Seurat meets tidyverse. The best of both worlds.

📊 Computation and processing of models' parameters

Em 2016, ministrei, em parceria com minha querida colega Thais Sobjak, um minicurso de Ecologia Numérica para os graduandos de Ciências Biológicas da Universidade Estadual do Oeste do Paraná (UNIOESTE). O curso foi bem básico e apresentamos os conceitos e práticas de PCA e Cluster em R. A Thais ensinou a parte de índices ecológicos.

interactive Bioinformatics Exploratory Tools

Brings bulk and pseudobulk transcriptomics to the tidyverse

The HotellingEllipse package helps draw the Hotelling's T-squared ellipse on a PCA or PLS score scatterplot by computing the Hotelling's T-squared statistic and providing the ellipse's coordinates, semi-minor, and semi-major axes lengths.

This project explores the use of classification algorithms in predicting patient drug use.

Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language

solving problems with data analysis, hypotheses and the most used statistical tests in ecology

R Package: Regularized Principal Component Analysis for Spatial Data

Analysing practical examples by using principal component analysis (PCA) and Clustring

📦 Research Compendium for Mouillot et al. 2024's paper

A collection of Poisson lognormal models for multivariate count data analysis

Exploratory Principal Component Analysis

a ggplot PCA with complex annotation

Evolutionary genomics of chromosomal inversions in Atlantic herring

Implementation of the paper "A new principal component analysis by particle swarm optimization with an environmental application for data science".

Relative Importance PCA Regression in R

Multidimensional analysis to search for the best voivodeship for families with children

PCA is a statistical technique for reducing the dimensionality of a dataset