I contribute to open-source software that makes statistical methodology for single-cell and high-dimensional biological data accessible and reproducible.
Current software
knit
Python · Kernel Normalised Independence Test
Method for kernel-based statistical testing of independence between distributions.
ktest + kAov
R / Python · Kernel hypothesis testing
Tools for kernel-based statistical testing of high-dimensional and single-cell data.
nucount
Python · Spatial transcriptomics · Cell-number estimation
Methods for estimating absolute cell numbers in spatial transcriptomics spots from histological images.
pppca
R · Point processes · PCA
Principal component analysis methods for replicated point-process data.
Previous software
Previous software contributions include pCMF, plsgenomics, SEX-DETector, curvclust, cghseg, geoclust, and methods for functional Poisson regression and genomic peak detection. These projects reflect my broader work in statistical genomics and computational biology.