Genomics Basics. Genome Browsers and Genomic Formats
An introduction to the field of genomics. Data availability and methodologies that are being developed for the analysis of complete genomes. Description of genomic data types (sequences, annotations, continuous data) and relevant format
Introduction to NGS - Methodology and Applications
An overview of the current state-of-the-art of NGS platforms, the methodology principles behind them and the applications for which they are used. We will be covering the main applications of NGS through its coupling with gene-expression analysis, analysis of genomic variability, gene regulation, chromatin structure etc.
This is the first of a series of classes devoted to downstream analysis of NGS data. It covers the basic initial analyses performed on NGS raw data including a number of caveats one should be aware of, plus the introductory, necessary terminology of NGS.
Mapping of sequence reads is the primary and often the most demanding step in downstream analyses. This class will first introduce the problem of multiple, short-read alignments and then cover the basic algorithms designed for this task and briefly discuss the principles behind them, alongside subtle differences between them.
Peak detection is the most challenging aspect in ChIPSeq approaches when one needs to determine regions of significant enrichment of reads in contrast to expected background noise. A number of approaches have been proposed for this task and this class will attempt a general overview before looking into some in greater detail.
RNASeq Data analysis - Differential Expression
This class will cover the basic principles behind differential gene expression analysis, starting with data normalization and various biases than one should bear in mind before attempting to compare gene expression. We will move on to discuss various models applied for this task and particularly focus on the statistical inference of the results.
Functional Analysis and Positional Enrichments
Gaining biological insight from NGS data is most of the times not straightforward due to the size of the datasets. In this class we will be discussing ways to summarize, interpret and prioritize results from NGS applications. The main focus will be put on a) the functional analysis of gene expression data and b) the positional enrichments of ChIPSeq data or other similar datasets in context of specific genomic markers.
Whole Exome Sequencing - Variant detection and Gene Prioritization
In this class we will be discussing how the ever-increasing speed and output of NGS methodologies and the rapidly decreasing cost of sequencing is assisting the analysis of genetic variability in an unprecedented way. We will be discussing how Whole-Exome-Sequencing (WES) can help us detect variants of medical interest as we overview the various steps in the process from sequencing to determining a variant and assessing its expected impact.
A short Bioinformatics Workshop for NGS
We will briefly present some real-life problems that we can encounter while working with NGS data and discuss solutions and strategies for the efficient analysis of the data and their interpretation.