Biology subjects

Jovana Maksimovic

Publications and source records attributed to Jovana Maksimovic.

2 recordsLinked to original sources

bioRxiv2016

A cross-package Bioconductor workflow for analysing methylation array data

Methylation in the human genome is known to be associated with development and disease. The Illumina Infinium methylation arrays are by far the most common way to interrogate methylation across the human genome. This paper provides a Bioconductor workflow using multiple packages for the analysis of methylation array data. Specifically, we demonstrate the steps involved in a typical differential methylation analysis pipeline including: quality control, filtering, normalization, data exploration and statistical testing for probe-wise differential methylation. We further outline other analyses such as differential methylation of regions, differential variability analysis, estimating cell type composition and gene ontology testing. Finally, we provide some examples of how to visualise methylation array data.

Bioinformatics↗

bioRxiv2015

Removing unwanted variation in a differential methylation analysis of Illumina HumanMethylation450 array data

Due to their relatively low-cost per sample and broad, gene-centric coverage of CpGs across the human genome, Illuminas 450k arrays are widely used in large scale differential methylation studies. However, by their very nature, large studies are particularly susceptible to the effects of unwanted variation. The effects of unwanted variation have been extensively documented in gene expression array studies and numerous methods have been developed to mitigate these effects. However, there has been much less research focused on the appropriate methodology to use for accounting for unwanted variation in methylation array studies. Here we present a novel 2-stage approach using RUV-inverse in a differential methylation analysis of 450k data and show that it outperforms existing methods.

Bioinformatics↗