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Provides easy to use, objective oriented functions for preprocessing methylation data produced by an Illumina Infinium BeadChip and detecting differentially methylated positions and regions within the DNA.
This scripts involves five major steps including GEO dataset download, data normalization, data manipulation, fetching phenodata and feature data and differentially expressed genes (DEGs) analysis using R and bioconductor packages.
Normalization, outlier detection, statistical analysis, and visualization of microarray data from 79 tumor samples to identify differentially expressed genes between recurrent and non-recurrent prostate cancer.
A selection of analytical approaches, tools, and utilities for the processing of microbiome data derived from either 16S rRNA amplicon sequencing or shotgun metagenomics.