Wonder if I can access the raw data though ...
Saturday, 13 September 2014
Wednesday, 27 August 2014
Source: Samtools-help mailing list
Friday, 2 May 2014
Geographic population structure analysis of worldwide human populations infers their biogeographical origins : Nature Communications : Nature Publishing Group
There's no stopping a cheesy geneticist when he puts his mind to making a research idea stick ... like coming up with acronyms like GPS to determine biogeographical origin ...
Tuesday, 29 April 2014
Seems like gut microbiome is getting more and more air time in news.
Monday, 21 April 2014
Welcome to the Google Genomics Preview! You've been approved for early access to the API.
The goal of the Genomics API is to encourage interoperability and build a foundation to store, process, search, analyze and share tens of petabytes of genomic data.
We've loaded sample data from public BAM files:
* The complete 1000 Genomes Project
* Selections from the Personal Genome Project
How to get started:
* Follow the instructions in the developer documentation
* Try the sample genome browser which calls the API
* Try out the other open source examples -- an R script, Python MapReduce, and a Java file-based implementation
* Write your own code to call the API and explore new uses
This is only the beginning. Your feedback will be essential to make the API useful. Please submit feature requests, bugs and suggestions on our GitHub page.
Thank you for being part of the first wave. If you'd rather join with a different email address (Gmail or Google Apps domain), please fill out the request form with that address too, and we'll grant access soon. Thank you for your interest!
Sincerely,The Google Genomics team
Friday, 18 April 2014
A standard way of describing chromosomal rearrangements would help clarify an already perplexing problem
Tuesday, 25 March 2014
From: Cole Trapnell <cole cs.umd.edu>
Date: Mon, Mar 24, 2014 at 11:51 PM
Subject: [Bowtie-bio-announce] Monocle 0.99.0
To: bowtie-bio-announce lists.sourceforge.net
I am proud to announce the first release of the Monocle analysis toolkit for single-cell RNA-Seq and qPCR. Monocle performs differential expression and time series analysis for single-cell expression experiments. You can read about Monocle and its “pseudo time” analysis of biological processes in the paper, which just appeared on Nature Biotech’s AOP list:
The Monocle source code and support site is also live:
I hope you will consider using Monocle for your single-cell expression analysis workflow! Please report any issues on the new Monocle google group:
Note that Monocle is currently considered an ALPHA release - new features and interfaces changes will be coming in future releases, along with significant new functionality. The release announcement for Monocle v 0.99.0 is below.
0.99.0 release - 3/23/2014
The first public release of Monocle is now available for download. Monocle is a toolkit for analyzing single cell expression experiments. It runs on the R statistical computing platform.
Monocle takes as input a matrix of gene or transcript expression values, along with information about each cell in the experiment, and some annotation about each gene/transcript, both provided as simple tables. It is designed for single-cell RNA-Seq experiments, but in principle Monocle can be used with other data types such as qPCR. For RNA-Seq, you can useCufflinks to estimate your expression values.
This software is a work in progress - it is a beta release, and new features will continue to be added over the next couple of weeks. To suggest a feature or report a bug, please post your comments on the Monocle user's group.