For analysis of differential gene expression, R package "DESeq" was used.
Next, the Illumina gene expression analysis package "lumi" [ 25] was used to assess the probability of probe expression above background.
Our obtained counts were subsequently passed through DEGSeq to calculate the differential gene expression (R package version 1.16.0) [ 86].
The DESeq differential gene expression R package (Anders and Huber, 2010) was used to identify isoforms whose observed and expected abundances were 'differential'differential
Among the genes assayed by qPCR, those that were labeled as "signature" (genes with a composite p≤0.01) by the Luminator gene expression analysis software package had a correlation of 0.847 (Spearman's Rho, p<0.0001, n=107, data not shown), whereas genes that were not called "signature" only exhibited a correlation of 0.435 (Spearman's Rho, p<0.0001, n=170, data not shown).
In this manuscript we present a novel strategy to deliver siRNA to podocytes to modulate specific gene expression by packaging siRNA on an antibody that binds podocyte membranes and is internalized by endocytosis.
Since the Affymetrix annotation is the most widely used probeset definition in numerous gene expression analysis packages including BioConductor, we compared our probesets annotation with the latest Affymetrix GeneChip annotations.
After alignment, we quantified gene expression with the software package eXpress 1.3.0 (Roberts and Pachter 2013), which reported the abundances of unigenes in the form of the fragments per kilobase of transcript per million mapped reads (FPKM).
To investigate it, we first used RSEM program to estimate gene expression and EdgeR package in bioconductor to identify genes that were differentially expressed between tumors and normal samples.
To identify differential gene expression the Limma package was used to fit linear models to the data, incorporating an empirical Bayes modification of the standard errors [ 79].
