Functional Genomics in Diabetes Research

The facility provides expert competence in functional genomics technologies and associated bioinformatic data analysis.

We work in close collaboration with the Bioinformatic and Expression Analysis (BEA) core facility at Karolinska Institutet to support the use of different functional genomics analysis platforms such as microarray and high throughput DNA sequencing for various omics analysis, including genome wide DNA methylation analysis (the methylome), global gene expression analysis (the transcriptome) and global DNA-binding analysis (the cistrome), details are in the Table below.

The facility is aiming to assist SRP Diabetes researchers through the full life cycle of a project from experimental design to manuscript writing and will provide help on both the wet-Lab and the bioinformatics data analysis. It is important to emphasize that the facility will also provide bioinformatics support for projects where the assays have not been run at BEA.

Access to the facility

The facility is open to all projects within the SRP Diabetes programme. As the bioinformatics support is extensive for each project and includes scientific input and discussions throughout the work, we pursue it as scientific collaborations within SRP Diabetes.

Analysis platform Equipment or Tools Applications
High throughput sequencing platforms Illumina HiSeq2000, MiSeq and other platforms 1. Transcriptome analysis including miRNA and long noncoding RNA from cells and tissues 2. Global DNA-binding analysis 3. Global DNA-methylation analysis
Microarray platforms Affymetrix, Illumina and Agilent microarray platform 1. Transcriptome analysis including miRNA and long noncoding RNA from cells and tissues 2. Global DNA-binding analysis 3. Global DNA-methylation analysis
Bioinformatic analysis pipelines 1. A range of commercial and freely available software, such as Bioconductor R and a range of packages, SeqMonk , Qlucore, Circos and IPA. 2. Access to Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) service for storing and analysis high throughput data. 1. Statistical comparison 2. Biological networks 3. Data visualization 4. Customized support

Contact:

Hui Gao

Researcher
H2 Department of Biosciences and Nutrition