R-universe search: exports:plot

Showing 17 of total 17 results (show query)

pecanproject

PEcAn.visualization:PEcAn visualization functions

The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation. This module is used to create more complex visualizations from the data generated by PEcAn code, specifically the models.

Maintained by David LeBauer. Last updated 4 hours ago.

bayesian cyberinfrastructure data-assimilation data-science ecosystem-model ecosystem-science forecasting meta-analysis national-science-foundation pecan plants

216 stars 10.98 score 74 scripts 11 dependents

brianstock

MixSIAR:Bayesian Mixing Models in R

Creates and runs Bayesian mixing models to analyze biological tracer data (i.e. stable isotopes, fatty acids), which estimate the proportions of source (prey) contributions to a mixture (consumer). 'MixSIAR' is not one model, but a framework that allows a user to create a mixing model based on their data structure and research questions, via options for fixed/ random effects, source data types, priors, and error terms. 'MixSIAR' incorporates several years of advances since 'MixSIR' and 'SIAR'.

Maintained by Brian Stock. Last updated 4 years ago.

jags cpp

98 stars 9.27 score 122 scripts

daijiang

phyr:Model Based Phylogenetic Analysis

A collection of functions to do model-based phylogenetic analysis. It includes functions to calculate community phylogenetic diversity, to estimate correlations among functional traits while accounting for phylogenetic relationships, and to fit phylogenetic generalized linear mixed models. The Bayesian phylogenetic generalized linear mixed models are fitted with the 'INLA' package (<https://www.r-inla.org>).

Maintained by Daijiang Li. Last updated 1 years ago.

bayesian glmm inla phylogeny species-distribution-modeling openblas cpp

31 stars 8.71 score 107 scripts 2 dependents

r-world-devs

cohortBuilder:Data Source Agnostic Filtering Tools

Common API for filtering data stored in different data models. Provides multiple filter types and reproducible R code. Works standalone or with 'shinyCohortBuilder' as the GUI for interactive Shiny apps.

Maintained by Krystian Igras. Last updated 13 days ago.

8 stars 8.01 score 55 scripts 1 dependents

bioc

BioCor:Functional similarities

Calculates functional similarities based on the pathways described on KEGG and REACTOME or in gene sets. These similarities can be calculated for pathways or gene sets, genes, or clusters and combined with other similarities. They can be used to improve networks, gene selection, testing relationships...

Maintained by Lluís Revilla Sancho. Last updated 5 months ago.

statisticalmethod clustering geneexpression network pathways networkenrichment systemsbiology bioconductor-packages bioinformatics functional-similarity gene gene-sets pathway-analysis similarity similarity-measurement

14 stars 6.47 score

jacolien

itsadug:Interpreting Time Series and Autocorrelated Data Using GAMMs

GAMM (Generalized Additive Mixed Modeling; Lin & Zhang, 1999) as implemented in the R package 'mgcv' (Wood, S.N., 2006; 2011) is a nonlinear regression analysis which is particularly useful for time course data such as EEG, pupil dilation, gaze data (eye tracking), and articulography recordings, but also for behavioral data such as reaction times and response data. As time course measures are sensitive to autocorrelation problems, GAMMs implements methods to reduce the autocorrelation problems. This package includes functions for the evaluation of GAMM models (e.g., model comparisons, determining regions of significance, inspection of autocorrelational structure in residuals) and interpreting of GAMMs (e.g., visualization of complex interactions, and contrasts).

Maintained by Jacolien van Rij. Last updated 3 years ago.

1 stars 6.45 score 576 scripts 2 dependents

jtimonen

lgpr:Longitudinal Gaussian Process Regression

Interpretable nonparametric modeling of longitudinal data using additive Gaussian process regression. Contains functionality for inferring covariate effects and assessing covariate relevances. Models are specified using a convenient formula syntax, and can include shared, group-specific, non-stationary, heterogeneous and temporally uncertain effects. Bayesian inference for model parameters is performed using 'Stan'. The modeling approach and methods are described in detail in Timonen et al. (2021) <doi:10.1093/bioinformatics/btab021>.

Maintained by Juho Timonen. Last updated 7 months ago.

bayesian-inference gaussian-processes longitudinal-data stan cpp

25 stars 5.94 score 69 scripts

bioc

autonomics:Unified Statistical Modeling of Omics Data

This package unifies access to Statistal Modeling of Omics Data. Across linear modeling engines (lm, lme, lmer, limma, and wilcoxon). Across coding systems (treatment, difference, deviation, etc). Across model formulae (with/without intercept, random effect, interaction or nesting). Across omics platforms (microarray, rnaseq, msproteomics, affinity proteomics, metabolomics). Across projection methods (pca, pls, sma, lda, spls, opls). Across clustering methods (hclust, pam, cmeans). It provides a fast enrichment analysis implementation. And an intuitive contrastogram visualisation to summarize contrast effects in complex designs.

