Description

OncodriveCLUST is a method aimed to identify genes whose mutations are biased towards a large spatial clustering. This method is designed to exploit the feature that mutations in cancer genes, especially oncogenes, often cluster in particular positions of the protein. We consider this as a sign that mutations in these regions change the function of these proteins in a manner that provides an adaptive advantage to cancer cells and consequently are positively selected during clonal evolution of tumours, and this property can thus be used to nominate novel candidate driver genes.

The method does not assume that the baseline mutation probability is homogeneous across all gene positions but it creates a background model using silent mutations. Coding silent mutations are supposed to be under no positive selection and may reflect the baseline clustering of somatic mutations. Given recent evidences of non-random mutation processes along the genome, the assumption of homogenous mutation probabilities is likely an oversimplication introducing bias in the detection of meaningful events.

How it works

Detailed description is contained in the main manuscript. Briefly, the following steps are performed: first, protein affecting mutations of each gene across a cohort of tumors are evaluated looking for those protein residues having a number of mutations barely expected by chance. Second, these positions are thereafter grouped to form mutation clusters. Third, each cluster is scored with a figure proportional to the percentage of the gene mutations that are enclosed within that cluster and inversely related to its length. The gene clustering score is obtained as the sum of the scores of all clusters (if any) found in that gene. Finally, each gene clustering score is compared with the background model to obtain a significance value. Background model is obtained performing the same steps than above but assessing only coding silent mutations.

How it performs

We have analysed those entries of the COSMIC database annotated as whole gene screen as well as data provided from 4 projects of the Cancer Genome Atlas. We demonstrated that the resulting candidate list of drivers is strongly enriched by known cancer driver genes and particularly oncogenes, supporting the idea that this approach can nominate novel driver candidates. In addition, comparison with methods based on other criteria (namely, functional impact and mutation recurrence across the tumor cohort) demonstrated that the clustering approach identifies known cancer drivers not detected by any of the other two methods, stressing the fact that the combination of methods is beneficial to identify cancer drivers. We conclude that OncodriveCLUST is a method that may be useful to identify cancer drivers through the assessment of the mutation clustering property that may be complementary to other methods aimed to identify genes involved in the disease.

How to install and run it

You will find detailed information on how to install OncodriveCLUST and run some examples at Bitbucket

OncodriveCLUST 0.4 is the version for the submitted paper and can be downloaded from here, and the suplementary datasets that have been analysed from here.

How to cite

If you use OncodriveCLUST, please cite it as Tamborero D, Gonzalez-Perez A and Lopez-Bigas N. OncodriveCLUST: exploiting the positional clustering of somatic mutations to identify cancer genes. Bioinformatics. 2013; doi: 10.1093/bioinformatics/btt395s

For any comments or feedback, please contact

David Tamborero, PhD

Bioinformatician, Postdoctoral Researcher

Research Unit on Biomedical Informatics - GRIB

Parc de Recerca Biomèdica de Barcelona (PRBB)

david.tamborero@upf.edu

Data analysis life cycle

Onexus is a modular framework to manage the complete life cycle of data analyses. Data analyses follow these steps: analysis definition, analysis execution, results storing, results browsing and finally results publishing.

(show details)

Use case

Onexus is a general framework, so its functionality depends on the implemented modules. On the first release we want to focus on making Onexus useful for this use case:

Easily build a website with big datasets

The website will allow your visitors to browse, filter and download data of their interest. Check this sitebeta.intogen.org to see what we are doing with an alpha version of Onexus. You will also get a webservice so your visitors will be able to automatically do downloads from their scripts.

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SLEA is a method to analyse the transcriptional status of gene modules (gene sets) per sample in a transcriptomic dataset. The results are presented in the form of interactive heatmaps which facilitates their interpretation. It can be used to identify tumor subtypes, correlate molecular features with clinical features and study relationship between modules.

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Open source code: https://github.com/chris-zen/wok

Source:https://bitbucket.org/bbglab/wok

Introduction

Wok is a workflow management system implemented in Python that makes very easy to structure the workflows, parallelize their execution and monitor its progress among other things. It is designed in a modular way allowing to adapt it to different infraestructures.

