The Core helps investigators build standardized workflows as well as customized, in-depth analyses with emphasis on quality control and statistical rigor.
The services listed below should give you an impression of the most commonly performed analyses - we are by no means limited to them and are happy to tackle new challenges.
We can provide extensive reports with publication-ready images as well as the analysis source code upon request. If you come across a paper with sequencing data analyses or other statistical methodology you would like to use (or think the Core should be aware of), please email it our way!
NGS Data Analysis
Genomics (WGS, WES)
- De novo assembly of eukaryotic and prokaryotic genomes
- Whole genome comparison at the genome architecture, and gene level (Evolutionary bioinformatics analysis)
- Genome functional annotation: Estimation, and analysis of repeat content, ab initio gene prediction, annotation of genes at three levels via protein domains and motifs, orthology search, and homology search
- Whole exome and whole genome analysis: variant calling, and annotation
Epigenomics (CHIP-seq, ATAC-seq)
- CHIP-seq of transcription factors, and histone modifications
- Measurements of open chromatin via ATAC-seq
- Basic analysis includes peak calling, and creation of enrichment tracks, in addition to raw data quality control, and genome alignment
- Additional analysis includes de novo motif detection, motif enrichment analysis, annotation of proximal and distal genes, and integration of peaks with expression data (from RNA-seq or microarray) for inference of regulatory effects
Transcriptomics (Arrays, RNAseq)
- Analysis of commercial and custom microarrays: differentially expressed genes, group comparison
- RNA-seq for mRNA: Gene or transcript quantification, differential analysis, and alternative splicing analysis
- Functional analysis of differentially expressed genes: Gene Ontology terms, motif analysis, and pathways enrichment analysis
- RNA-seq for small and non-coding RNA: Discovery of new microRNAs, microRNA target prediction
- Simultaneous/Dual-RNA seq time-course analysis for host-pathogen interaction studies
Other Analysis
- Single cell transcriptomics - Bioinformatics support for processing, quality control, analysis, and interpretation. Additional analysis include identifying subpopulations, differential expression, data visualization, and statistical analysis
- Metagenomics - Taxonomic identification and quantification for 16S amplicon sequencing, metagenome or metatranscriptome assembly, diversity and differential analysis
- CRISPR-Cas systems - Off target prediction in gene editing, end-end analysis of pooled CRISPR-Cas9 screens
Statistical Support
- Supervised machine learning approaches for classification purposes, and feature prediction
- Establish novel analysis pipelines using multivariate-, multiblock-, and network-based analysis for systems-level integration of -omics data across platforms
- Data visualization including heatmaps, violin plots, and other types of plots as well as custom visualizations
- Automation of analysis pipelines using Nextflow
- Literate programming using Rmarkdown