Maintained by Aditya Bhagwat. Last updated 2 months ago.

software dataimport preprocessing dimensionreduction principalcomponent regression differentialexpression genesetenrichment transcriptomics transcription geneexpression rnaseq microarray proteomics metabolomics massspectrometry

5.89 score 5 scripts

pyhernvann

EcoDiet:Estimating a Diet Matrix from Biotracer and Stomach Content Data

Biotracers and stomach content analyses are combined in a Bayesian hierarchical model to estimate a probabilistic topology matrix (all trophic link probabilities) and a diet matrix (all diet proportions). The package relies on the JAGS software and the 'jagsUI' package to run a Markov chain Monte Carlo approximation of the different variables.

Maintained by Pierre-Yves Hernvann. Last updated 1 years ago.

jags cpp

4 stars 5.33 score 12 scripts

pydemull

activAnalyzer:A 'Shiny' App to Analyze Accelerometer-Measured Daily Physical Behavior Data

A tool to analyse 'ActiGraph' accelerometer data and to implement the use of the PROactive Physical Activity in COPD (chronic obstructive pulmonary disease) instruments. Once analysis is completed, the app allows to export results to .csv files and to generate a report of the measurement. All the configured inputs relevant for interpreting the results are recorded in the report. In addition to the existing 'R' packages that are fully integrated with the app, the app uses some functions from the 'actigraph.sleepr' package developed by Petkova (2021) <https://github.com/dipetkov/actigraph.sleepr/>.

Maintained by Pierre-Yves de Müllenheim. Last updated 10 days ago.

accelerometer actigraph app monitor shiny

5 stars 5.24 score 8 scripts

poissonconsulting

embr:Model Builder Utility Functions and Virtual Classes

Utility functions and virtual classes shared by model builder packages such as tmbr, jmbr and smbr.

Maintained by Joe Thorley. Last updated 2 months ago.

analyses mbr

3 stars 4.61 score 4 scripts 3 dependents

sineadmorris

ushr:Understanding Suppression of HIV

Analyzes longitudinal data of HIV decline in patients on antiretroviral therapy using the canonical biphasic exponential decay model (pioneered, for example, by work in Perelson et al. (1997) <doi:10.1038/387188a0>; and Wu and Ding (1999) <doi:10.1111/j.0006-341X.1999.00410.x>). Model fitting and parameter estimation are performed, with additional options to calculate the time to viral suppression. Plotting and summary tools are also provided for fast assessment of model results.

Maintained by Sinead E. Morris. Last updated 5 years ago.

art hiv modeling-tools

2 stars 4.04 score 11 scripts

kwb-r

kwb.pilot:Importing, Aggregating and Visualising Data From KWB Pilot Plants

Collects, aggregates and visualises operational and analytical data from water suppliers (including a standardised reporting document).

Maintained by Michael Rustler. Last updated 2 years ago.

data-aggregation data-import data-visualisation project-aquanes project-mbr40 project-suleman project-ultimate

1 stars 4.01 score 17 scripts

bognasmug

miLAG:Calculates Microbial Lag Duration (on the Population Level) from Provided Growth Curve Data

Microbial growth is often measured by growth curves i.e. a table of population sizes and times of measurements. This package allows to use such growth curve data to determine the duration of "microbial lag phase" i.e. the time needed for microbes to restart divisions. It implements the most commonly used methods to calculate the lag duration, these methods are discussed and described in Opalek et.al. 2022. Citation: Smug, B. J., Opalek, M., Necki, M., & Wloch-Salamon, D. (2024). Microbial lag calculator: A shiny-based application and an R package for calculating the duration of microbial lag phase. Methods in Ecology and Evolution, 15, 301–307 <doi:10.1111/2041-210X.14269>.

Maintained by Bogna Smug. Last updated 2 months ago.

3.60 score 3 scripts

cran

ABC.RAP:Array Based CpG Region Analysis Pipeline

It aims to identify candidate genes that are “differentially methylated” between cases and controls. It applies Student’s t-test and delta beta analysis to identify candidate genes containing multiple “CpG sites”.

Maintained by Abdulmonem Alsaleh. Last updated 8 years ago.

2.00 score

cran

dualScale:Dual Scaling Analysis of Data

Dual Scaling, developed by Professor Shizuhiko Nishisato (1994, ISBN: 0-9691785-3-6), is a fundamental technique in multivariate analysis used for data scaling and correspondence analysis. Its utility lies in its ability to represent multidimensional data in a lower-dimensional space, making it easier to visualize and understand underlying patterns in complex data. This technique has been implemented to handle various types of data, including Contingency and Frequency data (CF), Multiple-Choice data (MC), Sorting data (SO), Paired-Comparison data (PC), and Rank-Order data (RO), providing users with a powerful tool to explore relationships between variables and observations in various fields, from sociology to ecology, enabling deeper and more efficient analysis of multivariate datasets.

Maintained by Roberto de la Banda. Last updated 1 years ago.

1.70 score

kwb-r

dwc.ar4gw:R Package for Preparing Modflow Output Data for Articifical Reality Visualisation

R Package for preparing Modflow output data for articifical reality visualisation.

Maintained by Michael Rustler. Last updated 4 years ago.

flopy modflow project-dwc

1.70 score 1 scripts