Andrii Iakovliev

@whimsial

@Helen Colhoun group

@Genoscores team

@molepi-precmed group

Post-doctoral Research Associate. Centre for Population Health Sciences and Informatics at University of Edinburgh, UK

PhD in Computer Science at the University of Southampton, UK

Research interests

I carry out research in genetic epidemiology and precision medicine with focus on autoimmune and infectious diseases.

Genetic susceptibility to a disease is typically determined by tiny effects from thousands of sites on the genome at which people differ from each other. I am developing new methods of genetic analysis, based on adding up the effects of all these variant sites on each gene to identify the core genes that cause disease.

Projects

My research projects/code repositories.

Genomewide aggregation of trans- effects (GATE) method

GATE computational pipeline

Description

The method is based on the Omnigenic model (Boyle et al., 2017) and can be applied to detect effector (core) genes mediating the disease. The pipeline makes use of the GENOSCORES platform to compute eQTL and pQTL scores and aggregate the trans QTL effects into genomewide scores which are then tested for association with the disease.

Work is supported by UK/Canada Collaboration on the genetics of long-term diabetes complications.

R Shell

GENOSCORES platform

GENOSCORES website

Description

I am a lead developer and maintainer of the GENOSCORES code base, server and database.

GENOSCORES consists of:

curated database of published GWAS summary statistics
web platform
R package
suite of software tools
REST API

GENOSCORES is used with any individual-level dataset consisting of genome-wide SNP genotypes to calculate genotypic scores for the intermediate phenotypes stored in the database.

Work is supported by The Academy of Medical Sciences Springboard award

R PHP HTML Shell SQL

Prediction of treatment response using gene expression data for genes predictive of synovial pathotypes in people with rheumatoid arthritis.

Description

I train predictive models with hierarchical shrinkage priors using hsstan package to predict treatment response using panels of biomarkers predictive of synovial pathotypes in RA.

This is a collaborative project within TRACT-RA collaboration.

Discovery of genetically predicted biomarkers mediating systemic lupus.

Description

I use GENOSCORES and GATE method to detect effector (core) genes mediating systemic lupus.

This is a collaboration with Centro Pfizer – Universidad de Granada – Junta de Andalucía de Genómica e Investigación Oncológica GENYO.

Spindle FEA

I developed an application to perform parametric modelling of elastic stability of the mitotic spindle in several cell types during mitosis. This work was carried out as part of my PhD.

Python SpindleFEA repo