BMC Bioinformatics | Full text | GC-Content Normalization for RNA-Seq Data 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. Normalizati
RNA-Seq Data Comparison with Gene Expression Microarrays White Paper: Sequencing False-positive rates were also estimated and compared across platforms. For the microarray platform, the false-positive rate was determined by comparing two versus three replicate arrays of the same sample. The RNA-Seq false-positi
Cufflinks RNA-Seq analysis tools - Background What is Cufflinks? Cufflinks is a program that assembles aligned RNA-Seq reads into transcripts, estimates their abundances, and tests for differential expression and regulation transcriptome-wide. Cufflinks runs on Linux and OS X. Cufflinks is described
Visaul RNA-Seq: As Easy As 1-2-3 Visual RNA-Seq by Integrative Biosciences, Inc. ... RNA-Seq Results Should Be As Easy As 1-2-3. At Visual RNA-Seq, we believe there should not be any barrier or jargon standing between you and your RNA-Seq results.
Cufflinks RNA-Seq analysis tools - Frequently Asked Questions What's the difference between FPKM and RPKM? They're almost the same thing. RPKM stands for Reads Per Kilobase of transcript per Million mapped reads. FPKM stands for Fragments Per Kilobase of transcript per Million mapped reads. In RNA-Seq, the ...
RNA-Seq profiling reveals novel hepatic gene expression pattern in aflatoxin B1 treated rats. 1. PLoS One. 2013 Apr 22;8(4):e61768. doi: 10.1371/journal.pone.0061768. Print 2013. RNA-Seq profiling reveals novel hepatic gene expression pattern in aflatoxin B1 treated rats. Merrick BA, Phadke DP, Auerbach SS, Mav D, Stiegelmeyer SM, Shah RR, Tice RR
Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflink Limitations of the protocol and software TopHat and Cufflinks do not address all applications of RNA-seq, nor are they the only tools for RNA-seq analysis. In particular, TopHat and Cufflinks require a sequenced genome (see below for references to tools t
JCI - 5′RNA-Seq identifies Fhl1 as a genetic modifier in cardiomyopathy To identify differences in start-site usage, we developed a computational approach that detected differences in read depth distribution at the start-site regions of genes and quantified the extent of change in start-site usage (Figure 1B and Supplemental
A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Seque (a) Titration order A, C, D, B. Log 2 fold-change is related to cross-platform titration consistency. At sufficiently strong log 2 fold-change, reliable titration is also found across platforms. The dark blue line represents the 22,074 'unmissable' genes
Estimating number of transcripts from RNA-Seq measurements (and why I believe in paywall) | Bits of RNA-Seq can be used to estimate transcript abundances in an RNA sample. Formally, a sample consists of n distinct types of transcripts, and each occurs with different multiplicity (copy number), so that transcript i appears times in the sample. By “abunda