Structure-Aware Principal Component Analysis for Single-Cell RNA-seq Data-Reference-Cited by-同舟云学术

Structure-Aware Principal Component Analysis for Single-Cell RNA-seq Data

Published:2018-12 Issue:12 Volume:25 Page:1365-1373
ISSN:1557-8666
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Lall Snehalika¹,Sinha Debajyoti²³,Bandyopadhyay Sanghamitra¹,Sengupta Debarka⁴

Affiliation:

1. Machine Intelligence Unit, Indian Statistical Institute, Kolkata, West Bengal, India.

2. Sy MeC Data Center, Indian Statistical Institute, Kolkata, West Bengal, India.

3. Department of Computer Science and Engineering, University of Calcutta, Kolkata, West Bengal, India.

4. Center for Computational Biology and Department of Computer Science and Engineering, Indraprastha Institute of Information Technology, Delhi, India.

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modelling and Simulation

Link

https://www.liebertpub.com/doi/pdf/10.1089/cmb.2018.0027

Reference19 articles.

1. LSH forest

2. SMOTE: Synthetic Minority Over-sampling Technique

3. Reproducible RNA-seq analysis using recount2

4. A survey of human brain transcriptome diversity at the single cell level

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