wiki:Courses/ComputationalMolecularBiologyResearch2015/P6

Increasing diagnostic yield of fast whole genome diagnostics for new borns on the Neonatal Intensive Care Unit (NICU)

Supervisors

Juha Karjalainen and Joeri van der Velde

Introduction

Next Generation Sequencing (NGS) has become a very important tool for geneticists. At the UMCG we recently enrolled in project "5 Genes per Minute (5GpM)" to move this high throughput technology from the research department into the clinic. In 5 GpM we aim to diagnose genetic disease in severely affected new borns on our Neonatal Intensive Care Unit (NICU) by means of whole genome screening. 5 Genes per Minute analysis can be requested for patients when all classic diagnostics failed and speed is essential. We aim for from blood sample to diagnosis in < 48 hours.

Our current bioinformatics analysis only considers single nucleotide variants (SNVs) and short insertion/deletions (InDels). So far we have analysed 10 patients and managed to pin point the causal genetic variant in one. There may be various reasons why we have no diagnosis in the other 9:

  • The symptoms are not caused by a genetic disease: something else is going on.
  • The genetic variant is part of a region that cannot be reliably sequenced.
  • The genetic variant was sequenced, but is not yet called by our bioinformatics pipeline.
  • The genetic variant was sequenced and called, but we cannot interpret the effect of the variant correctly.

Variant interpretation is a major challenge in diagnostics.

Projects 6 - Improved variant interpretation

In this student research project we aim to find which genes in certain patients could cause their disease or phenotype. For some patients, we know which variants they have but we don't know which of these variants are important.

The student will investigate gene function predictions for genes in which these unresolved variants are. We have predicted functions comprehensively for nearly all human genes so perhaps you will find previously unknown interesting genes that explain the phenotype(s) of the patient!

The work can be done using Excel or R. In later weeks, we can make part of the process automatic with R or any programming language.

Last modified 9 years ago Last modified on 2015-02-04T17:17:15+01:00