For the time being it is strongly focused on clusters implementing any DRMAA compatible resource manager (i.e. Oracle Grid Engine) which working nodes have a shared folder in common. Other, more flexible infrastructures (such as the Amazon EC2) are considered for future implementations.

Workflows in Wok are defined in an xml file with the .flow extension. This definition includes:

• the different modules (or pieces of processing)
• the interconnections between modules (i.e. the input of module B links with the output of module A)
• explicit dependencies (i.e. module A cannot be executed until module B has finished)
• descriptions that can be used to generate documentation automatically or to create web forms

Each module corresponds with a piece of software that has to be run in order to process some input and generate an output. For now, only Python scripts are allowed, but they can be used to execute software written in other languages.

Workflows in Wok can be treated as any software project and managed with version control system tools and the IDE of your choice.

Wok can be used as a terminal script or can be run in server mode.

The execution of a workflow in the terminal is done using the wok-run script which allows few options:

• An instance name (-n name), which allows to run the same workflow many times simultaneously independently
• Configuration files (-c file.conf), the configuration can be splitted in as much files as desired
• Configuration parameters (-D param=value), which overwrite any previous configuration in configuration files

The workflow definition file (i.e. myworkflow.flow) is passed as the first argument.

To monitor the execution of the workflow there are different resources available:

• The web server that allows to interact with the engine in a very straightforward way. Recommended!.
• The logs emited by the wok-run through the standard output,
• The intermediate files generated by Wok (i.e. the tasks output files)

It has been designed for workflow developers who feel more confortable programming than doing hundred of clicks and drag & drop's, and also for those who want infraestructure flexibility and full control and monitorization of the execution.

Authors

It is being developed by Christian Pérez-Llamas under the Biomedical Genomics Research Group.

The database of Genotypes and Phenotypes (dbGaP) was developed to archive and distribute the results of studies that have investigated the interaction of genotype and phenotype. Such studies include genome-wide association studies, medical sequencing, molecular diagnostic assays, as well as association between genotype and non-clinical traits. The advent of high-throughput, cost-effective methods for genotyping and sequencing has provided powerful tools that allow for the generation of the massive amount of genotypic data required to make these analyses possible.

dbGaP provides two levels of access - open and controlled - in order to allow broad release of non-sensitive data, while providing oversight and investigator accountability for sensitive data sets involving personal health information. Summaries of studies and the contents of measured variables as well as original study document text are generally available to the public, while access to individual-level data including phenotypic data tables and genotypes require varying levels of authorization.

View Certificate of Confidentiality

The data in dbGaP will be pre-competitive, and will not be protected by intellectual property patents. Investigators who agree to the terms of dbGaP data use may not restrict other investigators' use of primary dbGaP data by filing intellectual property patents on it. However, the use of primary data from dbGaP to develop commercial products and tests to meet public health needs is encouraged.

Submission Policy

Submitters who are not Federally-funded and affiliated with an NIH IC will need to work with an NIH DAC so that proposed submission can be reviewed for consistency with appropriate policies to protect the privacy of research participants and confidentiality of their data. Submissions to dbGaP will not be accepted without assurance that the submitting institution approves the submission and has verified that the data submission is consistent with all applicable laws and regulations, as well as institutional policies. Submitters must also identify any limits on research uses of the data that are specifically set by individual research participants, e.g., through their informed consent.

Data Content and Organization

Open-Access Data

Open-access data can be browsed online or downloaded from dbGaP without prior permission or authorization. These data will include, but may not be limited to, the following:

dbGaP Data Type	Where to Find It
Studies	'Study' column when browsing studies
	Result of a search under the tab 'Studies'
	Part of the breadcrumb path of a variable or document
Study Documents	Link from 'Browse Studies'
	Link under 'Associated Documents' on study report
	Result of a search under the tab 'Study Documents'
Phenotypic Variables	Link under 'Browse Studies'
	Link under 'Associated Variables' on study report
	Result of a search under the tab 'Variables'
Genotype-Phenotype Analyses	Link under 'Associated Analyses' on variable report
	Link under 'Associated Analyses' on study report Read more

About Us

In a nutshell... This is the place to find out about, take part in, and contribute to science through recreational activities and research projects. Learn more about citizen science.

