Steve Hoffmann (Leipzig University, Leipzig, Germany): The Art of Sequence Alignment
The alignment of sequence reads to the target genome is a fundamental step in next generation sequencing analysis. Mistakes in this step are inevitably looped through the whole investigation. Hence, the careful choice of alignment algorithms, scoring schemes and filters is of utmost importance for the successful study of biological data. This tutorial covers elementary topics of sequence analysis relevant for Next Generation Sequencing analysis and tackles common misconceptionsabout the meaning of base qualities or the treatment of multiple mappings.
David Langenberger (Leipzig University, Leipzig, Germany): DARIO - Analysis of small RNAs Sequencing Data
Small non-coding RNAs (ncRNAs) such as microRNAs, snoRNAs and tRNAs are a diverse collection of molecules with several important biological functions. Current methods for high- throughput sequencing for the first time offer the opportunity to investigate the entire ncRNAome in an essentially unbiased way. However, there is a substantial need for methods that allow a convenient analysis of these overwhelmingly large data sets.
In this tutorial, the problems of mapping short RNA-seq reads to a reference genome will be discussed and a downstream analysis pipeline called DARIO will be presented. DARIO is a free web service that allows biologists to study small RNA-seq experiments. It provides a wide range of analysis features, including quality control, read normalization, ncRNA quantification and prediction of putative ncRNA candidates.
Sebastian J. Schultheiss (Computomics, Tuebingen, Germany) and Geraldine Jean (University of Nantes, Nantes, France): Oqtans: Quantitative transcriptome analysis in the cloud I & II
With increasing throughput of sequencing technologies, large-scale sequencing is becoming routine in many labs, but data analysis still remains a challenge. A vast assortment of tools exists to perform various analysis tasks. Computational pipelines that combine these tools are emerging, but ease of use for non-expert users varies, and with it reproducibility of computational analyses. In this tutorial, we present an open-source workbench integrated in the Galaxy framework that enables researchers to set up a computational pipeline, called Oqtans, for quantitative transcriptome analysis. It's integrated in the easy-to-use Galaxy framework and is accessible locally or in the cloud (http://oqtans.org/). Oqtans provides a modular toolsuite that performs better or as well as the state-of-the-art for short-read alignments, transcript identification/quantification and differential expression analysis. We illustrate how a complete quantitative RNA-seq analysis can be performed easily and effectively with two understandable use cases.