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CSAMA 2019
17th edition

Bressanone-Brixen
July 21-26, 2019

Registration closes on 14 June 2019!

Lecturers

  • Simon Anders, Center for Molecular Biology Heidelberg
  • Vincent J. Carey, Harvard Medical School
  • Laurent Gatto, UCLouvain
  • Robert Gentleman, 23andMe, Mountain View
  • Wolfgang Huber, EMBL Heidelberg
  • Katharina Imkeller, German Cancer Research Center, Heidelberg
  • Martin Morgan, Roswell Park Comprehensive Cancer Center, Buffalo
  • Johannes Rainer, European Academy of Bozen
  • Davide Risso, University of Padova
  • Lori Shepherd, Roswell Park Comprehensive Cancer Center, Buffalo
  • Charlotte Soneson, Friedrich Miescher Institute for Biomedical Research, Basel

Teaching Assistants

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

Organized in collaboration with

Previous editions of CSAMA

About

The one-week intensive course Statistical Data Analysis for Genome-Scale Biology teaches statistical and computational data analysis of multi-omics studies in biology and biomedicine. It comprises lectures covering underlying theory and state of the art, and practical hands-on exercises based on the R / Bioconductor environment. 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.

The course is intended for researchers who have basic familiarity with the experimental technologies and their applications in biology, and who are interested in making the step from a user of bioinformatics software towards adapting or developing their own analysis workflows. The four practical sessions of the course will require you to follow and modify scripts in the computer language R. To freshen up your R skills, see below for some links.

Topics

  • Introduction to R and Bioconductor
  • The elements of statistics: hypothesis testing, multiple testing, bootstrap and permutation testing, clustering and classification, machine learning, visualisation
  • RNA-Seq data analysis – bulk and single cell
  • Computing with sequences and genomic intervals
  • Working with annotation – genes, genomic features, variants, transcripts and proteins
  • Gene set enrichment analysis
  • MS-based proteomics and metabolomics
  • Basics of microbiome analysis
  • Experimental design, batch effects and confounding
  • Reproducible research and workflow authoring with R markdown
  • Package development, version control and developer tools
  • Working with large data: performance parallelisation and cloud computing

Course Structure

The course consists of

  • Morning lectures: 20 x 45 minutes: Monday to Friday 8:30-12:00h
  • Practical computer tutorials in the afternoons: Mon, Tue, Thu, Fri 13:30-16:30h
  • Evening sessions: Mon, Tue 20:30-22:00h
  • A hike in the mountains and networking opportunity: Wed 14:30-22:00h

Course Materials

The course materials for the labs and lectures will be available for download prior to the course.

Download the course materials for the labs.
Download the course materials for the lectures.

Computer Tutorials

You will work on the labs at your own pace in small groups with expert guidance (all lecturers from the morning sessions plus teaching assistants).

Participants are required to bring their own laptop with the most recent release versions of R and Bioconductor installed: R-3.6.x and Bioconductor 3.9 installed (details will be provided). Please make sure that your computer’s hardware is sufficiently powered (>=8 GB RAM, >20 GB free disk space) and that you have administrator rights. The course material will be provided by a local network wireless network – however, this not connected to the internet. Please set up your computer beforehand; internet connections at the course venue can be slow and unreliable.

Social Programme

One of the afternoons is for a joint cultural and outdoors activity. We plan a trip into the mountains with a (light) walk in the high-alpine area, weather permitting, and delicious local dinner.

RossAlm

14.55hWe meet at “Casa della Gioventù” and walk 1 min to the bus waiting for us in Via Dante.

Please take the underpass to cross “Via Peter Mayr.”

The way to the bus stop in Via Dante

15:00hThe bus leaves towards the cable car for Mount Plose.

15:30hThe cable car takes us to the top of Mount Plose in about 20-30 min.

45-60 minHiking to RossAlm at 2200 m altitude.

18:00hSocial dinner at RossAlm.

20:30hTime to leave! We walk back to the bus from RossAlm.

21:30hThe bus takes us back to Brixen.

