Pathways and networks Tools

Model based analysis for chip-seq data

Peak-caller for CLIP- and RIP-Seq high-throughput protein-RNA interaction data. It accepts input in BED or BAM format and identifies regions of significant enrichment for reads. It can also optionally incorporate additional external covariates into the peak-calling process, and identify sites of differential binding occupancy between cell types, conditions or development stages.

Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data

ANANSE is a computational approach to infer enhancer-based gene regulatory networks (GRNs) and to use these GRNs to identify the key transcription factors in cell fate determination.

Rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genomes. It integrates and cross-links with a large number of in silico secondary metabolite analysis tools that have been published earlier.

A scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.