Our latest paper, based on the thesis work of former DPhil student Zhiyuan, has been published in Genome Biology. CIDER: an interpretable meta-clustering framework for single-cell RNA-seq data integration and evaluation describes a meta-clustering workflow based on inter-group similarity measures. We demonstrate that CIDER outperforms other scRNA-Seq clustering methods and integration approaches in both simulated and real datasets. Moreover, we show that CIDER can be used to assess the biological correctness of integration in real datasets, while it does not require the existence of prior cellular annotations.
Kaspar Martens will present his latest work at the NeurIPS Workshop “Learning Meaningful Representations of Life” Rarity: Discovering rare cell populations from single-cell imaging data. The work arises from his Turing-Crick Biomedical Award which supports a collaboration between the Alan Turing Institute and the Ciccarelli Group at Kings College London and the Francis Crick Institute.
Christopher Yau has supported Health Data Research UK (HDRUK) PhD students Fabian Falck and Haoting Zhang in the development of work that has now been published as a paper at the NeurIPS 2021 conference. The work entitled Multi-Facet Clustering Variational Autoencoders is a novel class of variational autoencoders with a hierarchy of latent variables, each with a Mixture-of-Gaussians prior, that learns multiple clusterings simultaneously, and is trained fully unsupervised and end-to-end. Chris, who directs the HDRUK PhD programme, writes about the work of the students in this blog.
The Columbia Hospital For Women Research Foundation have awarded Christopher Yau the prize for most impactful paper in 2020 in the field of obstetrical and gynecologic and breast disease. The prize consisted of a $5,000 to a charity of Chris and Ahmed’s choosing and they selected Ovarian Cancer Action who co-funded the original work.
Recently Christopher Yau worked with Ovarian Cancer Action UK to put together a webinar on his research for patients and the public. You can find the video on Youtube: “What is artificial intelligence and what does it mean for cancer research?”.
Congratulations to PhD student Dominic Danks whose paper BasisDeVAE: Interpretable Simultaneous Dimensionality Reduction and Feature-Level Clustering with Derivative-Based Variational Autoencoders. has been accepted for presentation at the International Conference for Machine Learning 2021.
Congratulations to PhD student Woojung Kim whose will presenting his work on “Learning multimorbidity and its temporal dynamics with the Wright-Fisher Indian Buffet Processs” at the EcoStat 2021 and the International Society for Bayesian Analysis World Meeting 2021 conferences.
Our paper “Adipocyte-like signature in ovarian cancer minimal residual disease identifies metabolic vulnerabilities of tumor-initiating cells” with the Oxford Ovarian Cancer Cell Lab has been featured on the cover of JCI Insight. The work used methods developed by former group student Kieran Campbell.