I have a noteworthy blogs tag on this blog that I sort of forgot about, and haven't used in years. But I started reading one recently that's definitely qualified for the distinction. The Microbiome Digest is written by Elisabeth Bik, a scientist studying the microbiome at Stanford.

A few folks have asked me how I get my news and stay on top of what's going on in my field, so I thought I'd share my strategy.

This is a few months old but I just got around to reading this series of blog posts on next-generation sequencing (NGS) by Gabe Rudy, Golden Helix's VP of product development. This series gives a seriously useful overview of NGS technology, then delves into the analysis of NGS data at each step, right down to a description of the most commonly used file formats and tools for the job. Check it out now if you haven't already.

Jeff Barret (@jcbarret on Twitter) over at Genomes Unzipped (@GenomesUnzipped) has posted a nice guide for the uninitiated on how to read a GWAS paper. Barret outlines five critical areas that readers should pay attention to: sample size, quality control, confounding (including population substructure), the replication requirement, and biological significance.

NYU PhD student Drew Conway has compiled a very nice list of 10 reasons why grad students should blog. I've been writing GGD for a little over a year now and it's been a great way to extend my own network past the Vanderbilt walls, participate in lively discussions with other scientists oceans away, and to write stuff that people actually read and find useful.

A District Court handed down a summary judgment invalidating most of Myriad's claims to both the BRCA1 DNA sequence and the method of testing for early-onset familial breast and ovarian cancer. See Genetic Future and Genomics Law Report for analysis.Getting Genetics Done by Stephen Turner is licensed under a Creative Commons Attribution (CC BY) License.

Head over to Revolutions Blog for a list of PDF and powerpoint resources for making the transition to R from other programming or stats languages.  All of these notes come from the New York R meetup. I enjoyed browsing the meetup's files - lots of powerpoints, PDFs, and example R data files for various topics, including several slideshows on ggplot2.

Learning R blog details some of the new features in the latest update to ggplot2. The latest version includes functions to make it easier to change axis and legend labels, as well as a function to easily set the limits of the plot display outside the range of the data. Be sure to check back next week - I'm putting together a short introductory ggplot2 tutorial.

Dan Vorhaus and Lawrence Moore recently put together this excellent three part series on Genomics Law Report.  Headlines about deCODE Genetics on the brink of insolvency and major shifts in the upper management of 23andMe inspired this series of posts on what would happen when a direct-to-consumer (DTC) genomics company goes declares bankruptcy.

Revolutions blog recently posted a link to R code by Joshua Reich with self-contained examples of using machine learning techniques in R, including various clustering methods (k-means, nearest neighbor, and kernel), recursive partitioning (CART), principle components analysis, linear discriminant analysis, and support vector machines.  This post also links to some slides that go over the basics of machine learning.