Gamma-SMC is an ultra-fast method to infer the pairwise coalesence times between a set of haplotypes in a large dataset. This inference is used in reconstructing demographic histories, detecting selection signatures, studying genome-wide associations, constructing ancestral recombination graphs, and more. Gamma-SMC is more than 10 times faster than current methods (0.14 seconds for a whole genome).
[github] [paper]
FactorialHMM is a Python package for fast exact inference in Factorial Hidden Markov Models, where the hidden state is the Cartesian product of multiple processes, each evolving independently (e.g. along the genome).
[github] [paper]
FEATHER (Fast pErmutAtion Testing of HERitability) is a method for fast permutation-based testing of marker sets and of heritability. FEATHER is free of parametric and asymptotic assumptions, and is thus guaranteed to properly control for false positive results. Since standard permutation testing is computationally prohibitive, FEATHER combines several novel techniques to obtain speedups of up to eight orders of magnitude.
[github] [paper]
RL-SKAT is a method for the calculation of exact p-values for the score test in heritability, in the case of a single kernel and a continuous phenotype.
[github] [paper]
FIESTA (Fast confidence IntErvals using STochastic Approximation) is a method for the construction of accurate confidence intervals (CIs) for heritability. FIESTA can be used as an add-on to existing methods for heritability and variance components estimation.
[github] [paper]
ALBI (Accurate LMM-based heritability Bootstrap confidence Intervals) is a method for the estimation of the distribution of the heritability estimator, and for the construction of accurate confidence intervals (CIs).
[github] [paper]