Molecular subtypes of cancers and autoimmune disease, defined by transcriptomic profiling, have provided insight into disease pathogenesis, molecular heterogeneity, and therapeutic responses. However, technical biases inherent to different gene...
Read More »A comparison of normalization methods for differential expression analysis of RNA-seq data
Normalization is an essential step with considerable impact on high-throughput RNA sequencing (RNA-seq) data analysis. Although there are numerous methods for read count normalization, it remains a challenge to choose an optimal method due to multiple factors contributing to read ...
Read More »How choice of analysis pipeline affects your data
Numerous statistical pipelines are now available for the differential analysis of gene expression measured with RNA-sequencing technology. Most of them are based on similar statistical frameworks after normalization, differing primarily in the choice of data distribution, mean and variance estimation ...
Read More »Comparison of TMM (edgeR), RLE (DESeq2), and MRN Normalization Methods
In the past 5 years, RNA-Seq approaches, based on high-throughput sequencing technologies, are becoming an essential tool in transcriptomics studies. It is now commonly accepted that a normalization preprocessing step can significantly improve the quality of the analysis, in particular, ...
Read More »The Impact of Normalization Methods on RNA-Seq Data Analysis
High-throughput sequencing technologies, such as the Illumina Hi-seq, are powerful new tools for investigating a wide range of biological and medical problems. Massive and complex data sets produced by the sequencers create a need for development of statistical and computational ...
Read More »The Impact of Normalization Methods on RNA-Seq Data Analysis
High-throughput sequencing technologies, such as the Illumina Hi-seq, are powerful new tools for investigating a wide range of biological and medical problems. Massive and complex data sets produced by the sequencers create a need for development of statistical and computational ...
Read More »An integrative method to normalize RNA-Seq data
Transcriptome sequencing is a powerful tool for measuring gene expression, but as well as some other technologies, various artifacts and biases affect the quantification. In order to correct some of them, several normalization approaches have emerged, differing both in the ...
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