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