Our softwares

D-GENIES : Dot plot large GENomes in an interactive, efficient and simple way

Description: Dot plots are widely used to quickly compare sequence sets. They provide a synthetic similarity overview, highlighting repetitions, breaks and inversions. Different tools have been developed to easily generated genomic alignment dot plots, but they are often limited in the input sequence size. D-GENIES is a standalone and WEB application performing large genome alignments using minimap2 software package and generating interactive dot plots. It enables users to sort query sequences along the reference, zoom in the plot and download several image, alignment or sequence files. D-GENIES is an easy to install open source software package (GPL) developed in Python and JavaScript. The source code is available at https://github.com/genotoul-bioinfo/dgenie and it can be tested at http://dgenies.toulouse.inra.fr/.



Description: Analyses of transcriptomes produced by high throughput sequencing have revealed the existence of many long non coding transcripts (lncRNA) that lack long or conserved open reading frames (ORFs). Most of these lncRNAs do not yet have a known function but increasing evidence from both plants and animals studies has revealed that some previously annotated lncRNAs have the capacity to encode small peptides [doi 10.1166/jpsp.2017.1070]. These small peptides, also called miPEPs, are recognized as key actors to regulate the transcription of their own pri-miRNAs. We designed and implemented a strategy for searching conserved peptides over several (un)related genomes.

Availability: soon.



Description: Kernel-based methods are powerful methods for integrating heterogeneous types of data. mixKernel aims at providing methods to combine kernel for unsupervised exploratory analysis. Different solutions are provided to compute a meta-kernel, in a consensus way or in a way that best preserves the original topology of the data. mixKernel also integrates kernel PCA to visualize similarities between samples in a non linear space and from the multiple source point of view. Functions to assess and display important variables are also provided in the package.

Availability: mixKernel is available on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site.

Publication: Mariette, J. and Villa-Vialaneix, N. Unsupervised multiple kernel learning for heterogeneous data integration. Bioinformatics. 2017. btx682. doi: 10.1093/bioinformatics/btx682. see


Description: sRNA-TaBac is a web visualization interface for target predictions. It allows you to load our data and visualize them througt a friendly interface. It is a tool to help you to explore all your data from one or several software. Key features: i) load easily our data: input format GFF3 like (see Data Format), ii) give our reference genome, iii) fold our actors and see interaction on it, iv) convert data into alignment-like format (see Alignment-like Format), v) save our table result into CSV, vi) implementation of several filters.

Availability: sRNA-TaBac is not yet available.



Description: In sRNAseq data sets, only a very small fraction of reads can be assigned to a known functionnal family resulting in a lot of sRNAseq data orphan of functional annotation. The bias introduced by errors, the editing of some sequences but also the lack of similarities in existing ncRNA databases make challenging their structural and functional annotation. sRNAseq data analysis tools such as miRDeep,  miRanalyzer and others focus on microRNAs annotation and prediction, neglecting other types of RNAs. Recently, web tools such as DARIO, Ncpro enlarged functional annotation. sRNAbrowse is a software under development which aims at profiling, annotating and exploring as many sRNAseq data as possible, considering different ncRNA families and differential expression in multiple conditions and/or tissues.

Availability: sRNAbrowse is freely available on GitLab (workflow srnaseq).

Published instance: Juanchich et al, 2016


Description: Building rich WEB environments aimed at helping scientists analyse their data is a common trend in bioinformatics. These applications are often specialized WEB portals or generic Workflow management systems (WMS). The first class provides multiple services and analysis tools in an integrated interface for a specific experiment or data type. Quite often these systems hide the processing steps in the back-office. The second class is mainly focused on workflow creation and provides a rather poor end-user interface but enable to combine tools and data sources as desired. Jflow is a fully scalable WMS that can easily be embedded in any WEB site, providing all WMS features and benefits to your project.

Availability: Jflow code is freely available on GitLab.

Publication: Jérôme Mariette, Frédéric Escudié, Philippe Bardou, Ibouniyamine Nabihoudine, Céline Noirot, Marie-Stéphane Trotard, Christine Gaspin, Christophe Klopp. Jflow: a workflow management system for web applications. Bioinformatics. 2015. doi 10.1093/bioinformatics/btv589. see


Description: jvenn is a plug-in for the jQuery Javascript library. It is a flexible tool, based upon the venny tool first developed by J.C Oliveros (Oliveros, J.C (2007) VENNY, An integrative tool for comparing lists with Venn Diagrams). Key features: hanldes up to 6 classes venn diagram, allows to display Edwards-Venn diagram, is easily integrable within your own web site, allows to provide the data from 3 different ways (lists/intersection counts/count lists), control the click callback function, provides statistic charts based on input data, search for elements, exports the venn diagram to PNG and SVG, exports lists to CSV.

