High throughput sequencing data analysis

In the last few years a range of new technologies have made large scale sequencing of genomes both fast and cost-efficient. At the bioinformatics core facility we are following the development of the analytical methods for handling the enormous datasets that result from high-throughput sequencing (HTS). We provide with a range of services related to HTS.

Typical input: A raw datafile recieved from a sequencer. 

Types of analysis:

• SNP, Indel, and gene variant discovery using whole genome, exome and targeted sequencing. The output is a list of interesting gene variants supplied with rich annotation.
• Mapping reads to a reference genome
• Assembling a genome and generating a consensus sequence based on de Novo sequencing
• Gene expression analysis including differential expression as well as SNP, Indel, and gene variant discovery from RNA sequencing data
• Detecting and characterizing miRNAs or other short RNAs from HTS data
• Finding protein-DNA contact points from ChIP-Seq data
• Analysis of DNA methylation from bisulfite sequencing
• Finding the number of operational taxonomic units (OTUs), creating phylogenetic trees and assigning species, genus or family information from metagenomic studies of short read data.
• General help with software, pipelines and algorithms related to HTS data