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r-nnlm
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public |
This is a package for Non-Negative Linear Models (NNLM). It implements fast sequential coordinate descent algorithms for non-negative linear regression and non-negative matrix factorization (NMF). It supports mean square error and Kullback-Leibler divergence loss. Many other features are also implemented, including missing value imputation, domain knowledge integration, designable W and H matrices and multiple forms of regularizations.
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2025-03-25 |
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vireosnp
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public |
vireoSNP - donor deconvolution for multiplexed scRNA-seq data
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2025-03-25 |
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txg
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public |
The 10x Genomics Cloud CLI is a command line interface (CLI) that allows you to upload FASTQ files to projects in your 10x Genomics account, create projects from the command line, and manage other tasks related to your 10x Genomics account.
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2025-03-25 |
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r-seuratdisk
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public |
The h5Seurat file format is specifically designed for the storage and analysis of multi-modal single-cell and spatially-resolved expression experiments, for example, from CITE-seq or 10X Visium technologies. It holds all molecular information and associated metadata, including (for example) nearest-neighbor graphs, dimensional reduction information, spatial coordinates and image data, and cluster labels. We also support rapid and on-disk conversion between h5Seurat and AnnData objects, with the goal of enhancing interoperability between Seurat and Scanpy.
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2025-03-25 |
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r-topicscore
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public |
Provides implementation of the "Topic SCORE" algorithm that is proposed by Tracy Ke and Minzhe Wang. The singular value decomposition step is optimized through the usage of svds() function in 'RSpectra' package, on a 'dgRMatrix' sparse matrix. Also provides a column-wise error measure in the word-topic matrix A, and an algorithm for recovering the topic-document matrix W given A and D based on quadratic programming. The details about the techniques are explained in the paper "A new SVD approach to optimal topic estimation" by Tracy Ke and Minzhe Wang (2017) <arXiv:1704.07016>.
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2025-03-25 |
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r-mvsusier
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public |
A more general implementation of the Sum of SIngle Effects (SuSiE) regression for Bayesian variable selection.
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2025-03-25 |
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r-grove
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public |
Functional denoising and functional ANOVA through wavelet-domain Markov groves. Fore more details see: Ma L. and Soriano J. (2016) Efficient functional ANOVA through wavelet-domain Markov groves. <arXiv:1602.03990v2 [stat.ME]>.
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2025-03-25 |
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r-coloc
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public |
Performs the colocalisation tests described in Plagnol et al (2009) <doi:10.1093/biostatistics/kxn039>, Wallace et al (2013) <doi:10.1002/gepi.21765>, Giambartolomei et al (2013) <doi:10.1371/journal.pgen.1004383>, Wallace (2020) <doi:doi.org/10.1371/journal.pgen.1008720>.
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2025-03-25 |
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r-bma
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public |
Package for Bayesian model averaging and variable selection for linear models, generalized linear models and survival models (cox regression).
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2025-03-25 |
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r-rrcov
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public |
Robust Location and Scatter Estimation and Robust Multivariate Analysis with High Breakdown Point: principal component analysis (Filzmoser and Todorov (2013), <doi:10.1016/j.ins.2012.10.017>), linear and quadratic discriminant analysis (Todorov and Pires (2007)), multivariate tests (Todorov and Filzmoser (2010) <doi:10.1016/j.csda.2009.08.015>), outlier detection (Todorov et al. (2010) <doi:10.1007/s11634-010-0075-2>). See also Todorov and Filzmoser (2009) <ISBN-13:978-3838108148>, Todorov and Filzmoser (2010) <doi:10.18637/jss.v032.i03> and Boudt et al. (2019) <doi:10.1007/s11222-019-09869-x>.
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2025-03-25 |
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r-rcpparmadillo
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public |
'Armadillo' is a templated C++ linear algebra library (by Conrad Sanderson) that aims towards a good balance between speed and ease of use. Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. The 'RcppArmadillo' package includes the header files from the templated 'Armadillo' library. Thus users do not need to install 'Armadillo' itself in order to use 'RcppArmadillo'. From release 7.800.0 on, 'Armadillo' is licensed under Apache License 2; previous releases were under licensed as MPL 2.0 from version 3.800.0 onwards and LGPL-3 prior to that; 'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'. Note that Armadillo requires a fairly recent compiler; for the g++ family at least version 4.6.* is required.
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2025-03-25 |
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r-mrash
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public |
No Summary
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2025-03-25 |
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r-invgamma
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public |
Light weight implementation of the standard distribution functions for the inverse gamma distribution, wrapping those for the gamma distribution in the stats package.
