Inheritance Model testing Andrew Stubbs Dept. Bioinformatics

NGS Protocol Overview

GATK NGS Protocol Overview

Overview of Inheritance Models

Phasing by Transmission

Phasing a VCF file by Transmission

[Clinical]-Annotation

Clinical Significance

GEMINI (GEnome MINIng)

What is GEMINI

GEMINI Framework

Pedigree format

VCF representation of genotypes ZygosityVCF representation Heterozygous0/1; 1/2; 0/2; etc. Homozygous Reference Alternate 0/0; 1/1; 2/2; etc. 0/0 1/1; 2/2; 3/3; etc. Missing./0;./1;./.; etc.

Pre-GEMINI processing: Normalise VCF

Pre-GEMINI processing: Erasmus Galaxy VCF VEP Annotation

Pre-GEMINI processing: VCF Annotation

GEMINI Phasing by Transmission

GEMINI workflow

GEMINI Automated tools for disease inheritance models

GEMINI in our Galaxy

Data Sets VCF: trio.trim.vep.vcf.gz : column names: trio.trim.names.txt Ped: Maternal: mat.dominant.ped BAM: Maternal:1805.BAM.sorted.bam : Paternal:1847.BAM.sorted.bam : Proband:4805.BAM.sorted.bam Notes: 1.The VCF has been normalized and decomposed with VT 2.The VCF has been annotated with VEP.

Practical #1: Autosomal Dominant

1.Upload:trio.trim.vep.vcf.gz - 17,237 lines, 123 comments, format vcf, database hg19 mat.dominant.ped 2.Search for gemini autosomal. – Select dominant model – Use gemini database – Use default paramaters

Practical #1: Autosomal Dominant 1.Create new history mat.dom.ped 2.Upload: trio.trim.vep.vcf.gz & mat.dominant.ped

Practical #1: Autosomal Dominant Load database: VCF (VEP annotated format) & ped file Rename database : gemini_mat.dom.db

Practical #1: Autosomal Dominant Search for autosomal dominant and run model on database HOW MANY VARIANTS ARE DETECTED?

Practical #1: Autosomal Dominant 1.Filtering and sort: Filter – High severity : c71 == ‘HIGH’ – aaf_esp_ea : c95 <= 0.01 – aaf_exac_all : c127 <= 0.01

Practical #1: Autosomal Dominant

High severity : c71 == ‘HIGH’ aaf_esp_ea : c95 <= 0.01 aaf_exac_all : c127 <= 0.01

Practical #1: Autosomal Dominant 1.Generate output Column Select – Chrom, Start, End – Ref, Alt – gene, impact – gts, gt_depths 2.output

Practical #1: Autosomal Dominant 1.Filtering and sort: Filter – Maternal Dominant inheritance: 1,514 variants – High severity: c71 == ‘HIGH’ : 15 variants – aaf_esp_ea : c95 <= 0.01: 7 variants – aaf_exac_all : c127 <= 0.01: 4 variants 2.Column Select

Practical #1: Autosomal Dominant 1.Variant visualisation – Create new history – Get Data: Load files from disk: 3 BAM files

Practical #1: Autosomal Dominant 1.Variant visualisation – Create trackster visual  add other bam files

Practical #1: Autosomal Dominant 1.Variant visualisation – Check variants 1847 paternal 1805 maternal 4805 proband

Practical #2: Autosomal Dominant 1.Create ped file for PATERNAL DOMINANT 2.Re-run Analysis for PATERNAL DOMINANT 3.What is the outcome? 4.Are any of these variants known to underlie a clinical phenotype in either Maternal of Paternal dominant inheritance model? We will review the results together ….

Practical #3: Autosomal Dominant

Command -q SELECT chrom, start, end, ref, alt, gene, impact, (gts).(*), (gt_depths).(*) FROM variants WHERE filter is NULL and impact_severity == 'HIGH‘ and (aaf_esp_ea <= 0.01 or aaf_esp_ea is NULL) and (aaf_exac_all <= 0.01 or aaf_exac_all is NULL) --header --gt-filter (gt_types).(phenotype==2).(==HET).(all) and (gt_types).(phenotype==1).(==HOM_REF).(all) and (gt_depths).(*).(>=20).(all)

Practical #3: Autosomal Dominant Use the gemini query tool to select maternal dominant inheritance. Is there a difference with your results in Practical # 1