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Scripts for the analysis of metagenomic data from the first week of life.

Scripts for the analysis of metagenomic data from the first week of life.

Network Analyses - SpiecEasi The Rscripts and Snakefile herein can be used to run SpiecEasi for generating networks from taxonomic counts Dependencies snakemake >= 5.3.0 References (SpiecEasi)[https://github.com/zdk123/SpiecEasi]

This repository contains the scripts that have been developed in the course of the GeneDER project (Biomedical Data Science group - Enrico Glaab Lab).

Gene regulation inference of COVID-19

GigaSOM.jl: Huge-scale, high-performance flow cytometry clustering in Julia.

Utilities that work with GNPS records.

Utilities that work with GNPS records.

Code used for the analysis of the RNA-seq, ATAC-seq and ChIP-seq datasets produced in this study. Original fastq files deposited in https://ega-archive.org/, under the accession number EGAD00001009288.

Graph representation learning modelling pipeline exploiting molecular interaction networks of transcriptomics (protein-protein interactions) and metabolomics (metabolite-metabolite interactions) to learn PD-specific fingerprints from the spatial distribution of molecular relationships in an end-to-end fashion. The scripts apply the graph representation learning modelling pipeline on networks of molecular interactions, where transcriptomics and metabolomics data from the PPMI and the LuxPARK cohort, respectively, are projected.

Graph representation learning modelling pipeline exploiting sample-similarity networks derived from high-throughput omics profiles to learn PD-specific fingerprints from the spatial distribution of molecular abundance similarities in an end-to-end fashion. The scripts apply the graph representation learning modelling pipeline on sample-similarity networks of transcriptomics and metabolomics data from the PPMI and the LuxPARK cohort, respectively.

R package for Gene Regulatory Networks

The sensitivity analysis of IFN1 boolean model is investigated against over expression and knockout mutations. The simulation is performed based on the ranked sensitivity values. Attractors' analysis is also performed to support the main conclusions.

Integrated meta-omics pipeline

Integrated meta-omics pipeline