If you're a scientist or a representative of a citizen science organization or community group: This is the place to tell eager people about your work and get them interested in helping out.

Our Mission

SciStarter will bring together the millions of citizen scientists in the world; the thousands of potential projects offered by researchers, organizations, and companies; and the resources, products, and services that enable citizens to pursue and enjoy these activities. 

We aim to:

Enable and encourage people to learn about, participate in, and contribute to science through both informal recreational activities and formal research efforts.

Inspire greater appreciation and promote a better understanding of science and technology among the general public.

Create a shared space where scientists can talk with citizens interested in working on or learning about their research projects.

Satisfy the popular urge to tinker, build, and explore by making it simple and fun for people—singles, parents, grandparents, kids—to jump in and get their hands dirty with science.

Our Team

Darlene Cavalier

Founder

darlene@scistarter.com

Darlene is also the founder of Science Cheerleader  a popular website and organization that works with 250 current and former NFL and NBA cheerleaders pursuing science and technology careers to promote science and the involvement of citizens in science and science-related policy. She has held executive positions at Walt Disney Publishing and has worked at Discover magazine for 15 years, where she now is a senior adviser and writer. She has created national science awards programs, science education initiatives, and a series of science-themed roundtable discussions for, among others, the Disney Institute, Space.com, Sally Ride's Imaginary Lines, and the Franklin Institute. She also serves on the Steering Committee for Science Debate and is a founding partner of Expert and Citizen Assessment of Science and Technology, which engages experts, stakeholders, and everyday citizens in assessing the implications of emerging developments in science and technology. She originated and managed the Emmy award-winning Science of NFL Football series produced by the NFL, NBC Sports, NBC Learn, the National Science Foundation and Science Cheerleader.

A former Philadelphia 76ers cheerleader, Darlene does not regret the years she gabbed through high school science classes. She earned a Master's degree at the University of Pennsylvania, studying science history, sociology, and science policy to learn more about people like herself: "hybrid actors," citizens interested in but not formally trained in the sciences. Discovering it was remarkably difficult to find opportunities to participate in science in any meaningful way, she launched SciStarter. Darlene lives in Philadelphia with her husband and four children, who have made it a hobby to explore the rainforests of Costa Rica. She's also a faculty associate at Arizona State University where she teaches a graduate course, aptly titled, Citizen Science.

Lily Bui 

Executive Editor

Lily@scistarter.com

Lily Bui holds dual degrees in International Studies and Spanish from the University of California Irvine. She has worked on Capitol Hill in Washington, D.C.; served in AmeriCorps in Montgomery County, Maryland; worked for a New York Times bestselling ghostwriter; and performed across the U.S. as a touring musician. She currently works in public media at WGBH-TV and the Public Radio Exchange (PRX) in Boston, MA. In her spare time, she thinks of cheesy science puns. Follow @dangerbui. 

Jenna Morgan Lang

Editor, Featured Projects and Newsletter

Jenna@scistarter.com

Dr. Jenna Lang spends her days exploring the various means by which microbes rule the world. She has worked with Jonathan Eisen since 2006, first as an employee of the DOE Joint Genome Institute, then as a Microbiology PhD student, and now as a permanent fixture in his lab at UC Davis. Jenna became hooked on Citizen Science while working with Darlene on Project MERCCURI, and now aims to include a citizen science component in all future research projects. For fun, she likes to play poker, at the Bellagio, in her wedding dress.

John Ohab

Contributor

john@scistarter.com

Dr. John Ohab is a digital strategist at the U.S. Naval Research Laboratory. John was previously a new technology analyst at the Department of Defense  Public Web Program, providing research and evaluation of web technology initiatives. He also led Defense Department's award-winning outreach project, “Armed with Science,” a cross-agency effort to connect military scientists and engineers with the public through social media. John joined the government through consecutive American Association for the Advancement of Science (AAAS) Science and Technology Policy Fellowships at the Department of Defense (2008) and the National Institute of Mental Health (2007). John received his B.S. in biopsychology from UC Santa Barbara in 2002 and his Ph.D. in neuroscience from UCLA in 2007. John was born and raised in Tempe, Arizona, experienced a moderately successful run in high school varsity tennis, and is waiting patiently for that elusive Arizona Cardinals Super Bowl victory.

