Genome Spot

If you are doing analysis of microarray data such as Infinium methylation arrays, then those genomic annotations you're using might be several years old.  The EPIC methylation chip was released in 2016 and the R bioconductor annotation set hasn't been updated much since. So we expect that some gene names have changed, which will reduce the performance of the downstream pathway analysis. The gene symbols you're using can be updated using the HGNChelper R package on CRAN. Let's say we want to make a table that maps probe IDs to gene names, the following code can be used. library("IlluminaHumanMethylationEPICanno.ilm10b4.hg19") anno <- getAnnotation(IlluminaHumanMethylationEPICanno.ilm10b4.hg19) myann <- data.frame(anno[,c("UCSC_RefGene_Name","UCSC_RefGene_Group","Islands_Name","Relation_to_Island")]) gp <- myann[,"UCSC_RefGene_Name",drop=FALSE] gp2 <- strsplit(gp$UCSC_RefGene_Name,";") names

It has been an amazing year of research. I've been at Burnet Institute since August 2023 as Head of Bioinformatics and I've really enjoyed the challenge of serving the many and varied 'omics projects at the Institute and loved discussing new project ideas with everyone here. I'm still active at Deakin in student supervision and project collaborations and this is ongoing. In terms of research directions, my group has been focused on our three themes:  1. Bioinformatics collaborative analysis 2. Building better software tools for omics analysis 3. Reproducibility and research rigour Some of the long-running projects have been completed including methylation analysis of type-1 diabetes complications, which has been about 10 years in the making [1]. The number of collaborative projects has dipped, which is normal when changing institutes and I hope this will lift in the coming years as Burnet work gets completed. In terms of research directions for 2024, there are many. One