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pytest-random-order
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public |
Randomise the order in which pytest tests are run with some control over the randomness
|
2025-04-22 |
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pywfa
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public |
A python wrapper for wavefront alignment using WFA2-lib
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2025-04-22 |
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torch-sparse-gpu
|
public |
PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations
|
2025-04-22 |
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torch-scatter-gpu
|
public |
PyTorch Extension Library of Optimized Scatter Operations
|
2025-04-22 |
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yabai
|
public |
A tiling window manager for macOS based on binary space partitioning
|
2025-04-22 |
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torch-cluster-gpu
|
public |
PyTorch Extension Library of Optimized Graph Cluster Algorithms
|
2025-04-22 |
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torch-sparse
|
public |
PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations
|
2025-04-22 |
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torch-scatter
|
public |
PyTorch Extension Library of Optimized Scatter Operations
|
2025-04-22 |
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watershed-sv
|
public |
Watershed-SV extends Watershed to model the impact of rare SVs
|
2025-04-17 |
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gn
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public |
GN is a meta-build system that generates build files for Ninja.
|
2025-04-17 |
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r-mr.ash.alpha
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public |
Implements variational empirical Bayes methods for linear
regression. Coordinate-wise optimization algorithms for model fitting
are implemented in C++ for efficient handling of large-scale data
sets.
|
2025-04-17 |
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bioconductor-s4vectors
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public |
Foundation of vector-like and list-like containers in Bioconductor
|
2025-04-11 |
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bioconductor-rbgl
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public |
An interface to the BOOST graph library
|
2025-04-11 |
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bioconductor-graph
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public |
'graph: A package to handle graph data structures'
|
2025-04-11 |
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rpy2
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public |
Python interface to the R language (embedded R)
|
2025-04-09 |
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activate-virtualenv
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public |
No Summary
|
2025-04-08 |
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virtualenvwrapper
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public |
No Summary
|
2025-04-08 |
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r-gmmat
|
public |
Perform association tests using generalized linear mixed models (GLMMs) in genome-wide association studies (GWAS) and sequencing association studies. First, GMMAT fits a GLMM with covariate adjustment and random effects to account for population structure and familial or cryptic relatedness. For GWAS, GMMAT performs score tests for each genetic variant as proposed in Chen et al. (2016) <doi:10.1016/j.ajhg.2016.02.012>. For candidate gene studies, GMMAT can also perform Wald tests to get the effect size estimate for each genetic variant. For rare variant analysis from sequencing association studies, GMMAT performs the variant Set Mixed Model Association Tests (SMMAT) as proposed in Chen et al. (2019) <doi:10.1016/j.ajhg.2018.12.012>, including the burden test, the sequence kernel association test (SKAT), SKAT-O and an efficient hybrid test of the burden test and SKAT, based on user-defined variant sets.
|
2025-04-08 |
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bioconductor-genesis
|
public |
GENetic EStimation and Inference in Structured samples (GENESIS): Statistical methods for analyzing genetic data from samples with population structure and/or relatedness
|
2025-04-08 |
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bioconductor-seqarray
|
public |
Data Management of Large-Scale Whole-Genome Sequence Variant Calls
|
2025-04-08 |
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bioconductor-snprelate
|
public |
Parallel Computing Toolset for Relatedness and Principal Component Analysis of SNP Data
|
2025-04-08 |
|
bioconductor-gdsfmt
|
public |
R Interface to CoreArray Genomic Data Structure (GDS) Files
|
2025-04-08 |
|
bioconductor-cytolib
|
public |
C++ infrastructure for representing and interacting with the gated cytometry data
|
2025-04-08 |
|
quantas
|
public |
Tools for inference of gene transcript structure and quantification of gene expression and alternate splicing
|
2025-04-08 |
|
torch-spline-conv-gpu
|
public |
Implementation of the Spline-Based Convolution Operator of SplineCNN in PyTorch
|
2025-04-04 |
