I'm going to include my blog as a form of community engagement in my fellowship application. The only objective way I can measure its impact is by the number of views. Luckily the WordPress API makes it easy to download all my web traffic and I have made this data available online. I wrote this post in case one of the assessors decided to check whether I was just making up numbers.
The diagram package makes it easy to create flowcharts in R. In this post I'll show an example of creating a simple flowchart. The most important part is to understand how the coordinate systems works; once you understand that, it's just a matter of placing your arrows and boxes accordingly to create your flowchart. To get started, install the package if you haven't already.
A couple of weeks ago, I wrote a post on identifying OMIM phenotypes that are associated with a gene of interest. I thought I solved the problem by using one of my favourite R packages (biomaRt) but alas. For example, I could not find any OMIM IDs associated with the TTN gene using biomaRt. In the end, I resorted to using the OMIM API through a small R package I wrote called romim.
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 May 10th: 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. Please refer to an updated post.
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.