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.

Statistical Analysis about cancer incidence in Modena hospital.

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

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

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 ).

Methods to estimate Negative Binomial Distribution

Optional presentation for the "Sistemi Complessi" course.

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).

Plots of how negative binomial distribution converges to Poisson distribution

We will extend the biclustering model to use Zero-Inflated Poisson (ZIP) and Zero-Inflated Negative Binomial (ZINB) distributions.