Radboudumc Technology Center Bioinformatics

What is bioinformatics?

The field of bioinformatics concerns the processing and analyzing of large amounts of biological data using computational methodologies. Bioinformatics combines expertise from many scientific disciplines, like biology, mathematics, statistics, computer science and biochemistry. Bioinformatics analysis can be applied to all sorts of biodata, but the biggest source of data comes from within the cell; genetics and DNA organization, gene expression and protein structures.

How do we apply bioinformatics?

Since the completion of the human genome and introduction of high throughput sequencing, the application of bioinformatics has shifted from a purely academic venture towards more clinical use-cases. With the revolution in sequencing, more and more reliable information can be gathered from our cells. Think of investigating disease causing mutations, finding gene expression profiles that lead to cancer metastasis, or analyzing protein structures to identify drug targets.

The RNA-DxP pipeline

At the RTC Bioinformatics, we get the most support requests for RNA Sequencing analysis. In order to both serve our clients and to contribute to a data-driven heathcare, we created the RNA-DxP pipeline. With this pipeline we aim to create a RNA-Seq data analysis workflow which is robust, reproducible and scalable, while still being innovative and feature complete. RNA-DxP is suitable for both biological as biomedical research, human and model organisms. We are working together with the Radboudumc department of Genetics to make RNA-DxP available for patient diagnostics purposes. The current features are:

• Advanced QC and Metrics
• Differential Gene Expression
• Alternative and Differential Splicing
• Fusion Gene detection
• Splice Junction analysis
• Pathway & GO Enrichment
• EnrichR and String Annotation
• RNA Variant Calling and Annotation
• Automated reporting and visualizations
• Scaled for projects of any size

Our analysis services and solutions

RNA Sequencing

• Thorough and interactive visualized QC analysis
• Differential Gene Expression Analysis
• Pathway analysis and Annotation
• Single Cell data analysis
• Transcriptome analysis
• Isoform detection and Rare disease diagnostics
• Publication-grade graphics and plots

DNA Sequencing

• Single Nucleotide and Structural Variant calling and annotation
• Sequence analysis and pattern recognition
• Genome assembly, annotation and visualization
• Comparative Genomics and Phylogenetics
• Bacterial classification and Pathogen marker analysis
• Somatic/Tumor variant calling

Protein Structure analysis

• Protein homology modeling and function prediction
• 3D-analysis of mutational effects
• Analysis of structures and complexes based on 3D projections

Metagenomics

• 16S and Marker Gene classification
• Microbiome Functional annotation
• Metagenome assembly
• Comparative Microbiomics analysis

Data Science

• Ontology and Text mining
• Integration with biostatistics
• Investigating use of Machine/Deep learning
• Big data visualizations
• Data management
• Data analysis automation and upscaling