Performance Evaluation of Giraffe-DeepVariant Workflow on WES data
Variation graphs provide a succinct encoding of the sequences of many genomes.
A Pangenome is a collection of genomes from individuals in a population and is represented as a variation graph.
Giraffe is a short-read mapping algorithm that finds the walk through the pangenomic graph that best matches the read.
Read alignments from Giraffe can be passed to DeepVariant, which visualizes these into pileup images (can be 6 or 7 channels deep) , and then uses a CNN to classify the images into variant calls.
- Conversion of BAM to paired-end fastQ files.
- Attempted the GiraffeDeepVariant workflow on Terra.
- Fixed the input parameter file to succeed.
- Fetched Giraffe-PE VCF. Used it for hap.py benchmarking comparisons.
- Investigations of exclusive BWA-only variants on IGV.
- DeepVariant Model Retraining on correct paired-end exome data.
- Repeat analysis
- Evaluate performance of Giraffe on other kits, (Nextera and IDT) as well as the general ref-seq region.