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Manuel Rivas

DPhil student

Research overview

I am currently a DPhil student working under the supervision of Professors Mark McCarthy and Peter Donnelly. I am based at the Wellcome Trust Centre for Human Genetics in the University of Oxford.

I am interested in the genetics of complex traits, including common diseases and related physiological measurements. 

My primary focus, at the moment, is on studying the functional consequences of protein truncating variants and their contribution to disease susceptibility and trait variation. Due to technological limitations, to date, the scientific community has focused on animal models to study the phenotypic changes caused by knocking down or knocking out a gene. This approach has severe deficiencies: first, and most important, is that the animal models commonly used are not truly representative of humans. With advances in sequencing technologies we can now begin to explore the changes caused by knocking down or knocking out a gene in humans. By identifying individuals that carry protein truncating variants (in the gene of interest) and linking this information with physiological phenotypes we can now begin to establish whether loss-of-function of a gene is harmful or beneficial to an individual.

Identifying protective (beneficial) protein truncating variants, in particular, have strong translational promise as they provide examples of genes where chemical inhibition may likely be safe and effective (e.g. PCSK9). However, even in this simple setting (studying protein truncating variants) many challenges arise. My research has focused on tackling these challenges, proposing alternate study designs, developing statistical methods for assessing association, and developing approaches for interpreting the transcriptional consequences of these DNA sequence variants.

I am currently developing statistical methods and computational software for the analysis and interpretation of genomic sequencing data, including:

  • MAMBA - (main developer) a program for analyzing DNA and RNA sequencing data, enabling tissue-specific isoform variant annotation, characterizing power for alternate study designs, and incorporation of statistical methods for cross-phenotype and cross-disorder rare variant association studies from population biobank sample collections;
  • PLINK/SEQ - (core developer) a toolset for working with human genetic variation data;
  • Genebook - (core developer) a platform for making results and data readily available upon publication;
  • Syzygy - (main developer) a program for variant calling in pooled sample setting.


Clarendon Scholarship Fund, Nuffield Department of Clinical Medicine Studentship Award, Green Templeton College Award

Selected publications

An up-to-date list of publications can be found in my Google Scholar profile here.

  1. Davis J McCarthy, Peter Humburg, Alexander Kanapin, Manuel A Rivas, Kyle Gaulton, Jean-Baptiste Cazier, Peter Donnelly, WGS500 Consortium. 2014. Choice of transcripts and software has a large effect on variant annotationGenome Medicine. [pdf
  2. LA Lange et al. 2014. Whole-Exome Sequencing Identifies Rare and Low-Frequency Coding Variants Associated with LDL CholesterolThe American Journal of Human Genetics 94 (2), 233-245. PMID: 24507775
  3. Manuel A. Rivas et al. 2013. Assessing association between protein truncating variants and quantitative traitsBioinformatics 29 (19), 2419-2426. PMID: 23860716
  4. Lappalainen T, Sammeth M*, Friedländer MR*, 't Hoen PA*, Monlong J*, Rivas MA*, et al. 2013. Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501(7468):506-11. PMID: 24037378
  5. M Beaudoin, P Goyette, G Boucher, KS Lo, MA Rivas, et al. 2013 Deep resequencing of GWAS loci identifies rare variants in CARD9, IL23R and RNF186 that are associated with ulcerative colitis. PLoS Genetics (9):e1003723. PMID: 24068945
  6. GM Clarke, MA Rivas, AP Morris. 2013 A Flexible Approach for the Analysis of Rare Variants Allowing for a Mixture of Effects on Binary or Quantitative TraitsPLoS Genetics 9 (8), e1003694. PMID: 23966874
  7. E Ruark, et al. 2013. Mosaic PPM1D mutations are associated with predisposition to breast and ovarian cancer. Nature 493 (7432):406-10. PMID: 23242139
  8. MA Rivas, et al. 2011 Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel diseaseNature Genetics 43 (11), 1066-1073. PMID: 21983784
  9. Neale BM*, Rivas MA*, et al. 2011. Testing for an unusual distribution of rare variantsPLoS Genetics  7 (3), e1001322. PMID: 21408211
  10. DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, Philippakis AA, del Angel G, Rivas MA, et al. 2011. A framework for variation discovery and genotyping using next-generation DNA sequencing dataNature Genetics 43(5):491-8. PMID: 21478889
  11. 1000 Genomes Project Consortium. 2010. A map of human genome variation from population-scale sequencing. Nature 467 (7319), 1061-1073. PMID: 2098109