Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression
Abstract Single-cell RNA-seq (scRNA-seq) data exhibits significant cell-to-cell variation due to technical factors, including the number of molecules detected in each cell, which can confound biological heterogeneity with technical effects. To address this, we present a modeling framework for the no...
Үндсэн зохиолчид: | Christoph Hafemeister, Rahul Satija |
---|---|
Формат: | Өгүүллэг |
Хэл сонгох: | English |
Хэвлэсэн: |
BMC
2019-12-01
|
Цуврал: | Genome Biology |
Нөхцлүүд: | |
Онлайн хандалт: | https://doi.org/10.1186/s13059-019-1874-1 |
Ижил төстэй зүйлс
-
Normalization Methods on Single-Cell RNA-seq Data: An Empirical Survey
-н: Nicholas Lytal, зэрэг
Хэвлэсэн: (2020-02-01) -
Quantile normalization of single-cell RNA-seq read counts without unique molecular identifiers
-н: F. William Townes, зэрэг
Хэвлэсэн: (2020-07-01) -
Negative binomial additive model for RNA-Seq data analysis
-н: Xu Ren, зэрэг
Хэвлэсэн: (2020-05-01) -
Differentially expressed genes of RNA-seq data are suggested on the intersections of normalization techniques
-н: Mohammad Elahimanesh, зэрэг
Хэвлэсэн: (2024-03-01) -
Tissue-aware RNA-Seq processing and normalization for heterogeneous and sparse data
-н: Joseph N. Paulson, зэрэг
Хэвлэсэн: (2017-10-01)