Availability: The plugin code and its documentation is freely available on GitLab. A running version of the plugin is also available from our WEB site.

Warning: Please note that we will not be adding any new features to this software.

Publication: Philippe Bardou, Jérôme Mariette, Frédéric Escudié, Christophe Djemiel and Christophe Klopp. jvenn: an interactive Venn diagram viewer. BMC Bioinformatics 2014, 15:293 doi:10.1186/1471-2105-15-293. see


Description : Transcriptome analysis based on a de novo assembly of next generation RNA sequences is now performed routinely in many laboratories. The generated results, including contig sequences, quantification figures, functional annotations and variation discovery outputs are usually bulky and quiet diverse. RNAbrowse is an user oriented storage and visualisation environment permitting to explore the data in a top-down manner, going from general graphical views to all possible details. The software package is based on biomart, easy to install and populate with local data.

Availability: The software package is available under the GNU General Public License (GPL) and can be downloaded from GitLab (workflow rnaseqdenovo).

Publication: Mariette J, Noirot C, Nabihoudine I, Bardou P, Hoede C, Djari A, Cabau C, Klopp C. (2014) RNAbrowse: RNA-Seq De Novo Assembly Results Browser. PLoS ONE 9(5): e96821. doi: 10.1371/journal.pone.0096821. see

Published instance: Magnanou et al, 2014; Hinaux et al, 2013; Riviere et al, 2015


Description: The platform works in tight collaboration with the GeT sequencing platform for the management and the analysis of data produced by their Roche 454 and Illumina HiSeq sequencers. NG6 is an extensible sequencing provider oriented LIMS. It includes read quality control and first level analysis processes which ease the data validation made jointly by the sequencing facility staff ant the end-users. It provides a secured user-friendly interface to visualize and download the raw sequences files and the analysis results.

Availability: The NG6 code is freely available on GitLab. To ease the installation, the package and all its dependencies are also available as a virtual machine. Installing and maintaining the system would require expertise in Linux system administration.

Publication:  Mariette J, Escudie F, Allias N, Salin G, Noirot C, Thomas S, Klopp C. NG6: Integrated next generation sequencing storage and processing environment. BMC Genomics, 2012 13:462. see


Description: The pyrocleaner is intended to clean the reads included in the sff file in order to ease the assembly process. It enables filtering sequences on different criteria such as length, complexity, number of undetermined bases which has been proven to correlate with poor quality and multiple copy reads. It also enables to clean paired-ends sff files and generates on one side a sff with the validated paired-ends and on the other the sequences which can be used as shotgun reads.

Availability: The PyroCleaner code is freely available on GitLab.

Publication: Mariette J, Noirot C, Klopp C. Assessment of replicate bias in 454 pyrosequencing and a multi-purpose read-filtering tool. BMC Research Notes 2011, 4:149. see


Description: RNAspace is a platform which aims at providing an integrated environment for non-coding RNA annotation. The increasing number of ncRNA discovered since 2000 and the lack of user friendly tools for finding and annotating them, have made necessary to propose to biologists an in silico environment allowing structural and functional annotations of these molecules with regard to available protein genes annotation environments. RNAspace makes available a variety of ncRNA gene finders and ncRNA databases as well as user-friendly tools to explore computed results including comparison, visualization and edition of putative RNAs. RNAspace also allows to export putative RNAs in various formats.

Availability: RNAspace is an open source project. It is developed in Python. It is copyrighted with the GNU General Public License, and is free (in the GNU sense) for all to use, and is in constant development. RNAspace is hosted at Sourceforge. It is also available as a web server at rnaspace.org.

Publication: Marie-Josée Cros, Antoine de Monte, Jérôme Mariette, Philippe Bardou, Benjamin Grenier-Boley, Daniel Gautheret, Hélène Touzet, and Christine Gaspin. RNAspace.org: an integrated environment for the prediction, annotation and analysis of ncRNA. RNA 2011 17 (11) see