Cargando…
GC-Content Normalization for RNA-Seq Data
BACKGROUND: Transcriptome sequencing (RNA-Seq) has become the assay of choice for high-throughput studies of gene expression. However, as is the case with microarrays, major technology-related artifacts and biases affect the resulting expression measures. Normalization is therefore essential to ensu...
Autores principales: | Risso, Davide, Schwartz, Katja, Sherlock, Gavin, Dudoit, Sandrine |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3315510/ https://www.ncbi.nlm.nih.gov/pubmed/22177264 http://dx.doi.org/10.1186/1471-2105-12-480 |
Ejemplares similares
-
Normalization benchmark of ATAC-seq datasets shows the importance of accounting for GC-content effects
por: Van den Berge, Koen, et al.
Publicado: (2022) -
A general and flexible method for signal extraction from single-cell RNA-seq data
por: Risso, Davide, et al.
Publicado: (2018) -
Publisher Correction: A general and flexible method for signal extraction from single-cell RNA-seq data
por: Risso, Davide, et al.
Publicado: (2019) -
Bioconductor workflow for single-cell RNA sequencing: Normalization, dimensionality reduction, clustering, and lineage inference
por: Perraudeau, Fanny, et al.
Publicado: (2017) -
Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments
por: Bullard, James H, et al.
Publicado: (2010)