Companion repository to Lause, Berens & Kobak (2021): "Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data", Genome Biology

Probabilistic outlier identification for bulk RNA sequencing data

NewWave

Code for fitting a negative binomial distribution in Python

Various Fortran codes

Negative binomial distributed pseudorandom numbers.

High-precision ribosome pause detection tool utilizing Negative Binomial modeling to optimize Z-scores and extract ML-ready contextual features from Ribo-seq data.

RNS-Seq Count Model Explorer

The DOTNB repository is a collection of code files that implement DOTNB across several programming languages. The DOTNB is the distribution for the Difference Of Two Negative Binomial distributions, i.e., Z=X-Y ~ DOTNB (λ_1,λ_2,p_1,p_2), where X ~ NB(λ_1,p_1 ) and Y ~ NB(λ_2,p_2 ).

Create an iterator for generating pseudorandom numbers drawn from a negative binomial distribution.

Create an array containing pseudorandom numbers drawn from a negative binomial distribution.

Slides sobre modelos de regressão poisson e binomial negativa inflacionadas de zeros

Optional presentation for the "Sistemi Complessi" course.

This project analyzes species observations from the National Park Service’s biodiversity database to examine how species category, nativeness, and abundance classification influence richness across U.S. National Parks.

Conducting a predictive data analysis to predict the future rental bike demands.

Regional Consistency Probability for Single-Arm Multi-Regional Clinical Trials

Final project in Safety Management: analytics and predictive modeling for occupational incidents. Includes EDA, logistic regression, Poisson/Negative Binomial with overdispersion checks, ROC/AUC, and prediction exercises.

DEGage is a novel model-based method for gene differential expression analysis between two groups of scRNA-seq count data. It employs a novel family of discrete distributions for describing the difference of two NB distributions (named DOTNB).

Exploratory and descriptive statistical analysis of daily COVID-19 case and fatality reports from Kaggle (2020–2024).

GLM para dados de contagem: Poisson vs Binomial Negativa, diagnóstico de superdispersão e validação fora da amostra.