Background

I am an MRC Career Development Award research fellow (as of Oct 2018; grant title "Methods to improve genetic understanding of cardiometabolic traits through multiple traits and diverse population studies") and joined the MRC Biostatistics Unit in October 2016. Previously, I held an MRC Methodology Research fellowship (now known as MRC Skills Development Fellowship) in the Metabolic Disease group at the Wellcome Sanger institute. I have a PhD in Statistics from Western University, Canada.  

Research Interests

My interests include the development of statistical methods that could improve our genetic understanding of cardiometabolic diseases, as well co-morbidities with them. This involves approaches to jointly analyse multiple diseases/traits, as well as cross-ancestry approaches. Software for all methods from my group are available at my GitHub page. They are made to be user-friendly and my group is increasingly involved in data visualisation tools to help in interpretation of the results. I am involved in several projects that contribute to our understanding of cardiovascular disease, type 2 diabetes, and hypertrophic cardiomyopathy, with researchers from the UK and Africa.     ORCID: 0000-0002-4857-2249 Twitter:  https://twitter.com/JennAsimit

Current Group Members:

Research Associates:      

• Feng Zhou
• Siru Wang

 

Past Group Members:

• Research Associates: Nicolás Hernández

• Interns: Benjamin Pitter-Fagan

   

Selected Papers

• F Zhou, O Soremekun, T Chikowore, S Fatumo, I Barroso, AP Morris, JL Asimit. (2023). Leveraging information between multiple population groups and traits improves fine-mapping resolution. Nature Communications 14, 7279
• AB Kamiza, SM Touré, F Zhou, O Soremekun, C Cissé, M Wélé, AM Touré, O Nashiru, M Corpas, M Nyirenda, A Crampin, J Shaffer, S Doumbia, E Zeggini, AP Morris, JL Asimit, T Chikowore, S Fatumo. (2023). Multi-trait discovery and fine-mapping of lipid loci in 125,000 individuals of African ancestry. Nature Communications 14, 5403
• F Zhou, AS Butterworth, JL Asimit. (2022). flashfm-ivis: interactive visualisation for fine-mapping of multiple quantitative traits. Bioinformatics. btac453.
• N Hernandez, J Soenksen, P Newcombe, M Sandhu, I Barroso, C Wallace, JL Asimit. (2021). The flashfm approach for fine-mapping multiple quantitative traits. Nature Communications 12, 6147.
• A Hutchinson, J Asimit, C Wallace. (2020). Fine-mapping genetic associations. Human Molecular Genetics 29(R1), R81–R88.
• JL Asimit, DB Rainbow, MD Fortune, NF Grinberg, LS Wicker, C Wallace. (2019). Stochastic search and joint fine-mapping increases accuracy and identifies previously unreported associations in immune-mediated diseases. Nature Communications 10 (1), 3216.
• Y Xue, M Mezzavilla, M Haber, S McCarthy, Y Chen, VNarasimhan, A Gilly, Q Ayub, V Colonna, L Southam, C Finan, A Massala, H Chheda, P Palta, G Ritchie, J Asimit, G Dedoussis, P Gasparini, A Palotie, S Ripatti, N Soranzo, D Toniolo, FL Wilson, R Durbin, C Tyler-Smith, E Zeggini. (2017). Enrichment of low-frequency functional variants revealed by whole-genome sequencing of multiple isolated European populations. Nature Communications, 8, 15927.
• JL Asimit, F Payne, AP Morris, HJ Cordell, I Barroso (2017). A two-stage inter-rater approach for enrichment testing of variants associated with multiple traits, European Journal of Human Genetics,25, 341–349.