Please pack/bring:

  • Solid footwear (ideal: hiking shoes or boots)
  • Jacket or warm sweater for the descent (it may get quite fresh)

Please note: If you don’t attend the social programme, please let us know at the latest on Monday 22 July via email to bell [at] embl.de

No Internet Access

Please note: The course venue does not provide stable internet access. The course provides a local network with the course material.


R BASICS

Programme

Sunday, July 21

18:00–20:00 Registration & Installation help desk
18:00–20:00 Get Together with drinks and nibbles

Monday, July 22

08:30–09:15 Lecture 01 Introduction to R and Bioconductor (MM)
09:15–10:00 Lecture 02 Using Bioconductor for computing with sequences and ranges (LS)
10:00–10:30 Coffee break
10:30–11:15 Lecture 03 Linear models (basic intro) (RG)
11:15–12:00 Lecture 04 Hypothesis testing incl. multiple (WH)
12:00–13:00 Lunch break
13:00–13:30   Installation help desk
13:30–15:00 Lab 1 Introduction to Bioconductor (MM)
15:00–16:30 Lab 2 Multiple testing, FDR (WH)
16:30–17:00 Flashlight talks
  • Monika Pepelnjak
  • Maximilian J. Helf
  • Petra Svatonova
  • Domenico di Fraia
20:30–22:00 Evening session tbc

Tuesday, July 23

08:30–09:15 Lecture 05 Quantification (both alignment and alignment-free) (CS)
09:15–10:00 Lecture 06 Normalization and differential expression (SA)
10:00–10:30 Coffee break
10:30–11:00 Lecture 06 (cont.) Single-cell technology (incl. Announcement of group project) (KI, DR)
11:00–12:00 Lecture 07 Single-cell data analysis I: error models, normalization, factor analysis, (ZI)NB-WaVE. (DR)
12:00–13:30 Lunch break
13:30–16:30 Lab 3 End-to-end RNA-Seq workflow (SA, CS, DR, WH, JR)
16:30–17:00 Flashlight talks
  • Staci Thornton
  • Fabienne Meier-Abt
  • Inigo Barrio
  • Henry F. Thomas
20:30–22:00 Evening session
  • tbc

Wednesday, July 24

08:30–09:15 Lecture 08 Experimental design, batch effects and ‘correction’, confounding (CS)
09:15–10:00 Lecture 09 eQTLs, sQTLs (RG)
10:00–10:30 Coffee break
10:30–11:15 Lecture 10 Single-cell data analysis II: factor analysis, dimension reduction (“t-SNE”), cell type assignment (SA)
11:15–12:00 Lecture 11 Annotation resources (JR with MM/LS)
12:00–13:30 Lunch break
14:50–22:30   Social programme: excursion to the mountains, dinner

Thursday, July 25

08:30–09:15 Lecture 12 Visualization, grammar of graphics and ggplot2 (WH)
09:15–10:00 Lecture 13 Mass spec proteomics (LG)
10:00–10:30 Coffee break
10:30–11:00 Lecture 14 Metabolomics (JR)
11:00–11:45 Lecture 15 Clustering and classification (VJC)
11:45–12:00 BiocFileCache / Annotation resources (LS)
12:00–13:30 Lunch break
13:30–16:30 Lab 4 Mass spec proteomics (LG)
13:30–16:30 Lab 5 Preprocessing of untargeted metabolomics data (JR)
13:30–16:30 Lab 6 BiocFileCache / Annotation resources (LS)
13:30–16:30 Group work on single cell technologies (KI)
16:30–17:00 Flashlight talks
  • Amir Fallahshahroudi
  • Constantin Ahlmann-Eltze
  • Thomas Naake
  • tbc

Friday, July 26

08:30–09:15 Lecture 16 High-throughput genetics – CRISPR screens analysis (KI)
09:15–10:00 Lecture 17 Machine Learning (RG)
10:00–10:30 Coffee break
10:30–11:15 Lecture 18 Gene set enrichment analysis (MM)
11:15–12:00 Lecture 19 Working with large-scale data (MM with VJC)
12:00–13:30 Lunch break
13:30–14:00 Presentations from group work on single-cell technologies
14:00–16:30 Lab 7 Creating and maintaining an R package (DR)
14:00–16:30 Lab 8 Graphics. Including making an interactive plot in a shiny GUI (WH)
14:00–16:30 Lab 9 Large data, performance, and parallelization; large-scale efficient computation with genomic intervals (VJC, MM)
14:00–16:30 Lab 10 Machine learning (supervised) (WH) (optional)
16:30   Closing remarks

