vioplot - Violin Plot

A violin plot is a combination of a box plot and a kernel density plot. This package allows extensive customisation of violin plots.

Last updated 8 months ago

boxplotcolourscustomisationdatavizformulaplottingviolin-plotviolinplotvioplot

11.97 score 26 stars 8 dependents 2.0k scripts 9.5k downloads

leiden - R Implementation of Leiden Clustering Algorithm

Implements the 'Python leidenalg' module to be called in R. Enables clustering using the leiden algorithm for partition a graph into communities. See the 'Python' repository for more details: <https://github.com/vtraag/leidenalg> Traag et al (2018) From Louvain to Leiden: guaranteeing well-connected communities. <arXiv:1810.08473>.

Last updated 9 months ago

10.62 score 38 stars 54 dependents 188 scripts 15k downloads

matrixcalc - Collection of Functions for Matrix Calculations

A collection of functions to support matrix calculations for probability, econometric and numerical analysis. There are additional functions that are comparable to APL functions which are useful for actuarial models such as pension mathematics. This package is used for teaching and research purposes at the Department of Finance and Risk Engineering, New York University, Polytechnic Institute, Brooklyn, NY 11201. Horn, R.A. (1990) Matrix Analysis. ISBN 978-0521386326. Lancaster, P. (1969) Theory of Matrices. ISBN 978-0124355507. Lay, D.C. (1995) Linear Algebra: And Its Applications. ISBN 978-0201845563.

Last updated 4 years ago

8.21 score 148 dependents 1.7k scripts 7.3k downloads

graphsim - Simulate Expression Data from 'igraph' Networks

Functions to develop simulated continuous data (e.g., gene expression) from a sigma covariance matrix derived from a graph structure in 'igraph' objects. Intended to extend 'mvtnorm' to take 'igraph' structures rather than sigma matrices as input. This allows the use of simulated data that correctly accounts for pathway relationships and correlations. This allows the use of simulated data that correctly accounts for pathway relationships and correlations. Here we present a versatile statistical framework to simulate correlated gene expression data from biological pathways, by sampling from a multivariate normal distribution derived from a graph structure. This package allows the simulation of biological pathways from a graph structure based on a statistical model of gene expression. For example methods to infer biological pathways and gene regulatory networks from gene expression data can be tested on simulated datasets using this framework. This also allows for pathway structures to be considered as a confounding variable when simulating gene expression data to test the performance of genomic analyses.

Last updated 2 years ago

benchmarkinggene-expressiongene-regulatory-networksgeneticsgenomic-data-analysisgenomicsgraph-algorithmsigraph-networksjossngs-analysissimulated-datasimulation-modeling

5.08 score 24 stars 2 scripts 393 downloads