Mark Severance

Director of Space-based citizen science projects

Mark@scistarter.com

Mark Severance is SciStarter’s Space Guy and he has been a Space Guy all of his life. A NASA engineer at the Johnson Space Center in Houston, Mark has spent most of his career in Mission Control Center-Houston as a Flight Controller for the Space Shuttle and International Space Station. He also spent time in Mission Control Center-Moscow as a NASA Operations Lead early in the ISS program and when NASA had Astronauts working onboard the Mir space station. He has had a life-long interest in spaceflight and views the space program as a catalyst for engaging minds of all ages in a deeper understanding of science, engineering, technology and mathematics. Mark holds BS degrees in Physics and Electrical Engineering from SMU and MS in Physical Science, with a concentration in Orbital Mechanics, from the University of Houston. He began his hands on interest in space as teenager through his radio tracking of Soviet and Chinese human and robotic spacecraft in conjunction with the Kettering Group. He credits his satellite tracking as the most directive force in his educational and professional careers. Mark is currently a NASA engineer and manger for a space communications lab at the Johnson Space Center. Previous to this assignment, he worked in NASA’s Office of Education to start a program of educational activities and experiments onboard the ISS. He is heading up SciStarter’s in-development suite of space-related, citizen science projects.

Jonathan Brier

Strategic Advisor

brierjon@scistarter.com

Jonathan Brier is citizen science enthusiast from Michigan who enjoys working with Internet connected technologies a little too much. He holds a M.S. in Information and specialized in social computing from the University of Michigan School of Information and a B.S. in Media and Communication technologies from Michigan State University. His interest for science began with his continued use of the word “why” for which his father an engineer and mother a teacher took the time to give an explanation that would make any scientist proud. Jon’s citizen science passion began with his discovery of the SETI@home distributed computing project after watching the movie Contact. This branched to all things citizen science as he learned of more ways science research could harness public participation. Outside his day job as a User Experience Researcher at the University of Michigan, he works with GridRepublic on BOINC powered distributed computing projects and scours the Internet for anything and everything related to citizen science. He hopes to bring added enthusiasm and expertise to SciStarter.

Caren Cooper

Contributor

Caren@scistarter.com

Dr. Caren Cooper is also a blogger for Scientific American and the Public Library of Science. She is a research associate at the Cornell Laboratory of Ornithology and Senior Fellow in the Environmental Leadership Program. She is co-chair of the publications committee of the newly forming Association for Citizen Science and co-editor of an upcoming special feature on citizen science in the open-access journal Ecology & Society. She has authored over 35 scientific papers, co-developed software to automate metrics of incubation rhythms, and is co-creator of NestWatch, CamClickr, Celebrate Urban Birds, YardMap, and the House Sparrow Project. Follow her @CoopSciScoop. She likes to propel herself on one wheel, two wheel, and eight wheel devices.

Nick Fordes

Contributor

Nick@scistarter.com

Nick Fordes is a science enthusiast who enjoys doing, teaching, and communicating science.  Nick recently graduated from the University of Idaho with an M.S. in Water Resources.  His research involved creating a web-based participatory GIS application for use in watershed management. He has a true love for technology and appreciation for what the web-based communications can do for promoting science and increasing science literacy.   Nick most recently worked with the Council for Environmental Education, developing K-12 environmental science based curriculum.  In his spare time, Nick enjoys biking the bayous in Houston and fishing as often as he can.  He has been known to use his scientific knowledge to make a pretty mean brisket.