Flashlight talks

Each talk 5 min + 2 min questions

Lecturers and Teaching Assistants

Simon Anders (SA), Simone Bell (SB), Vincent J. Carey (VJC), Laurent Gatto (LG), Robert Gentleman (RG), Wolfgang Huber (WH), Katharina Imkeller (KI), Martin Morgan (MM), Davide Risso (DR), Mike Smith (MS), Johannes Rainer (JR), Lori Shepherd (LS), Charlotte Soneson (CS).

Venue

We will welcome you on Sunday around 18:00h for a welcome buffet at the main site (1).

The main idea of this pre-course meeting is to meet each other in an informal environment, but you can also consider this as a course registration where we will give you all the course materials including the receipt of your payment.

Please note: there will be food and drinks to satisfy your hunger and thirst, and usually we move on into the town in smaller groups to enjoy the many beergardens and restaurants.

Conference sites

The following map is a very reduced one. You can have a big one in PNG format, or you can browse an interactive one from the web page of the Tourist Office in Bressanone-Brixen.

Conference sites (small map)

(1) Casa della Gioventù – main course site:

Casa della Gioventù is the place where both morning lectures and laboratory will take place, and it is also the place of the Welcome Buffet.

It is a building of the University of Padova, located in Via Rio Bianco 6, 5 minutes from the town center.

(2) Hotel Albero Verde (Grüner Baum):

It is a hotel were many of the participants usually stay.

(3) The railway station:

Where many of you will arrive.

Travel & Accommodation

How to get to Bressanone – Brixen

Bressanone (or Brixen) is in the bilingual province of Bolzano (Bozen) at 500 meters of altitude, in the Italian Alps, close to the Dolomites.

View Larger Map

By Train

Bressanone is on the international line between Munich (Germany) and Verona (Italy). Every train on this line stops in Bressanone. Moreover, there are many commuter connections from Innsbruck (Austria) and from Bolzano (Italy) to Bressanone.

The train from Verona P.ta Nuova to Bressanone takes about 2 hours, with frequent connections throughout the day. The train from Munich takes about 3.5 hours, with connections every 2 hours.

By Airplane

Several airports have good train connections to Bressanone:

  • Bolzano, Italy (BZO) 50 km (30 minutes by train)
  • Innsbruck, Austria (INN) 80 km (1 hours by train)
  • Verona, Italy (Valerio Catullo, VRN) 200 km
  • Munich, Germany (Franz-Josef Strauss, MUC) 260 km
  • Venezia, Italy (Marco Polo, VCE) 320 km
  • Milano-Linate, Italy (LIN) 330 km
  • Milano-Malpensa, Italy (MXP) 350 km

The closest large airport is Verona (Valerio Catullo) international airport. From Verona airport to the railway station Verona P.ta Nuova (see above) there are shuttle busses every 20 minutes from 6:30am to 11:35pm. From Verona to Bressanone it takes about 2 hours by train, and you have several trains per day (see above).

About Munich: please do not confuse Munich’s main airport (Franz-Josef Strauss) with Ryanair’s “Munich West” (Memmingen) – it is far out in the Allgäu, and it is not much fun coming from there by public transport; with a rental car, it may however be an option.

Hotel information

You need to make your reservation directly.

Hotel Gruener Baum (Albero Verde)

Please make your reservations yourself and ask for further information by sending an email to the following address: info@gruenerbaum.it or check their web site for the telephone number.

Hotel Goldene Krone

Please make your reservations yourself and ask for further information by sending an email to the following address: info@goldenekrone.com or check their web site for the telephone number.

Hotel Elephant

Please make your reservations yourself and ask for further information by sending an email to the following address: info@hotelelephant.com or check their web site for the telephone number.

Other accommodation

There also exist two youth hostel-like accommodations. These locations have low fares, and they can be considered as equivalent both for quality and location (Brixen is a small town). Please ask directly them if you need rooms (with or without bath, etc).