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2025-03-25 |
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mpebpm
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public |
This package provides GPU-accelerated inference for the Empirical Bayes Poisson Means (EBPM) problem. This model can be used to model variation in scRNA-seq data due to measurement error, as well as variation in true gene expression values (Sarkar and Stephens 2020).
This implementation readily supports fitting the model for data on the order of 10^6 cells and 10^4 genes in parallel. It also supports fitting multiple EBPM problems per gene in parallel, as arise when e.g., cells have been assigned to groups (clusters). For example, we have used the method to solve 537,678 EBPM problems (54 conditions by 9,957 genes) in parallel in a few minutes (Sarkar et al. 2019).
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2025-03-25 |
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r-susier
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public |
Implements methods for variable selection in linear regression based on the "Sum of Single Effects" (SuSiE) model, as described in Wang et al (2020) <DOI:10.1101/501114>. These methods provide simple summaries, called "Credible Sets", for accurately quantifying uncertainty in which variables should be selected. The methods are motivated by genetic fine-mapping applications, and are particularly well-suited to settings where variables are highly correlated and detectable effects are sparse. The fitting algorithm, a Bayesian analogue of stepwise selection methods called "Iterative Bayesian Stepwise Selection" (IBSS), is simple and fast, allowing the SuSiE model be fit to large data sets (thousands of samples and hundreds of thousands of variables).
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2025-03-25 |
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r-fasttopics
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public |
Fast algorithms for fitting topic models and non-negative factorizations to count data.
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2025-03-25 |
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r-rcpp
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public |
The 'Rcpp' package provides R functions as well as C++ classes which offer a seamless integration of R and C++. Many R data types and objects can be mapped back and forth to C++ equivalents which facilitates both writing of new code as well as easier integration of third-party libraries. Documentation about 'Rcpp' is provided by several vignettes included in this package, via the 'Rcpp Gallery' site at <http://gallery.rcpp.org>, the paper by Eddelbuettel and Francois (2011, <doi:10.18637/jss.v040.i08>), the book by Eddelbuettel (2013, <doi:10.1007/978-1-4614-6868-4>) and the paper by Eddelbuettel and Balamuta (2018, <doi:10.1080/00031305.2017.1375990>); see 'citation("Rcpp")' for details.
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2025-03-25 |
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r-cowplot
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public |
Provides various features that help with creating publication-quality figures with 'ggplot2', such as a set of themes, functions to align plots and arrange them into complex compound figures, and functions that make it easy to annotate plots and or mix plots with images. The package was originally written for internal use in the Wilke lab, hence the name (Claus O. Wilke's plot package). It has also been used extensively in the book Fundamentals of Data Visualization.
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2025-03-25 |
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r-rcppparallel
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High level functions for parallel programming with 'Rcpp'. For example, the 'parallelFor()' function can be used to convert the work of a standard serial "for" loop into a parallel one and the 'parallelReduce()' function can be used for accumulating aggregate or other values.
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2025-03-25 |
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ucsc-liftover
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public |
Move annotations from one assembly to another
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2025-03-25 |
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pyplink
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public |
Python module to read binary Plink files.
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2025-03-25 |
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scqtl
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public |
This package implements maximum likelihood estimation of the zero-inflated negative binomial model described in:
Abhishek K Sarkar, Po-Yuan Tung, John D. Blischak, Jonathan E. Burnett, Yang I. Li, Matthew Stephens, Yoav Gilad. "Discovery and characterization of variance QTLs in human induced pluripotent stem cells". PLoS Genetics (2019). https://doi.org/10.1371/journal.pgen.1008045
The key idea is that we learn latent point-Gamma distributions for expression per individual/condition per gene, and then perform all downstream analysis on (the parameters of) those distributions.
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2025-03-25 |
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scmodes
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public |
This package collects implementations of single cell expression models, and code to evaluate their performance as described in Sarkar, AK and Stephens, M. "Separating measurement and expression models clarifies confusion in single-cell RNA sequencing analysis"
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2025-03-25 |
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r-pracma
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public |
Provides a large number of functions from numerical analysis and linear algebra, numerical optimization, differential equations, time series, plus some well-known special mathematical functions. Uses 'MATLAB' function names where appropriate to simplify porting.
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2025-03-25 |
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hyperopt
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public |
Distributed Asynchronous Hyperparameter Optimization
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2025-03-25 |
