Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications
Abstract Dropout events in single-cell RNA sequencing (scRNA-seq) cause many transcripts to go undetected and induce an excess of zero read counts, leading to power issues in differential expression (DE) analysis. This has triggered the development of bespoke scRNA-seq DE methods to cope with zero i...
Main Authors: | Koen Van den Berge, Fanny Perraudeau, Charlotte Soneson, Michael I. Love, Davide Risso, Jean-Philippe Vert, Mark D. Robinson, Sandrine Dudoit, Lieven Clement |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2018-02-01
|
Series: | Genome Biology |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s13059-018-1406-4 |
Similar Items
-
Estimation Parameters And Modelling Zero Inflated Negative Binomial
by: Cindy Cahyaning Astuti, et al.
Published: (2016-11-01) -
Evaluation of negative binomial and zero-inflated negative binomial models for the analysis of zero-inflated count data: application to the telemedicine for children with medical complexity trial
by: Kyung Hyun Lee, et al.
Published: (2023-09-01) -
Modeling zero inflation is not necessary for spatial transcriptomics
by: Peiyao Zhao, et al.
Published: (2022-05-01) -
Statistical analysis of variability in TnSeq data across conditions using zero-inflated negative binomial regression
by: Siddharth Subramaniyam, et al.
Published: (2019-11-01) -
Using zero inflated models to analyze dental caries with many zeroes
by: Javali Shivalingappa, et al.
Published: (2010-01-01)