An adjacency list is simply an unordered list that describes connections between vertices. It's a commonly used input format for graphs. In this post, I use the melt() function from the reshape2 package to create an adjacency list from a correlation matrix. I use the geneData dataset, which consists of real but anonymised microarray expression data, from the Biobase package as an example. Finally, I'll show some features of the igraph package.
Just recently, the genome Aggregation Database (gnomAD) VCF files were available for download:
— Daniel MacArthur (@dgmacarthur) February 27, 2017
Update 2017 March 15th: I realised that this approach doesn't work for all genes, unfortunately. For example, the gene TTN (which is an HGNC approved gene symbol) is associated with 600334, 603689, 604145, 608807, 611705, and 613765 but biomaRt returns an NA.
I was interested in the number of Online Mendelian Inheritance in Man (OMIM) disorders a particular gene was associated with, which in this case was FGFR2. Once again it was biomaRt to the rescue. OMIM is a collection of genes and disorders, and the morbid map refers to the disorders. This post is on looking up the OMIM morbid IDs for FGFR2.
A colleague asked me this question: "I'm trying to find a way to find genes that overlap between three datasets. I have used intersect for two dataframes but can't seem to find a solution for three dataframes on google. Do you know any snazzy way of doing that?" I thought using the venn() function from the gplots package is a pretty snazzy solution, so that's what I recommended.
In the age of 50,000+ and 60,000+ whole exome catalogues, it's hard to find processed data for a single exome. At least I had trouble trying to find a single VCF file for a single exome from one individual. After searching for a while, I gave up and decided to generate one myself. This post is on how I generated a single VCF file, which I have hosted on my web server.
I created a basic Shiny app that uses the myvariant package to fetch variant information from MyVariant.info. The variants need to be represented in the format recommended by the Human Genome Variation Society. Once you have your variant of interest in the correct format, just hit "Get variant info!" and the annotations will appear on the right. You can find the app hosted at: https://davetang.shinyapps.io/get_variant_info/.