• M Horikoshi, L Pasquali, S Wiltshire, JR Huyghe, A Mahajan, JL Asimit, T Ferreira, AE Locke, NR Robertson, X Wang, X Sim, H Fujita, K Hara, R Young, W Zhang, S Choi, H Chen, I Kaur, F Takeuchi, P Fontanillas, D Thuillier, L Yengo, JE Below, CHT Tam, Y Wu, T2D-GENES Consortium, Goncalo Abecasis, D Altshuler, GI Bell, J Blangero, NP Burtt, R Duggirala, JC Florez, CL Hanis, M Seielstad, G Atzmon, JCN Chan, RCW Ma, P Froguel, JG Wilson, D Bharadwaj, J Dupuis, JB Meigs, YS Cho, T Park, JS Kooner, JC Chambers, D Saleheen, T Kadowaki, ES Tai, KL Mohlke, N J Cox, J Ferrer, E Zeggini, N Kato, YY Teo, M Boehnke, MI McCarthy, and AP Morris (2016). Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms. Human Molecular Genetics.
• JL Asimit, K Hatzikotoulas, M McCarthy, AP Morris, E Zeggini (2016). Trans-ethnic study design approaches for fine-mapping, European Journal of Human Genetics. 24, 1330–1336.
• JL Asimit, K Panoutsopoulou, E Wheeler, SI Berndt, the GIANT consortium, the arcOGEN consortium, HJ Cordell, AP Morris, E Zeggini, I Barroso (2015). A Bayesian approach to the overlap analysis of epidemiologically linked traits, Genetic Epidemiology, 39, 624-634.
• D Gurdasani, T Carstensen, F Tekola-Ayele, L Pagani, I Tachmazidou, K Hatzikotoulas, S Karthikeyan, L Iles, A Choudhury, GRS Ritchie, Y Xue, JL Asimit, RN Nsubuga, EH Young, C Pomilla, K Kivinen, K Rockett, A Kamali, AP Doumatey, G Asiki, J Seeley, F Sisay-Joof, M Jallow, S Tollman, E Mekonnen, R Ekong, T Oljira, N Bradman, K Bojang, M Ramsay, A Adeyemo, E Bekele, A Motala, S Norri, F Pirie, P Kaleebu, D Kwiatkowski, C Tyler-Smith, C Rotimi, MS Sandhu, E Zeggini (2015). The African Genome Variation Project shapes medical genetics in Africa, Nature, 517, 327—332.
• R Magi, JL Asimit, AG Day-Williams, E Zeggini and AP Morris. (2012). Genome-wide association analysis of imputed rare variants: application to seven common complex diseases, Genetic Epidemiology, 36, 785—796.
• JL Asimit, AG Day-Williams, AP Morris and E Zeggini (2012). ARIEL and AMELIA: Testing for an accumulation of rare variants using next-generation sequencing data, Human Heredity, 73, 84—94.
• JL Asimit, AG Day-Williams, L Zgaga, I Rudan, V Boraska and E Zeggini (2012). An evaluation of different meta-analysis approaches in the presence of allelic heterogeneity, European Journal of Human Genetics, 20, 709—712.
• MC Lopes, C Joyce, GRS Ritchie, SL John, F Cunningham, JL Asimit, and E Zeggini (2012). A combined functional annotation score for non-synonymous variants, Human Heredity, 73, 47—51.
• JL Asimit, IL. Andrulis, and SB Bull (2011). Regression models, scan statistics and reappearance probabilities to detect regions of association between gene expression and copy number, Statistics in Medicine, 30, 1157—1178.

Refereed Book Chapter

• JL Asimit and AP Morris (2015). Collapsing approaches for the association analysis of rare variants, In Assessing rare variation in complex traits: Design and analysis of genetic studies, Springer-Verlag, New York, 135-148.

Software Development

1. MGflashfm (Multi-Group FLexible And SHared information Fine-Mapping)
2. flashfmZoom (a tool for joint fine-mapping and exploration of GWAS results in the UK Biobank)
3. flashfm-ivis (FLexible And SHared information Fine-Mapping - Interactive VISualisation)
4. Flashfm (FLexible And SHared information Fine-Mapping)
5. MFM (Multinomial Fine-mapping)
6. COMET (Corrected Overlap and Marginal Enrichment Test)
7. BOAT (Bayesian Overlap Analysis Tool)
8. ARIEL (Accumulation of Rare variants Integrated and Extended Locus-specific test)
9. AMELIA (Allele Matching Empirical Locus-specific Integrated Association test)