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Getting Genetics Done

Getting Things Done in Genetics & Bioinformatics Research
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BioinformaticsPathwaysRVisualizationBiological Sciences
Published

I get a lot of requests in the core about running a "pathway analysis." Someone ran a handful of gene expression arrays, or better yet, ran an RNA-seq experiment (with replicates!). These, and many other kinds of high-throughput assays (GWAS, ChIP-seq, etc.) result in a list of genes and some associated p-value, fold change, or other statistic. Here's some R code to download public data from a study on susceptibility to colorectal cancer.

BioinformaticsRBiological Sciences
Published

I direct the Bioinformatics Core at the University of Virginia, and I'm hiring. Visit this link on the UVA Jobs website for more information. Here's the description: I'm Hiring - Bioinformatics Analyst in the UVA Bioinformatics CoreGetting Genetics Done by Stephen Turner is licensed under a Creative Commons Attribution (CC BY) License.

PubMedBiological Sciences
Published

I'm updating my CV and biosketch for a few grant applications, and for some time now, NIH has required you to include the PubMed Central ID for each article you publish that arose from NIH support. I only have a dozen or so papers indexed in PubMed, but I still wanted a way to do this automatically. If you have scores of publications, looking up all the PMCIDs could easily become a hassle. First, create an account at My NCBI.

Biological Sciences
Published

The winter Joint Techs meeting is next week in Baton Rouge. I'm not going, but I plan on participating via a netcast to see what's going on. Jim Bottum, Clemson's CIO, is moderating an entire day devoted to the topic Enhancing Infrastructure Support for Data Intensive Science. Of particular interest to me are the talks from 9:30-11am Tuesday January 24 from researchers and those supporting climatology, genomics, and the XSEDE projects.

BioinformaticsRSoftwareBiological Sciences
Published

Lately I've been using the limma package often for analyzing microarray data. When I read in Affy CEL files using ReadAffy(), the resulting ExpressionSet won't contain any featureData annotation. Consequentially, when I run topTable to get a list of differentially expressed genes, there's no annotation information other than the Affymetrix probeset IDs or transcript cluster IDs.

RBiological Sciences
Published

I use this all the time, and the setup is dead simple. Follow the code below to load the RMySQL package, connect to a database (here the UCSC genome browser's public MySQL instance), set up a function to make querying easier, and query the database to return results as a data frame. Getting Genetics Done by Stephen Turner is licensed under a Creative Commons Attribution (CC BY) License.