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K-nearest-neighbors induced topological PCA for single cell RNA-sequence data analysis

  • Published:2024-06 Issue: Volume:175 Page:108497
  • ISSN:0010-4825
  • Container-title:Computers in Biology and Medicine
  • language:en
  • Short-container-title:Computers in Biology and Medicine

Author:

Cottrell Sean,Hozumi YutaORCID,Wei Guo-WeiORCID

Funder

Bristol-Myers Squibb

National Science Foundation

NIH

National Aeronautics and Space Administration

NSF

Michigan State University Research Foundation

National Institutes of Health

Publisher

Elsevier BV

Reference48 articles.

1. A step-by-step workflow for low-level analysis of single-cell RNA-seq data with bioconductor;Lun,2016

2. The triumphs and limitations of computational methods for scrna-seq;Kharchenko;Nature Methods,2021

3. Current best practices in single-cell RNA-seq analysis: a tutorial;Luecken;Molecular Syst. Biol.,2019

4. Single-cell rna-seq technologies and related computational data analysis;Chen;Front. Genet.,2019

5. Machine learning and statistical methods for clustering single-cell rna-sequencing data;Petegrosso;Brief. Bioinform.,2020

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