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r-ggalign
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public |
A 'ggplot2' extension providing an integrative framework for composable visualization, enabling the creation of complex multi-plot layouts such as insets, circular arrangements, and multi-panel compositions. Built on the grammar of graphics, it offers tools to align, stack, and nest plots, simplifying the construction of richly annotated figures for high-dimensional data contexts—such as genomics, transcriptomics, and microbiome studies—by making it easy to link related plots, overlay clustering results, or highlight shared patterns.
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2025-09-28 |
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nodejs
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public |
a platform for easily building fast, scalable network applications
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2025-09-28 |
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r-hardyweinberg
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public |
Contains tools for exploring Hardy-Weinberg equilibrium (Hardy, 1908; Weinberg, 1908) <doi:10.1126/science.28.706.49> for bi and multi-allelic genetic marker data. All classical tests (chi-square, exact, likelihood-ratio and permutation tests) with bi-allelic variants are included in the package, as well as functions for power computation and for the simulation of marker data under equilibrium and disequilibrium. Routines for dealing with markers on the X-chromosome are included (Graffelman & Weir, 2016) <doi: 10.1038/hdy.2016.20>, including Bayesian procedures. Some exact and permutation procedures also work with multi-allelic variants. Special test procedures that jointly address Hardy-Weinberg equilibrium and equality of allele frequencies in both sexes are supplied, for the bi and multi-allelic case. Functions for testing equilibrium in the presence of missing data by using multiple imputation are also provided. Implements several graphics for exploring the equilibrium status of a large set of bi-allelic markers: ternary plots with acceptance regions, log-ratio plots and Q-Q plots.
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2025-09-28 |
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checkstyle
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public |
Checkstyle is a development tool to help programmers write Java code that adheres to a coding standard
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2025-09-28 |
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lint-staged
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public |
Run linters on git staged files
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2025-09-28 |
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qcarchivetesting
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public |
Additional testing fixtures and functions for the QCArchive project
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2025-09-28 |
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qcportal
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public |
Python library for interacting with QCArchive/QCFractal servers
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2025-09-28 |
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qcfractal
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public |
Database and Web API for the QCArchive project
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2025-09-28 |
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qcfractalcompute
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public |
Distributed worker package for QCArchive
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2025-09-28 |
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psqlodbc
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public |
psqlODBC is the official PostgreSQL ODBC Driver
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2025-09-28 |
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blackdoc
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public |
run black on documentation code snippets
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2025-09-28 |
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r-treedist
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public |
Implements measures of tree similarity, including information-based generalized Robinson-Foulds distances (Phylogenetic Information Distance, Clustering Information Distance, Matching Split Information Distance; Smith, 2020) <doi:10.1093/bioinformatics/btaa614>; Jaccard-Robinson-Foulds distances (Bocker et al. 2013) <doi:10.1007/978-3-642-40453-5_13>, including the Nye et al. (2006) metric <doi:10.1093/bioinformatics/bti720>; the Matching Split Distance (Bogdanowicz & Giaro 2012) <doi:10.1109/TCBB.2011.48>; Maximum Agreement Subtree distances; the Kendall-Colijn (2016) distance <doi:10.1093/molbev/msw124>, and the Nearest Neighbour Interchange (NNI) distance, approximated per Li et al. (1996) <doi:10.1007/3-540-61332-3_168>. Calculates the median of a set of trees under any distance metric.
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2025-09-28 |
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uharfbuzz
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public |
Streamlined Cython bindings for the harfbuzz shaping engine
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2025-09-28 |
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apache-airflow-providers-openlineage
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public |
Provider package apache-airflow-providers-openlineage for Apache Airflow
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2025-09-28 |
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apache-airflow-providers-cncf-kubernetes
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public |
Provider package apache-airflow-providers-cncf-kubernetes for Apache Airflow
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2025-09-28 |
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apache-airflow-providers-microsoft-psrp
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public |
Provider package apache-airflow-providers-microsoft-psrp for Apache Airflow
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2025-09-28 |
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pyct
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public |
Python package common tasks for users (e.g. copy examples, fetch data, ...)
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2025-09-28 |
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apache-airflow-providers-celery
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public |
Provider package apache-airflow-providers-celery for Apache Airflow
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2025-09-28 |
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apache-airflow-providers-smtp
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public |
Provider package apache-airflow-providers-smtp for Apache Airflow
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2025-09-28 |
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apache-airflow-providers-fab
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public |
Provider package apache-airflow-providers-fab for Apache Airflow
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2025-09-28 |
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apache-airflow-providers-edge3
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public |
Provider package apache-airflow-providers-edge3 for Apache Airflow
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2025-09-28 |
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r-spatstat
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public |
Comprehensive open-source toolbox for analysing Spatial Point Patterns. Focused mainly on two-dimensional point patterns, including multitype/marked points, in any spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, point patterns on a linear network, and patterns of other geometrical objects. Supports spatial covariate data such as pixel images. Contains over 2000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks. Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the functions ppm(), kppm(), slrm(), dppm() similar to glm(). Types of models include Poisson, Gibbs and Cox point processes, Neyman-Scott cluster processes, and determinantal point processes. Models may involve dependence on covariates, inter-point interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods. A model can be fitted to a list of point patterns (replicated point pattern data) using the function mppm(). The model can include random effects and fixed effects depending on the experimental design, in addition to all the features listed above. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.
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2025-09-28 |
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python-engineio
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public |
Engine.IO server
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2025-09-28 |
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markupsafe
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public |
Safely add untrusted strings to HTML/XML markup.
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2025-09-28 |
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r-ghostknockoff
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public |
Functions for multiple knockoff inference using summary statistics, e.g. Z-scores. The knockoff inference is a general procedure for controlling the false discovery rate (FDR) when performing variable selection. This package provides a procedure which performs knockoff inference without ever constructing individual knockoffs (GhostKnockoff). It additionally supports multiple knockoff inference for improved stability and reproducibility. Moreover, it supports meta-analysis of multiple overlapping studies.
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2025-09-28 |
