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zhiyuan-hu-lab
CIDER:Meta-Clustering for scRNA-Seq Integration and Evaluation
A workflow of (a) meta-clustering based on inter-group similarity measures and (b) a ground-truth-free test metric to assess the biological correctness of integration in real datasets. See Hu Z, Ahmed A, Yau C (2021) <doi:10.1101/2021.03.29.437525> for more details.
Maintained by Zhiyuan Hu. Last updated 2 months ago.
5.30 score
bioc
PIUMA:Phenotypes Identification Using Mapper from topological data Analysis
The PIUMA package offers a tidy pipeline of Topological Data Analysis frameworks to identify and characterize communities in high and heterogeneous dimensional data.
Maintained by Mattia Chiesa. Last updated 5 months ago.
clusteringgraphandnetworkdimensionreductionnetworkclassification
4 stars 5.08 score 2 scripts
f-rousset
spaMM:Mixed-Effect Models, with or without Spatial Random Effects
Inference based on models with or without spatially-correlated random effects, multivariate responses, or non-Gaussian random effects (e.g., Beta). Variation in residual variance (heteroscedasticity) can itself be represented by a mixed-effect model. Both classical geostatistical models (Rousset and Ferdy 2014 <doi:10.1111/ecog.00566>), and Markov random field models on irregular grids (as considered in the 'INLA' package, <https://www.r-inla.org>), can be fitted, with distinct computational procedures exploiting the sparse matrix representations for the latter case and other autoregressive models. Laplace approximations are used for likelihood or restricted likelihood. Penalized quasi-likelihood and other variants discussed in the h-likelihood literature (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) are also implemented.
Maintained by François Rousset. Last updated 10 months ago.
4.94 score 208 scripts 5 dependents