Data Normalization

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 ...

from RPubs – by Prasanth A S In order to explain the different methods of normalization and their problems with large array of data, which are assumed to have: most genes are not differentially expressed across conditions. the distribution of ...

The sequencing of the full transcriptome (RNA-seq) has become the preferred choice for the measurement of genome-wide gene expression. Despite its widespread use, challenges remain in RNA-seq data analysis. One often-overlooked aspect is normalization. Despite the fact that a variety ...

from StatQuest It used to be when you did RNA-seq, you reported your results in RPKM (Reads Per Kilobase Million) or FPKM (Fragments Per Kilobase Million). However, TPM (Transcripts Per Kilobase Million) is now becoming quite popular. Since there seems ...

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 ...

Single-cell RNA-seq is a promising technology with broad applications and discerning biological noise from technical noise is critical for correctly interpreting the data (Jaitin, et al., 2014). Recently, statistical methods are developed to model the technical noise from spike-in ERCC ...

Next generation sequencing technologies are powerful new tools for investigating a wide range of biological and medical questions. Statistical and computational methods are key to analyzing massive and complex sequencing data. In order to derive gene expression measures and compare ...