ggsignif - Significance Brackets for 'ggplot2'
Enrich your 'ggplots' with group-wise comparisons. This package provides an easy way to indicate if two groups are significantly different. Commonly this is shown by a bracket on top connecting the groups of interest which itself is annotated with the level of significance (NS, *, **, ***). The package provides a single layer (geom_signif()) that takes the groups for comparison and the test (t.test(), wilcox.text() etc.) as arguments and adds the annotation to the plot.
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asteriskggplot-extensionggplot2significance-stars
16.43 score 612 stars 479 dependents 4.4k scripts 174k downloads
glmGamPoi - Fit a Gamma-Poisson Generalized Linear Model
Fit linear models to overdispersed count data. The package can estimate the overdispersion and fit repeated models for matrix input. It is designed to handle large input datasets as they typically occur in single cell RNA-seq experiments.
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regressionrnaseqsoftwaresinglecellgamma-poissonglmnegative-binomial-regressionon-diskopenblascpp
12.12 score 122 stars 4 dependents 2.1k scripts 10k downloads
sparseMatrixStats - Summary Statistics for Rows and Columns of Sparse Matrices
High performance functions for row and column operations on sparse matrices. For example: col / rowMeans2, col / rowMedians, col / rowVars etc. Currently, the optimizations are limited to data in the column sparse format. This package is inspired by the matrixStats package by Henrik Bengtsson.
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infrastructuresoftwaredatarepresentationcpp
12.06 score 55 stars 156 dependents 326 scripts 27k downloadsggupset - Combination Matrix Axis for 'ggplot2' to Create 'UpSet' Plots
Replace the standard x-axis in 'ggplots' with a combination matrix to visualize complex set overlaps. 'UpSet' has introduced a new way to visualize the overlap of sets as an alternative to Venn diagrams. This package provides a simple way to produce such plots using 'ggplot2'. In addition it can convert any categorical axis into a combination matrix axis.
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ggplotggplot-extensionupset
10.11 score 396 stars 7 dependents 924 scripts 4.2k downloadsproDA - Differential Abundance Analysis of Label-Free Mass Spectrometry Data
Account for missing values in label-free mass spectrometry data without imputation. The package implements a probabilistic dropout model that ensures that the information from observed and missing values are properly combined. It adds empirical Bayesian priors to increase power to detect differentially abundant proteins.
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proteomicsmassspectrometrydifferentialexpressionbayesianregressionsoftwarenormalizationqualitycontrol
8.28 score 23 stars 2 dependents 76 scripts 543 downloadslemur - Latent Embedding Multivariate Regression
Fit a latent embedding multivariate regression (LEMUR) model to multi-condition single-cell data. The model provides a parametric description of single-cell data measured with treatment vs. control or more complex experimental designs. The parametric model is used to (1) align conditions, (2) predict log fold changes between conditions for all cells, and (3) identify cell neighborhoods with consistent log fold changes. For those neighborhoods, a pseudobulked differential expression test is conducted to assess which genes are significantly changed.
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transcriptomicsdifferentialexpressionsinglecelldimensionreductionregressionquartoopenblascpp
6.87 score 101 stars 92 scripts 355 downloadstransformGamPoi - Variance Stabilizing Transformation for Gamma-Poisson Models
Variance-stabilizing transformations help with the analysis of heteroskedastic data (i.e., data where the variance is not constant, like count data). This package provide two types of variance stabilizing transformations: (1) methods based on the delta method (e.g., 'acosh', 'log(x+1)'), (2) model residual based (Pearson and randomized quantile residuals).
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singlecellnormalizationpreprocessingregressioncpp
6.23 score 22 stars 39 scripts 310 downloadseinsum - Einstein Summation
The summation notation suggested by Einstein (1916) <doi:10.1002/andp.19163540702> is a concise mathematical notation that implicitly sums over repeated indices of n-dimensional arrays. Many ordinary matrix operations (e.g. transpose, matrix multiplication, scalar product, 'diag()', trace etc.) can be written using Einstein notation. The notation is particularly convenient for expressing operations on arrays with more than two dimensions because the respective operators ('tensor products') might not have a standardized name.
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cpp
5.32 score 12 stars 9 dependents 13 scripts 599 downloadsmixdir - Cluster High Dimensional Categorical Datasets
Scalable Bayesian clustering of categorical datasets. The package implements a hierarchical Dirichlet (Process) mixture of multinomial distributions. It is thus a probabilistic latent class model (LCM) and can be used to reduce the dimensionality of hierarchical data and cluster individuals into latent classes. It can automatically infer an appropriate number of latent classes or find k classes, as defined by the user. The model is based on a paper by Dunson and Xing (2009) <doi:10.1198/jasa.2009.tm08439>, but implements a scalable variational inference algorithm so that it is applicable to large datasets. It is described and tested in the accompanying paper by Ahlmann-Eltze and Yau (2018) <doi:10.1109/DSAA.2018.00068>.
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categorical-dataclusteringquestionnairesvariational-inferencecpp
4.27 score 17 stars 22 scripts 196 downloads