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...
المؤلفون الرئيسيون: | Christoph Hafemeister, Rahul Satija |
---|---|
التنسيق: | مقال |
اللغة: | English |
منشور في: |
BMC
2019-12-01
|
سلاسل: | Genome Biology |
الموضوعات: | |
الوصول للمادة أونلاين: | https://doi.org/10.1186/s13059-019-1874-1 |
مواد مشابهة
-
Normalization Methods on Single-Cell RNA-seq Data: An Empirical Survey
حسب: Nicholas Lytal, وآخرون
منشور في: (2020-02-01) -
Quantile normalization of single-cell RNA-seq read counts without unique molecular identifiers
حسب: F. William Townes, وآخرون
منشور في: (2020-07-01) -
Negative binomial additive model for RNA-Seq data analysis
حسب: Xu Ren, وآخرون
منشور في: (2020-05-01) -
Differentially expressed genes of RNA-seq data are suggested on the intersections of normalization techniques
حسب: Mohammad Elahimanesh, وآخرون
منشور في: (2024-03-01) -
Tissue-aware RNA-Seq processing and normalization for heterogeneous and sparse data
حسب: Joseph N. Paulson, وآخرون
منشور في: (2017-10-01)