Biology subjects

Jean-Philippe Fortin

Publications and source records attributed to Jean-Philippe Fortin.

4 recordsLinked to original sources

bioRxiv2016

Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array

The minfi package is widely used for analyzing Illumina DNA methylation array data. Here we describe modifications to the minfi package required to support the HumanMethylationEPIC (\"EPIC\") array from Illumina. We discuss methods for the joint analysis and normalization of data from the HumanMethylation450 (\"450k\") and EPIC platforms. We also introduce the single-sample Noob (ssNoob) method, a normalization procedure suitable for incremental preprocessing of individual Human-Methylation arrays. Our results recommend the ssNoob method when integrating data from multiple generations of Infinium methylation arrays. Finally, we show how to use reference 450k datasets to estimate cell type composition of samples on EPIC arrays. The cumulative effect of these updates is to ensure that minfi provides the tools to best integrate existing and forthcoming Illumina methylation array data.

Bioinformatics↗

bioRxiv2016

Human splicing diversity across the Sequence Read Archive

We aligned 21,504 publicly available Illumina-sequenced human RNA-seq samples from the Sequence Read Archive (SRA) to the human genome and compared detected exon-exon junctions with junctions in several recent gene annotations. 56,865 junctions (18.6%) found in at least 1,000 samples were not annotated, and their expression associated with tissue type. Newer samples contributed few novel well-supported junctions, with 96.1% of junctions detected in at least 20 reads across samples present in samples before 2013. Junction data is compiled into a resource called intropolis available at http://intropolis.rail.bio. We discuss an application of this resource to cancer involving a recently validated isoform of the ALK gene.

Genomics↗

bioRxiv2015

Reconstructing A/B compartments as revealed by Hi-C using long-range correlations in epigenetic data

Analysis of Hi-C data has shown that the genome can be divided into two compartments called A/B compartments. These compartments are cell-type specific and are associated with open and closed chromatin. We show that A/B compartments can be reliably estimated using epigenetic data from several different platforms, the Illumina 450k DNA methylation microarray, DNase hypersensitivity sequencing, single-cell ATAC sequencing and single-cell whole-genome bisulfite sequencing. We do this by exploiting the fact that the structure of long range correlations differs between open and closed compartments. This work makes A/B compartments readily available in a wide variety of cell types, including many human cancers.

Genomics↗

bioRxiv2014

Functional normalization of 450k methylation array data improves replication in large cancer studies

We propose an extension to quantile normalization which removes unwanted technical variation using control probes. We adapt our algorithm, functional normalization, to the Illumina 450k methylation array and address the open problem of normalizing methylation data with global epigenetic changes, such as human cancers. Using datasets from The Cancer Genome Atlas and a large case-control study, we show that our algorithm outperforms all existing normalization methods with respect to replication of results between experiments, and yields robust results even in the presence of batch effects. Functional normalization can be applied to any microarray platform, provided suitable control probes are available.

Bioinformatics↗