CSAMA 2016 – we were there

The 14th edition of the course Statistical Data Analysis for Genome Scale Biology took place in July 2016 in Bressanone-Brixen. More than 70 participants spent a fantastic week studying in a mix of lectures and practical computer tutorials, learning from the lecturers Wolfgang Huber, Martin Morgan, Vincent Carey, Charlotte Soneson, Simon Anders, Michael Love, Levi Waldron and Jennifer Bryan. Senior scientists, Postdocs and students from the Huber group participated to this course as well. Additionally, everybody enjoyed biking and hiking in the high-alpine regions. One of the highlights of that week was a wonderful hiking tour into the Plose Mountain.

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Wolfgang Huber, Mike Smith, Alejandro Reyes and Levi Waldron enjoyed a mountain bike tour in the late afternoon after the course.

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Wolfgang Huber, Karsten Bach and Nils Kurzawa on another mountain bike tour on Saturday after the course.

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The 2017 course will take place from 11 to 16 June.

Photos from Brixen by Junyan Lu.

The Huber Group on the 5th NCT Run

The race event of the National Center for Tumor Diseases (NCT) Heidelberg took place for the 5th time last Friday, 8 July 2016. Tousands of participants including patients and their families, pysichians, scientists and friends of the NCT run “to opose cancer with a positive note.” An EMBL team supports this initiative every year.
See more (in German only)

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From the left to the right: Annika Gable, Mike Smith, Britta Velten, Karsten Bach, Junyan Lu, Nils Kurzawa and Alejandro Reyes.

CSAMA 2016 Statistics and Computing in Genome Data Science

CSAMA 2016 (14th edition)
Statistics and Computing in Genome Data Science
Bressanone-Brixen, Italy (South Tyrol Alps)
July 10-15, 2016

Lecturers:

  • Simon Anders, Institute for Molecular Medicine, Helsinki
  • Jennifer Bryan, University of British Columbia, Vancouver
  • Vincent J. Carey, Channing Laboratory, Harvard Medical School
  • Wolfgang Huber, European Molecular Biology Laboratory (EMBL), Heidelberg
  • Michael Love, Dana Farber Cancer Institute and the Harvard School of Public Health
  • Martin Morgan, Roswell Park Cancer Institute, Buffalo, New York.
  • Charlotte Soneson, University of Zurich
  • Levi Waldron, CUNY School of Public Health at Hunter College, New York

Teaching Assistants:

  • Simone Bell, EMBL, Heidelberg
  • Alejandro Reyes, EMBL, Heidelberg
  • Mike L. Smith, EMBL, Heidelberg

The one-week intensive course Statistics and Computing in Genome Data Science teaches statistical and computational analysis of multi-omics studies in biology and biomedicine. It covers the underlying theory and state of the art (the morning lectures), and practical hands-on exercises based on the R / Bioconductor environment (the afternoon labs). The course covers the primary analysis of high-throughput sequencing based assays in functional genomics and integrative methods including efficiently operating with genomic intervals, statistical testing, linear models, machine learning, bioinformatic annotation and visualization. At the end of the course, you should be able to run analysis workflows on your own (multi-)omic data, adapt and combine different tools, and make informed and scientifically sound choices about analysis strategies.

Topics include:

  • Introduction to Bioconductor
  • Elements of statistics: hypothesis testing, multiple testing, regression, regularization, clustering and classification (machine learning), visualization
  • Computing with sequences and genomic intervals
  • Integrating multiple layers of ‘omic data
  • Working with annotation – genes, genomic features and variants
  • RNA-Seq data analysis and differential expression
  • Single-cell RNA-Seq
  • Proteomics primers
  • Interactive displays with Shiny

The course consists of

  • morning lectures: 20 x 45 minutes: Monday to Friday 8:30h – 12:00h
  • 4 practical computer tutorials in the afternoons (14:00h – 17:00h) on Monday, Tuesday, Thursday and Friday

The registration for CSAMA 2016 closed on June 15th 2016

Visit the course’s website at: http://www.huber.embl.de/csama

SOUND second consortium meeting

The second consortium meeting of the SOUND project, which is led by Wolfgang Huber, was hosted by our colleagues from IDMEC Lisbon. Principal investigators, postdocs and PhD students attended the meeting and presented recent results and progress in the work packages. All partners are well on track with their project aims and the atmosphere of sharing research developments was quite enthusiastic. Junyan Lu held a talk on “Mechanistic study of drug response using ex-vivo drug testing and multi-omics technology“ and Małgorzata Oleś provided a presentation on “Modulators of drug response identified by multivariate lasso regression”. Wolfgang Huber gave a lecture on “Data driven hypothesis weighting and false discovery rates”.

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SOUND consortium

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Photos from Lisbon by Junyan Lu.

