reference41 articles.

1. Fast unfolding of communities in large networks;Blondel;J. Stat. Mech.,2008

2. Spatially resolved, highly multiplexed RNA profiling in single cells;Chen;Science,2015

3. Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing;Cusanovich;Science,2015

4. Milo: differential abundance testing on single-cell data using k-NN graphs;Dann;bioRxiv,2020

5. Visualizing high-dimensional data using t-SNE;Van Der Maaten;J. Mach Learn Res.,2008

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Methods and Insights from Single-Cell Expression Quantitative Trait Loci;Annual Review of Genomics and Human Genetics;2023-08-25

2. Benchmarking of analytical combinations for COVID-19 outcome prediction using single-cell RNA sequencing data;Briefings in Bioinformatics;2023-04-24

3. Statistical Power Analysis for Designing Bulk, Single-Cell, and Spatial Transcriptomics Experiments: Review, Tutorial, and Perspectives;Biomolecules;2023-01-24

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