Lisa Gardiner

Contributor

lisa@sciscistarter.com

Dr. Lisa Gardiner enjoys exploring the Earth from the tops of Colorado’s mountains to the bottom of tropical seas. She has a background in earth science, climate science, ecology, and paleontology - receiving her B.A. from Smith College in Geology and Marine Science and her Ph.D. from University of Georgia in Geology. She is currently honing her skills writing about science in the M.F.A. program at Goucher College. Lisa started Citizen Science Buzz, a blog on Talking Science to share exciting stories about how the public is getting involved with science. Lisa also develops resources for the public, students, and teachers to learn about the earth at Spark, UCAR Science Education. She has written for educational websites, led workshops for teachers, taught environmental education, and occasionally helped develop museum exhibits. She is the author and illustrator of several books and articles about science for children. For several years, Lisa’s eyes were glued to fossil coral reefs in the Bahamas as she searched for tiny clams and snails to study for her dissertation. Now she lives a mile above the ocean in Colorado and is a fan on hiking in summer, whether through mountain tundra or through city blocks, and skiing and snowshoeing in winter. When wearing her artist hat, Lisa creates painting of trees (or forests, depending on your perspective).

Pete Madden

Contributor

Pete@scistarter.com

Pete Madden is a freelance journalist based in Los Angeles, California. He holds an M.S. in Digital Media from the Columbia Journalism School and a B.A. in Communication Studies and English from Vanderbilt University. He is currently Content Coordinator at Escape Apps, a tech startup that creates travel and local discovery smartphone apps, and he has worked for the Los Angeles Times, ABC World News with Diane Sawyer, and Regis High School, a tuition-free prep school in New York City. An avid swimmer and diver, Pete has been lucky enough to explore the reefs in Australia, Belize, and the Galapagos, and when he's not writing about citizen science, you can find him planning his next underwater adventure.

Read more 

Bioconductor is an open source, open development software project to provide tools for the analysis and comprehension of high-throughput genomic data. It is based primarily on the R programming language.

The Bioconductor release version is updated twice each year, and is appropriate for most users. There is also a development version, to which new features and packages are added prior to incorporation in the release. A large number of meta-data packages provide pathway, organism, microarray and other annotations.

The Bioconductor project started in 2001 and is overseen by a core team, based primarily at the Fred Hutchinson Cancer Research Center, and by other members coming from US and international institutions. It gained widespread exposure in a 2004 Genome Biology paper.

Bioconductor Packages

Most Bioconductor components are distributed as R packages. The functional scope of Bioconductor packages includes the analysis of DNA microarray, sequence, flow, SNP, and other data.

Project Goals

The broad goals of the Bioconductor project are:

• To provide widespread access to a broad range of powerful statistical and graphical methods for the analysis of genomic data.
• To facilitate the inclusion of biological metadata in the analysis of genomic data, e.g. literature data from PubMed, annotation data from Entrez genes.
• To provide a common software platform that enables the rapid development and deployment of extensible, scalable, and interoperable software.
• To further scientific understanding by producing high-quality documentation and reproducible research.
• To train researchers on computational and statistical methods for the analysis of genomic data.

Main Project Features

The R Project for Statistical Computing. Using R provides a broad range of advantages to the Bioconductor project, including:

• A high-level interpreted language to easily and quickly prototype new computational methods.
• A well established system for packaging together software with documentation.
• An object-oriented framework for addressing the diversity and complexity of computational biology and bioinformatics problems.
• Access to on-line computational biology and bioinformatics data.
• Support for rich statistical simulation and modeling activities.
• Cutting edge data and model visualization capabilities.
• Active development by a dedicated team of researchers with a strong commitment to good documentation and software design.

Read more

Source:stephenturner & gettinggeneticsdone

• Workshops:

Cold Spring Harbor Courses: meetings.cshl.edu/courses.html

Cold Spring Harbor has been offering advanced workshops and short courses in the life sciences for years. Relevant workshops include Advanced Sequencing Technologies & Applications, Computational & Comparative Genomics, Programming for Biology, Statistical Methods for Functional Genomics, the Genome Access Course, and others. Unlike most of the others below, you won't find material from past years' CSHL courses available online.

Canadian Bioinformatics Workshops: bioinformatics.ca/workshops

Bioinformatics.ca through its Canadian Bioinformatics Workshops (CBW) series began offering one and two week short courses in bioinformatics, genomics and proteomics in 1999. The more recent workshops focus on training researchers using advanced high-throughput technologies on the latest approaches being used in computational biology to deal with the new data. Course material from past workshops is freely available online, including both audio/video lectures and slideshows. Topics include microarray analysis, RNA-seq analysis, genome rearrangements, copy number alteration,network/pathway analysis, genome visualization, gene function prediction, functional annotation, data analysis using R, statistics for metabolomics, and much more.

