Lab of bioinformatics and computational genomics

Tools

Software and data by biobix

All Biobix code and data is released under the GNU General public license. You should be aware that some of the downloads on this page include code from other projects which is available under different license terms.

All Biobix projects are distributed WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
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Galaxy Tools

A lot of our tools can be used trough our galaxy server on: galaxy.ugent.be

MAGE, Modeller of Allelic Gene Expression

MAGE is the Modeller of Allelic Gene Expression, an R package providing extensive functions for various RNAseq-based allelic analyses. This ranges from basic tasks such as (solely) RNAseq-based genotyping, to the analysis of more complex population-level phenomena such as (differential) allelic bias, allellic divergence and (loss of) imprinting analyses. More information about what these are and how to model them using MAGE can be found in the package vignette.

DeepRibo



DeepRibo is a deep neural network created by Clauwaert. J et. al. for the annotation of Open Reading Frames (ORF) in prokaryotes using ribosome profiling data and short DNA sequences (Shine-Dalgarno region). The package is written in python 3 and uses the PyTorch library for deep learning purposes. A model has been trained and evaluated using seven ribo-seq datasets.

mQC


MappingQC is a tool to easily generate some figures which give a nice overview of the quality of the mapping of ribosome profiling data. More specific, it gives an overview of the P site offset calculation, the gene distribution and the metagenic classification. Furthermore, MappingQC does a thorough analysis of the triplet periodicity and the linked triplet phase (typical for ribosome profiling) in the canonical transcript of your data. Especially, the link between the phase distribution and the RPF length, the relative sequence position and the triplet identity are taken into account.


proBAMconvert is a conversion tool to convert common peptide identification files (mzIdentML, pepXML, mzTAB) to the proBAM or proBED format, as defined by the HUPO Proteomics Standards Initiative. In essence, proBAMconvert reads peptide identification files, maps identified peptides onto the genome and writes output into the proBAM/proBED format.

RiboZinB: A tool to identifying actively translated isoform(s) from ribosome profiling data. The case of the Zero-inflated model.



REPARATION (Ribosome Profiling Assisted (Re-)Annotation of Bacterial genomes) is a pipeline that uses ribosome profiling data for a de novo open reading frame delineation in prokaryotic (bacterial) genomes.


In recent years, increasing amounts of genomic and clinical cancer data have become publicly available through large-scale collaborative projects such as The Cancer Genome Atlas (TCGA). However, as long as these datasets are difficult to access and interpret, they are essentially useless for a major part of the research community and their scientific potential will not be fully realized. To address these issues we developed MEXPRESS, a straightforward and easy-to-use web tool for the integration and visualization of the expression, DNA methylation and clinical TCGA data on a single-gene level (http://mexpress.be).



PROTEOFORMER is a proteogenomic pipeline that delineates true in vivo proteoforms and generates a protein sequence search space for peptide to MS/MS matching.

virusScan is a methodology for the identification of viruses in these otherwise unused paired-end MBD-seq data. Viral detection is accomplished by mapping non-reference alignable reads to a comprehensive set of viral genomes.

Monoallelic gene expression is typically initiated early in the development of an organism. Dysregulation of monoallelic gene expression has already been linked to several non-Mendelian inherited genetic disorders. In humans, monoallelic DNA-methylation (MAM) is deemed to be an important regulator of monoallelic gene expression, but only few examples are known.