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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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Computational approaches to interpreting genomic sequence variation.

Graham Rs Ritchie¹, Paul Flicek¹

¹European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD UK ; Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA UK.

Genome Medicine

|December 5, 2014

Summary

This summary is machine-generated.

Identifying disease-causing genetic variants is crucial. This review assesses computational tools for functional variant analysis, prioritizing them for research and understanding molecular mechanisms.

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Area of Science:

Human genetics
Bioinformatics
Genomic variation analysis

Background:

Identifying sequence variants linked to human disease is a key goal in genetics.
Experimental validation is the gold standard but impractical for millions of variants per genome.
Computational methods are essential for interpreting functional variation.

Purpose of the Study:

To review and assess computational techniques for categorizing functional variants.
To prioritize variants for experimental follow-up.
To generate hypotheses on molecular mechanisms of genetic variation.

Main Methods:

Review of current bioinformatics approaches for functional variant identification.
Assessment of algorithms like SIFT and PolyPhen for coding variation.
Discussion of novel techniques for genome-wide variation interpretation.

Main Results:

Computational tools offer various approaches to identify functional variants.
Limitations exist in current methods for variant categorization and prioritization.
Bioinformatics approaches aid in generating hypotheses for downstream experiments.

Conclusions:

Computational methods are vital for understanding functional variation due to experimental limitations.
Continued development of bioinformatics tools is needed for accurate variant interpretation.
These tools are crucial for translating genetic variation studies into biological insights.