UC Davis Bioinformatics Training

 Program:training.bioinformatics.ucdavis.edu

The UC Davis Bioinformatics Training program offers several intensive short bootcamp workshops on RNA-seq, data analysis and visualization, and cloud computing with a focus on Amazon's computing resources. They also offer a week-long Bioinformatics Short Course, covering in-depth the practical theory and application of cutting-edge next-generation sequencing techniques. Every course's documentation is freely available online, even if you didn't take the course.

MSU NGS Summer Course: bioinformatics.msu.edu/ngs-summer-course-2013

This intensive two week summer course will introduce attendees with a strong biology background to the practice of analyzing short-read sequencing data from Illumina and other next-gen platforms. The first week will introduce students to computational thinking and large-scale data analysis on UNIX platforms. The second week will focus on mapping, assembly, and analysis of short-read data for resequencing, ChIP-seq, and RNAseq. Materials from previous courses are freely available online under a CC-by-SA license.

Genetic Analysis of Complex Human Diseases: hihg.med.miami.edu/edu...

The Genetic Analysis of Complex Human Diseases is a comprehensive four-day course directed toward physician-scientists and other medical researchers. The course will introduce state-of-the-art approaches for the mapping and characterization of human inherited disorders with an emphasis on the mapping of genes involved in common and genetically complex disease phenotypes. The primary goal of this course is to provide participants with an overview of approaches to identifying genes involved in complex human diseases. At the end of the course, participants should be able to identify the key components of a study team, and communicate effectively with specialists in various areas to design and execute a study. The course is in Miami Beach, FL. (Full Disclosure: I teach a section in this course.) Most of the course material from previous years is not available online, but my RNA-seq & methylation lectures are on Figshare.

UAB Short Course on Statistical Genetics and Genomics:soph.uab.edu/ssg/...

Focusing on the state-of-art methodology to analyze complex traits, this five-day course will offer an interactive program to enhance researchers' ability to understand & use statistical genetic methods, as well as implement & interpret sophisticated genetic analyses. Topics include GWAS Design/Analysis/Imputation/Interpretation; Non-Mendelian Disorders Analysis; Pharmacogenetics/Pharmacogenomics; ELSI; Rare Variants & Exome Sequencing; Whole Genome Prediction; Analysis of DNA Methylation Microarray Data; Variant Calling from NGS Data; RNAseq: Experimental Design and Data Analysis; Analysis of ChIP-seq Data; Statistical Methods for NGS Data; Discovering new drugs & diagnostics from 300 billion points of data. Video recording from the 2012 course are available online.

MBL Molecular Evolution Workshop: hermes.mbl.edu/education/...

One of the longest-running courses listed here (est. 1988), the Workshop on Molecular Evolution at Woods Hole presents a series of lectures, discussions, and bioinformatic exercises that span contemporary topics in molecular evolution. The course addresses phylogenetic analysis, population genetics, database and sequence matching, molecular evolution and development, and comparative genomics, using software packages including AWTY, BEAST, BEST, Clustal W/X, FASTA, FigTree, GARLI, MIGRATE, LAMARC, MAFFT, MP-EST, MrBayes, PAML, PAUP*, PHYLIP, STEM, STEM-hy, and SeaView. Some of the course materials can be found by digging around the course wiki.

• Online Material:

Canadian Bioinformatics Workshops: bioinformatics.ca/workshops

(In person workshop described above). Course material from past workshops is freely available online, including both audio/video lectures and slideshows. Topics include microarray analysis, RNA-seq analysis, genome rearrangements, copy number alteration, network/pathway analysis, genome visualization, gene function prediction, functional annotation, data analysis using R, statistics for metabolomics, andmuch more.

UC Davis Bioinformatics Training Program:

 training.bioinformatics.ucdavis.edu

(In person workshop described above). Every course's documentation is freely available online, even if you didn't take the course. Past topics include Galaxy, Bioinformatics for NGS, cloud computing, and RNA-seq.

