| Package Name | Access | Summary | Updated |
|---|---|---|---|
| sphinxygen | public | A script to generate Sphinx ReST from Doxygen XML | 2025-04-25 |
| htseq | public | HTSeq is a Python library to facilitate processing and analysis of data from high-throughput sequencing (HTS) experiments. | 2025-04-23 |
| nvidia-dlfw-inspect | public | No Summary | 2025-04-23 |
| rsjsonnet | public | A Rust implementation of the Jsonnet language | 2025-04-23 |
| transformer-engine-pytorch | public | No Summary | 2025-04-23 |
| megatron-lm | public | Megatron Core - a library for efficient and scalable training of transformer based models | 2025-04-22 |
| nemo-toolkit | public | NeMo - a toolkit for Conversational AI | 2025-04-22 |
| pytest-random-order | public | Randomise the order in which pytest tests are run with some control over the randomness | 2025-04-22 |
| pywfa | public | A python wrapper for wavefront alignment using WFA2-lib | 2025-04-22 |
| torch-sparse-gpu | public | PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations | 2025-04-22 |
| torch-scatter-gpu | public | PyTorch Extension Library of Optimized Scatter Operations | 2025-04-22 |
| torch-cluster-gpu | public | PyTorch Extension Library of Optimized Graph Cluster Algorithms | 2025-04-22 |
| torch-sparse | public | PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations | 2025-04-22 |
| torch-scatter | public | PyTorch Extension Library of Optimized Scatter Operations | 2025-04-22 |
| watershed-sv | public | Watershed-SV extends Watershed to model the impact of rare SVs | 2025-04-17 |
| gn | public | GN is a meta-build system that generates build files for Ninja. | 2025-04-17 |
| bioconductor-rbgl | public | An interface to the BOOST graph library | 2025-04-11 |
| bioconductor-graph | public | 'graph: A package to handle graph data structures' | 2025-04-11 |
| rpy2 | public | Python interface to the R language (embedded R) | 2025-04-09 |
| activate-virtualenv | public | No Summary | 2025-04-08 |
| virtualenvwrapper | public | No Summary | 2025-04-08 |
| 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 |
| 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 |
| bioconductor-seqarray | public | Data Management of Large-Scale Whole-Genome Sequence Variant Calls | 2025-04-08 |
| bioconductor-snprelate | public | Parallel Computing Toolset for Relatedness and Principal Component Analysis of SNP Data | 2025-04-08 |
