A machine learning framework for scRNA-seq UMI threshold optimization and accurate classification of cell types

A machine learning framework for scRNA-seq UMI threshold optimization and accurate classification of cell types

Recent advances in single cell RNA sequencing (scRNA-seq) technologies have been invaluable in the study of the diversity of cancer cells and the tumor microenvironment. While scRNA-seq platforms allow processing of a high number of cells, uneven read quality and technical artifacts hinder the abili...

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Bibliographic Details
Main Authors: Isaac Bishara, Jinfeng Chen, Jason I. Griffiths, Andrea H. Bild, Aritro Nath
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-11-01
Series:Frontiers in Genetics
Subjects:
ScRNA-seq
UMI (unique molecular identifier)
QC
quality control
threshold
optimization
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2022.982019/full

Internet

https://www.frontiersin.org/articles/10.3389/fgene.2022.982019/full

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