MSU NGS Summer Course: bioinformatics.msu.edu/ngs-summer-course-2013

(In person workshop described above). Materials from previous courses are freely available online under a CC-by-SA license, which cover mapping, assembly, and analysis of short-read data for resequencing, ChIP-seq, and RNAseq.

EMBL-EBI Train Online: www.ebi.ac.uk/training/online

Train online provides free courses on Europe's most widely used data resources, created by experts at EMBL-EBI and collaborating institutes. Topics include Genes and Genomes, Gene Expression,Interactions, Pathways, and Networks, and others. Of particular interest may be the Practical Course on Analysis of High-Throughput Sequencing Data, which covers Bioconductor packages for short read analysis, ChIP-Seq, RNA-seq, and allele-specific expression & eQTLs.

UC Riverside Bioinformatics Manuals: manuals.bioinformatics.ucr.edu

This is an excellent collection of manuals and code snippets. Topics include Programming in R, R+Bioconductor, Sequence Analysis with R and Bioconductor, NGS analysis with Galaxy and IGV, basicLinux skills, and others.

Software Carpentry: software-carpentry.org

Software Carpentry helps researchers be more productive by teaching them basic computing skills. We recently ran a 2-day Software Carpentry Bootcamp here at UVA. Check out the online lectures for some introductory material on Unix, Python, Version Control, Databases, Automation, and many other topics.

Coursera: coursera.org/courses

Coursera partners with top universities to offer courses online for anytone to take, for free. Courses are usually 4-6 weeks, and consist of video lectures, quizzes, assignments, and exams. Joining a course gives you access to the course's forum where you can interact with the instructor and other participants. Relevant courses include Data Analysis, Computing for Data Analysis using R, and Bioinformatics Algorithms, among others. You can also view all of Jeff Leek's Data Analysis lectures on Youtube.

Rosalind: http://rosalind.info

Quite different from the others listed here, Rosalind is a platform for learning bioinformatics through gaming-like problem solving. Visit the Python Village to learn the basics of Python. Arm yourself at theBioinformatics Armory, equipping yourself with existing ready-to-use bioinformatics software tools. Or storm the Bioinformatics Stronghold, implementing your own algorithms for computational mass spectrometry, alignment, dynamic programming, genome assembly, genome rearrangements, phylogeny, probability, string algorithms and others.

• Other Resources:

Titus Brown's list bioinformaticscourses: Includes a few others not listed here (also see the comments).

GMOD Training and Outreach: GMOD is the Generic Model Organism Database project, a collection of open source software tools for creating and managing genome-scale biological databases. This page links out to tutorials on GMOD Components such as Apollo, BioMart, Galaxy, GBrowse, MAKER, and others.

Seqanswers.com: A discussion forum for anything related to Bioinformatics, including Q&A, paper discussions, new software announcements, protocols, and more.

Biostars.org: Similar to SEQanswers, but more strictly a Q&A site.

BioConductor Mailing list: A very active mailing list for getting help with Bioconductor packages. Make sure you do some Google searching yourself first before posting to this list.

Bioconductor Events: List of upcoming and prior Bioconductor training and events worldwide.

Learn Galaxy: Screencasts and tutorials for learning to use Galaxy.

Galaxy Event Horizon: Worldwide Galaxy-related events (workshops, training, user meetings) are listed here.

Galaxy RNA-Seq Exercise: Run through a small RNA-seq study from start to finish using Galaxy.

Rafael Irizarry's Youtube Channel: Several statistics and bioinformatics video lectures.

PLoS Comp Bio Online Bioinformatics Curriculum: A perspective paper by David B Searls outlining a series of free online learning initiatives for beginning to advanced training in biology, biochemistry, genetics, computational biology, genomics, math, statistics, computer science, programming, web development, databases, parallel computing, image processing, AI, NLP, and more.

Getting Genetics Done: Shameless plug – I write a blog highlighting literature of interest, new tools, and occasionally tutorials in genetics, statistics, and bioinformatics. I recently wrote this post about how to stay current in bioinformatics & genomics.