Personal profile

Research interests

I currently work on developing software currently called "SparsePainter" for efficient chromosome painting.

My research mainly focuses on applying statistical methods to population genetics.

I have developed a C++ software for efficient local ancestry inference, which is freely available from GitHub:

SparsePainter

I have also developed two R packages which are available from GitHub:

LDAandLDAS: Linkage Disequilibrium of Ancestry (LDA) and LDA Score (LDAS)

HTRX: Haplotype Trend Regression with eXtra Flexibility

Talks and Posters:

Sparse haplotype-based fine-scale local ancestry inference at scale reveals recent selection on immune responses, Probabilistic Modeling in Genomics 2024, April 2024

SparsePainter: an efficient fine-scale chromosome painting software, Chromosome painting conference, August 2023

Using ancient DNA to understand Multiple Sclerosis, Statistics discussion group, MRC IEU, University of Bristol, April 2022.

Using ancient DNA to understand Multiple Sclerosis, Research Students' Conference in Population Genetics, University of Warwick, June 2022.

HTRX: Haplotype Trend Regression with eXtra flexibility for learning SNPs and non-contiguous haplotypes associated with a phenotype. IEU monthly meeting, University of Bristol, November 2022.

Papers:

Barrie, W., Yang, Y., Irving-Pease, E.K. et al. Elevated genetic risk for multiple sclerosis emerged in steppe pastoralist populations. Nature 625, 321–328 (2024).

Yang, Y., Durbin, R., Iversen, A.K.N & Lawson, D.J. Sparse haplotype-based fine-scale local ancestry inference at scale reveals recent selection on immune responses. medRxiv (2024) doi: 10.1101/2024.03.13.24304206.

Yang, Y. & Lawson, D.J. HTRX: an R package for learning non-contiguous haplotypes associated with a phenotype. Bioinformatics Advances 3.1, vbad038 (2023).

 

Education/Academic qualification

MSc Statistics (Medical Statistics), University College London

21 Sept 202020 Sept 2021

Award Date: 20 Sept 2021

BSc Mathematics and Applied Mathematics, Beijing University of Chemical Technology

25 Aug 201615 Jun 2020

Award Date: 15 Jun 2020

Keywords

  • Population genetics
  • Biostatistics
  • Association Study
  • Statistics
  • Machine Learning
  • R packages

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Collaborations and top research areas from the last five years

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  • Elevated genetic risk for multiple sclerosis emerged in steppe pastoralist populations

    Barrie, W., Yang, Y., Irving-Pease, E. K., Attfield, K. E., Scorrano, G., Jensen, L. T., Armen, A. P., Dimopoulos, E. A., Stern, A., Refoyo-Martinez, A., Pearson, A., Ramsøe, A., Gaunitz, C., Demeter, F., Jørkov, M. L. S., Møller, S. B., Springborg, B., Klassen, L., Hyldgård, I. M. & Wickmann, N. & 11 others, Vinner, L., Korneliussen, T. S., Allentoft, M. E., Sikora, M., Kristiansen, K., Rodriguez, S., Nielsen, R., Iversen, A. K. N., Lawson, D. J., Fugger, L. & Willerslev, E., 10 Jan 2024, In: Nature. 625, 7994, p. 321-328 8 p.

    Research output: Contribution to journalArticle (Academic Journal)peer-review

    Open Access
    25 Citations (Scopus)
  • HTRX: an R package for learning non-contiguous haplotypes associated with a phenotype

    Yang, Y. & Lawson, D. J., 23 Mar 2023, (E-pub ahead of print) In: Bioinformatics Advances. 3, 1, vbad038.

    Research output: Contribution to journalArticle (Academic Journal)peer-review

    Open Access
    39 Citations (Scopus)