NGS background

Next generation sequencing
Next generation sequencing (NGS) describes any of several high throughput approaches to sequence DNA in a massively parallel fashion. In contrast to Sanger sequencing, also known as capillary sequencing or first-generation sequencing, NGS is able to sequence millions to 20 billions short sequences (50-400bp each) in parallel per instrument run [1].
In the relatively short time frame since 2005, NGS has fundamentally altered genomics research and allowed investigators to conduct experiments that were previously not technically feasible or affordable [2].
Since then, many different assays have been developed that allow to measure different aspects of the genome. Examples are RNA-Seq, which measures gene expression, ChIP-Seq which measures protein binding, ATAC-Seq which allows to measure open chromatin regions or HiC that allows to measure chromatin interactions to name a few. A comprehensive list of technologies and assays is available from [3]. A major challenge that we address is to develop specific and robust analysis workflows for these NGS applications. 

The following links provide more information on specific topics:
Primer on sequencing technologies
Measuring gene expression with RNA-seq
Best practices in gene expression analysis
Analysis of RNA processing / alternative splicing
Identification of Protein-RNA interactions
Mapping the epigenome
Single cell genomics
Computational challenges in single cell genomics
Making a case for using spike-in controls

Single cell genomics
Recent advances in genomics allows the analysis of single cells by next generation sequencing [4]. Different technologies have been established: Droplet based sequencing separates individual cells in droplets (using microfluidics devices) with beads containing the chemistry to create the sequencing libraries (e.g. 10X Genomics Chromium, 10X Genomics, Pleasanton, CA or DropSeq [4]). Other approaches isolate single cells into individual wells of a multi-well plate and then the sequencing libraries are generated (e.g. SMART-Seq2 [5]). The protocols for single cell RNA-Seq differ in how the sequencing libraries are created: 10x Chromium and DropSeq libraries contain fragments of the 5 prime regions of the transcripts, SMART-Seq2 libraries contain fragments covering the full length of the transcripts. Beside RNA-Seq, single cell ATAC-Seq (e.g. Chromium Next GEM ATAC, 10X Genomics, Pleasanton, CA) interrogates open chromatin regions.

[2] Karl V. Voelkerding; Shale A. Dames & Jacob D. Durtschi (2009). "Next-Generation Sequencing: From Basic Research to Diagnostics". Clinical Chemistry. 55 (4): 641–658. doi:10.1373/clinchem.2008.112789. PMID 19246620.
[4] Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, et al. Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets. Cell. 2015;161:1202–14.
[5] Picelli S, Björklund ÅK, Faridani OR, Sagasser S, Winberg G, Sandberg R. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods. 2013;10:1096–8.