TFscope
Characterizing the binding preferences of transcription factors (TFs) in different cell types and conditions is key to understand how they orchestrate gene expression. TFscope is a machine learning approach that identifies sequence features explaining the binding differences observed between two ChIP-seq experiments targeting either the same TF in two conditions or two TFs with similar motifs (paralogous TFs). TFscope systematically investigates differences in the core motif, nucleotide environment and co-factor motifs, and provides the contribution of each key feature in the two experiments.
TFscope online execution
Other tools
LoRDEC: hybrid correction of long…
Overview In a nutshell, LoRDEC is a program for error correcting long sequencing reads using short reads. It implements a hybrid correction approach. It uses little memory and is very efficient. Most importantly it scales up to process very large data sets. It can be applied to long reads obtained with either Pacific Biosciences SMRT…
PEWO: a collection of workflows…
Introduction and context In the Bioinformatics team of the LIRMM (CNRS & Univ. Montpellier), we develop a series of tools for metagenomics / metabarcoding analysis. Our tools exploit phylo-k-mers (which are k-mers combined with phylogenetic information) computed for an input set of reference sequences and their phylogeny. The phylo-k-mers are computed and indexed with IPK,…
EPIK: Precise and scalable evolutionary…
EPIK is a program dedicated to « Phylogenetic Placement » (PP) of metagenomic or metabarcoding reads on a reference tree. It is similar in spirit and technically the successor of RAPPAS (Linard et al. 2020). EPIK achieves identical or slightly better accuracy than RAPPAS and outperforms it in speed and flexibility. In many aspects the documentation of RAPPAS…