A computing tool is developed to automated identify somatic mutation-driven immune cells. The operation modes including: i) inferring the relative abundance matrix of tumor-infiltrating immune cells and integrating it with a particular gene mutation status, ii) detecting differential immune cells with respect to the gene mutation status and converting the abundance matrix of significant differential immune cell into two binary matrices (one for up-regulated and one for down-regulated), iii) identifying somatic mutation-driven immune cells by comparing the gene mutation status with each immune cell in the binary matrices across all samples, and iv) visualization of immune cell abundance of samples in different mutation status..

Allows users to easily build custom 'docker images' <https://docs.docker.com/> from
    'Amazon Web Service Sagemaker' <https://aws.amazon.com/sagemaker/> using
    'Amazon Web Service CodeBuild' <https://aws.amazon.com/codebuild/>.

The Sparse Marginal Epistasis Test is a computationally efficient 
    genetics method which detects statistical epistasis in complex traits;
    see Stamp et al. (2025, <doi:10.1101/2025.01.11.632557>) for details.

Implements statistical methods for analyzing the counts of areal data, with a focus on the detection of spatial clusters and clustering.  The package has a heavy emphasis on spatial scan methods, which were first introduced by Kulldorff and Nagarwalla (1995) <doi:10.1002/sim.4780140809> and Kulldorff (1997) <doi:10.1080/03610929708831995>.

Simple class to hold contents of a SMET file as specified in
    Bavay (2021) <https://code.wsl.ch/snow-models/meteoio/-/blob/master/doc/SMET_specifications.pdf>.
    There numerical meteorological measurements are all based on MKS (SI) units
    and timestamp is standardized to UTC time.

Provides the filtering algorithms for the state space models on the Stiefel manifold as well as the corresponding sampling algorithms for uniform, vector Langevin-Bingham and matrix Langevin-Bingham distributions on the Stiefel manifold.