sPLINK (safe PLINK) allows the federated, privacy-preserving analysis of GWAS data. It works on distributed datasets without exchanging raw data and is robust against imbalanced phenotype distributions across cohorts. Federated and user-friendly analysis with sPLINK, thus, has the potential to replace meta-analysis as the gold standard for collaborative GWAS. The tool is available online [here](https://www.exbio.wzw.tum.de/splink/).
To address the COVID-19 pandemic we developed a drug repurposing tool, which integrates SARS-CoV-2 and SARS-CoV interaction data.
To address the pandemic of the Coronavirus Disease-2019 (COVID-19), drug repurposing can be a helpful approach since it offers the possibility to find alternative fields of application for already approved drugs. **CoVex** is the first network and systems medicine online data analysis platform that integrates virus-human interaction data for SARS-CoV-2 and SARS-CoV. It is available as [interactive webtool](https://exbio.wzw.tum.de/covex/). More information and current updates can be found at the [CoVex blog](https://www.baumbachlab.net/exbio-vs-covid-part-1) at the *Chair of Experimental Bioinformatics* website.
Scellnetor is a novel scRNA-seq clustering tool. It allows the analysis of pseudo time-courses in single-cell sequencing data via a network-constrained clustering algorithm. Scellnetor is available as interactive online application at the [Scellnetor website](https://exbio.wzw.tum.de/scellnetor/).
EpiGEN is a Python pipeline for simulating epistasis data. It supports epistasis models of arbitrary size, which can be specified either extensionally or via parametrized risk models. Moreover, the user can specify the minor allele frequencies (MAFs) of both noise and disease SNPs, and provide a bias target distribution for the generated phenotypes to simulate observation bias. EpiGEN is freely available as python 3 package on [GitHub](https://github.com/baumbachlab/epigen).
The fast log-rank test implementation is now available as Python and R package.
Fastlogranktest is a software package providing wicked-fast implementations of the logrank test in C++, R, and Python.
BiCoN is a powerful new systems medicine tool to stratify patients while elucidating the responsible disease mechanisms. BiCoN is a network-constrained biclustering approach which restricts biclusters to functionally related genes connected in molecular interaction networks and maximizes the expression difference between two subgroups of patients. A package for network-constrained biclustering of patients and multi-omics data can also be used. Download and installation instructions can be found [here](https://pypi.org/project/bicon/).