Group Retreat 2015

The group retreat 2015 took place in the end of September in the beautiful Black Forest. In a joint event bringing together the groups of Wolfgang Huber and Judith Zaugg, 22 scientists spent a fantastic time together exchanging their research approaches and results. Additionally, they enjoyed developing and discussing “Blue Sky” science projects in small groups, presented in a “back to basics” way using hand-drawn posters. The retreat was closed with a wonderful hiking tour on the third day.

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Huber Group

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Registration open: CSAMA 2015 (13th ed.) Statistics and Computing in Genome Data Science

CSAMA 2015 (13th edition)
Statistics and Computing in Genome Data Science
Bressanone-Brixen, Italy (South Tyrol Alps)
June 14-19, 2015

Registration for CSAMA 2015 is now open
http://www.huber.embl.de/csama

Lecturers:

  • Martin Morgan, Fred Hutchinson Cancer Research Center (USA)
  • Wolfgang Huber, European Molecular Biology Laboratory
  • Vincent J. Carey, Channing Laboratory, Harvard Medical School (USA)
  • Michael Love, Dana Farber Cancer Institute and the Harvard School of Public Health (USA)
  • Simon Anders, European Molecular Biology Laboratory
  • Mark Robinson, University of Zurich (CH)
  • Laurent Gatto, University of Cambridge (UK)
  • Paul Pyl, University of Copenhagen (DK)

The one-week intensive course “Statistics and Computing in Genome Data Science” teaches statistical and computational analysis of multi-omics studies in biology and biomedicine. It covers the underlying theory and state of the art (the morning lectures), and practical hands-on exercises based on the R / Bioconductor environment (the afternoon labs). The course covers the primary analysis (“preprocessing”) of high-throughput sequencing based assays in functional genomics (transcriptomics, epigenetics, etc.) as well as integrative methods including efficiently operating with genomic intervals, statistical testing, linear models, machine learning, bioinformatic annotation and visualization. At the end of the course, you should be able to run analysis workflows on your own (multi-)omic data, adapt and combine different tools, and make informed and scientifically sound choices about analysis strategies.

Topics include:

  • Introduction to Bioconductor
  • Elements of statistics: hypothesis testing, multiple testing, regression, regularization, clustering and classification (machine learning), visualization
  • Computing with sequences and genomic intervals
  • RNA-Seq data analysis and differential expression
  • ChIP-Seq and epigenetics
  • Integrating DNA variant calls with functional data, and large-scale efficient computation with genomic intervals
  • Working with annotation – genes, genomic features and variants
  • Metagenomics and proteomics primers
  • Single-cell RNA-Seq primer
  • Interactive displays with Shiny

The course consists of

  • morning lectures: 20 x 45 minutes: Monday to Friday 8:30am – 12:00am
  • 4 practical computer tutorials in the afternoons (2pm – 5pm) on Monday, Tuesday,Thursday and Friday

For registration visit our website at: http://www.huber.embl.de/csama

Ascona Workshop 2015

Statistical Learning of Biological Systems from Perturbations

May 31 to June 5, 2015

Registration and details

Advances in biotechnology have made genome-scale measurements routine, including most recent techniques for perturbing individual genes in a targeted manner. These interventional data hold the promise to infer biological networks and to move forward systems biological approaches significantly. A major challenge now is to use the vast amount of data generated from these technologies and to devise appropriate statistical models and computational inference methods. Unlike observational data, interventional data can reveal causal relationships among genes or other biomolecular entities. As such, the statistical analysis and computational integration of perturbation data is an important step towards large-scale biological system identification with abundant applications in biology and medicine.

This workshop will (i) explore recent advances and open problems in statistical learning, data integration, and causal inference of biological systems; (ii) present biomedical applications to recent genome-wide perturbation data, such as RNA interference data, obtained, for example, from cancer cells or cells infected by pathogens; and (iii) facilitate meaningful interaction between biomedical and quantitative researchers.

Advanced Course: R programming and development

On 15-16 January 2015 we are hosting the Advanced Course: R programming and development.

The course will focus on two aspects of R programming and development.
The first part will introduce object-oriented programming using R’s S3 and S4 system and describe how to define classes, generic functions and methods. It will also present how to create Bioconductor-compliant R packages and document them. The second part will focus on various advanced topics in R programming such as unit testing, debugging, profiling and calling C/C++ code. It will also describe how to write efficient and elegant code using vectorisation, parallelization, and the functional programming paradigm. Finally, creating web applications with shiny will be discussed.

These topics will be illustrated using a small real-life bioinformatic case study. Participants will produce, at the end of the course, a fully fledged Bioconductor compliant R package.

European Bioconductor Developers’ Meeting

12th-13th January 2015, EMBL Heidelberg

We are proudly hosting this year’s European Bioconductor Developers’ Meeting.

The meeting is aimed at bioinformaticians, programmers and software engineers who contribute to the Bioconductor project, or are interested in developing packages for Bioconductor. The goals are to:

  • foster the exchange of technical expertise,
  • keep contributors up to date with the latest developments,
  • coordinate any related efforts.

For details see the the event’s website.