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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 |
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r-v8
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public |
An R interface to V8, Google's open source JavaScript and WebAssembly engine. This package can be compiled either with V8 version 6 and up, a NodeJS shared library, or the legacy 3.14/3.15 branch of V8.
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2025-09-28 |
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r-seqminer
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public |
Integrate sequencing data (Variant call format, e.g. VCF or BCF) or meta-analysis results in R. This package can help you (1) read VCF/BCF/BGEN files by chromosomal ranges (e.g. 1:100-200); (2) read RareMETAL summary statistics files; (3) read tables from a tabix-indexed files; (4) annotate VCF/BCF files; (5) create customized workflow based on Makefile.
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2025-09-28 |
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r-rcppclock
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public |
Time the execution of overlapping or unique 'Rcpp' code chunks using convenient methods, seamlessly write timing results to an 'RcppClock' object in the R global environment, and summarize and/or plot the results in R.
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2025-09-28 |
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airflow
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public |
Airflow is a platform to programmatically author, schedule and monitor
workflows
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2025-09-28 |
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airflow-with-all-core
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public |
Airflow is a platform to programmatically author, schedule and monitor
workflows
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2025-09-28 |
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airflow-with-all
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public |
Airflow is a platform to programmatically author, schedule and monitor
workflows
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2025-09-28 |
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apache-airflow
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public |
Airflow is a platform to programmatically author, schedule and monitor
workflows
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2025-09-28 |
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litellm
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public |
Library to easily interface with LLM API providers
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2025-09-28 |
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super_collections
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public |
Dictionaries as you dreamed them when you were a kid.
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2025-09-28 |
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super-collections
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public |
Dictionaries as you dreamed them when you were a kid.
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2025-09-28 |
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r-spatstat.model
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public |
Functionality for exploratory data analysis and nonparametric analysis of spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) 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.
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2025-09-28 |
