|
rust-std-aarch64-apple-darwin
|
public |
Rust is a systems programming language that runs blazingly fast, prevents segfaults, and guarantees thread safety.
This package provides the compiler (rustc) and the documentation utilities rustdoc.
|
2025-09-22 |
|
rust-std-aarch64-pc-windows-msvc
|
public |
Rust is a systems programming language that runs blazingly fast, prevents segfaults, and guarantees thread safety.
This package provides the compiler (rustc) and the documentation utilities rustdoc.
|
2025-09-22 |
|
r-readtext
|
public |
Functions for importing and handling text files and formatted text files with additional meta-data, such including '.csv', '.tab', '.json', '.xml', '.html', '.pdf', '.doc', '.docx', '.rtf', '.xls', '.xlsx', and others.
|
2025-09-22 |
|
r-disco
|
public |
Concordance and discordance of homologous gene regulation allows comparing reaction to stimuli in different organisms, for example human patients and animal models of a disease. The package contains functions to calculate discordance and concordance score for homologous gene pairs, identify concordantly or discordantly regulated transcriptional modules and visualize the results. It is intended for analysis of transcriptional data.
|
2025-09-22 |
|
rust-std-x86_64-apple-darwin
|
public |
Rust is a systems programming language that runs blazingly fast, prevents segfaults, and guarantees thread safety.
This package provides the compiler (rustc) and the documentation utilities rustdoc.
|
2025-09-22 |
|
xproperty
|
public |
C++ properties and observer pattern
|
2025-09-22 |
|
precious
|
public |
One code quality tool to rule them all
|
2025-09-22 |
|
pymsbuild
|
public |
The pymsbuild build backend.
|
2025-09-22 |
|
r-collateral
|
public |
The purrr package allows you to capture the side effects (errors, warning, messages and other output) of functions using safely() and quietly(). Using collateral, you can quickly see which elements of a list (or list-column) returned results, which threw errors and which returned warnings or other output.
|
2025-09-22 |
|
r-cmplot
|
public |
Manhattan plot, a type of scatter plot, was widely used to display the association results. However, it is usually time-consuming and laborious for a non-specialist user to write scripts and adjust parameters of an elaborate plot. Moreover, the ever-growing traits measured have necessitated the integration of results from different Genome-wide association study researches. Circle Manhattan Plot is the first open R package that can lay out. Genome-wide association study P-value results in both traditional rectangular patterns, QQ-plot and novel circular ones. United in only one bull's eye style plot, association results from multiple traits can be compared interactively, thereby to reveal both similarities and differences between signals. Additional functions include: highlight signals, a group of SNPs, chromosome visualization and candidate genes around SNPs.
|
2025-09-22 |
|
pondpond
|
public |
Pond is a high performance object-pooling library for Python.
|
2025-09-22 |
|
auto_gptq
|
public |
An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.
|
2025-09-22 |
|
r-ordpens
|
public |
Selection and/or smoothing of ordinally scaled independent variables using a group lasso or generalized ridge penalty.
|
2025-09-22 |
|
r-lsa
|
public |
The basic idea of latent semantic analysis (LSA) is, that text do have a higher order (=latent semantic) structure which, however, is obscured by word usage (e.g. through the use of synonyms or polysemy). By using conceptual indices that are derived statistically via a truncated singular value decomposition (a two-mode factor analysis) over a given document-term matrix, this variability problem can be overcome.
|
2025-09-22 |
|
r-uptasticsearch
|
public |
'Elasticsearch' is an open-source, distributed, document-based datastore (<https://www.elastic.co/products/elasticsearch>). It provides an 'HTTP' 'API' for querying the database and extracting datasets, but that 'API' was not designed for common data science workflows like pulling large batches of records and normalizing those documents into a data frame that can be used as a training dataset for statistical models. 'uptasticsearch' provides an interface for 'Elasticsearch' that is explicitly designed to make these data science workflows easy and fun.
|
2025-09-22 |
|
r-gggrid
|
public |
An extension of 'ggplot2' that makes it easy to add raw 'grid' output, such as customised annotations, to a 'ggplot2' plot.
|
2025-09-22 |
|
changeforest
|
public |
Classifier based non-parametric change point detection
|
2025-09-22 |
|
napari-convpaint
|
public |
A plugin for segmentation by pixel classification using convolutional feature extraction
|
2025-09-22 |
|
r-ddpcr
|
public |
An interface to explore, analyze, and visualize droplet digital PCR (ddPCR) data in R. This is the first non-proprietary software for analyzing two-channel ddPCR data. An interactive tool was also created and is available online to facilitate this analysis for anyone who is not comfortable with using R.
|
2025-09-22 |
|
r-gfa
|
public |
Factor analysis implementation for multiple data sources, i.e., for groups of variables. The whole data analysis pipeline is provided, including functions and recommendations for data normalization and model definition, as well as missing value prediction and model visualization. The model group factor analysis (GFA) is inferred with Gibbs sampling, and it has been presented originally by Virtanen et al. (2012), and extended in Klami et al. (2015) <DOI:10.1109/TNNLS.2014.2376974> and Bunte et al. (2016) <DOI:10.1093/bioinformatics/btw207>; for details, see the citation info.
|
2025-09-22 |
|
r-testit
|
public |
Provides two convenience functions assert() and test_pkg() to facilitate testing R packages.
|
2025-09-22 |
|
multiaddr
|
public |
Python implementation of jbenet's multiaddr
|
2025-09-22 |
|
r-logistf
|
public |
Fit a logistic regression model using Firth's bias reduction method, equivalent to penalization of the log-likelihood by the Jeffreys prior. Confidence intervals for regression coefficients can be computed by penalized profile likelihood. Firth's method was proposed as ideal solution to the problem of separation in logistic regression, see Heinze and Schemper (2002) <doi:10.1002/sim.1047>. If needed, the bias reduction can be turned off such that ordinary maximum likelihood logistic regression is obtained. Two new modifications of Firth's method, FLIC and FLAC, lead to unbiased predictions and are now available in the package as well, see Puhr et al (2017) <doi:10.1002/sim.7273>.
|
2025-09-22 |
|
sentencepiece
|
public |
Unsupervised text tokenizer for Neural Network-based text generation.
|
2025-09-22 |
|
sentencepiece-python
|
public |
Unsupervised text tokenizer for Neural Network-based text generation.
|
2025-09-22 |
