Considerations for Analyzing Targeted NGS Data Exome Tim Hague, CTO.
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Considerations for Analyzing Targeted NGS Data Exome Tim Hague, CTO Omixon Workshops Considerations for Analyzing Targeted NGS Data - Exome Tim Hague, CEO
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Transcript of Considerations for Analyzing Targeted NGS Data Exome Tim Hague, CTO.
Considerations for Analyzing Targeted NGS Data
Exome
Tim Hague, CTO
Omixon WorkshopsConsiderations for Analyzing Targeted NGS Data - ExomeTim Hague, CEO
3 sets of full exome sequences for the same individual, targeted by 3 different kits
One set had data problems because reads were from 2 different sequencers
Remaining 2 sets were analyzed both by the customer and by Omixon
Exome Analysis
Illumina TruSeq ~62 Mbp
Nimblegen SeqCap EZ Exome ~64 Mbp
~35 Mbp overlap between targets
Exons, ORFs and putative translated regions captured
40M and 37M read pairs resp., 101bp length
Exome Targets
In this case we are comparing two full NGS analysis pipelines
Including the mapping/alignment and a multi-step variant call pipeline
The Omixon pipeline for this analysis uses two variant callers
The Omixon pipeline also uses recalibration and indel realignment
Full Analysis Pipelines
Finding Long Indels 1.
Better Indel Resolution 1.
Better Indel Resolution 2.
If indels are important to an analysis then this needs to be taken into account, from the planning stage onwards
BWA does better when indel realignment is used, in combination with paired data
Indel Handling
Less Low Quality False Positives
Some of these low quality variants can be removed by filtering, after variant call
Quality and coverage cut-offs have to be parameterized properly in the alignment and variant call
Quality recalibration can also help to reduce low quality false positives
Quality and Coverage
Variations Next to Coding Areas
Most of the exon kits also provide variant calls close to the coding regions
These should be included in the analysis if possible
Splicing and Promoters
Less False Positives in Complex Regions 1.
Less False Positives in Complex Regions 2.
Less False Positives in Complex Regions 3.
Less False Positives in Complex Regions 4.Higher Coverage
Less False Positives in Complex Regions 5.Lower Coverage
Mismappings due to pseudogenes or repeats – or just complex regions?
Sometime more coverage can actually be bad
Need to watch out for non-specific read mappings (reads mapping to multiple places)
Complex Regions
Regions Where Both Aligners are Confused 1.
Regions Where Both Aligners are Confused 2.
Some regions are extremely difficult to map with any techniques
A different approach may be required to mapping/alignment
A different approach may be required to variant call (local de novo, phasing etc)
Very Complex Regions
Problems with Sex Chromosomes
There are may heterozygous calls in the X and Y chromosomes that are certainly false positives or incorrect calls.
This is true for both pipelines, the read specificity and variant call procedure has to be improved for these chromosomes.
These kinds of comparative studies can be useful in analyzing the effectiveness of exome sequencing
Different exome kits can give different results
The data analysis and variant call tools chosen for the analysis can also have a big impact
There is some potential to improve the quality of the customer's exome analysis pipeline
Summary
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