We have extensive expertise in human brain transcriptomic analyses using a wide variety of programing languages, which include R, Python and Bash. This expertise is reflected in the software tools that we have released throughout the years, which can be checked out below.
We are also big advocates of open science, so most of our projects have been released under a open-source licence and the code is available on GitHub.
AWS S3 Integrity Check
Bash tool to verify the integrity of a dataset uploaded/downloaded to/from an Amazon S3 bucket.
Publication: aws-s3-integrity-check: an open-source bash tool to verify the integrity of a dataset stored on Amazon S3
View Code Docker
CoExp
CoExp is a framework for the generation, deployment, sharing and exploitation of co-expression networks as annotation models of genes and their role in transcription (Botía, J.A. et al. BMC Syst Biol 2017. doi: 10.1186/s12918-017-0420-6). This family of R packages can be separately downloaded from GitHub and also managed within the CoExp website, in which all CoExp R models are available to be accessed and used for your own research.
Publication: CoExp: A Web Tool for the Exploitation of Co-expression Networks.
Visit App Back-end Code Front-end Code Docker
dasper
The aim of dasper is to detect aberrant splicing events from RNA-seq data. dasper will use as input both junction and coverage data from RNA-seq to calculate the deviation of each splicing event in a patient from a set of user-defined controls. dasper uses an unsupervised outlier detection algorithm to score each splicing event in the patient with an outlier score representing the degree to which that splicing event looks abnormal.
Publication: Detection of pathogenic splicing events from RNA-sequencing data using dasper.
Bioconductor View Code
F3UTER
Finding 3' Un-translated Expressed Regions (F3UTER) is a machine learning-based framework which leverages both genomic and tissue-specific transcriptomic features to predict previously unannotated 3'UTRs in the human genome. F3UTER was applied to transcriptomic data covering 39 human tissues studied within GTEx, enabling the identification of tissue-specific unannotated 3'UTRs for 1,513 genes.
Publication: Leveraging omic features with F3UTER enables identification of unannotated 3'UTRs for synaptic genes.
Visit App View Code
ggtranscript
ggtranscript is a ggplot2 extension that makes it easy to visualize transcript structure and annotation.
Publication: ggtranscript: an R package for the visualization and interpretation of transcript isoforms using ggplot2.
View Code
GMSCA
GMSCA (Gene Multifunctionality Secondary Co-expression Analysis) is a software tool that exploits the co-expression paradigm to increase the number of functions and cell types ascribed to a gene in bulk-tissue co-expression networks. GMSCA was applied to 27 co-expression networks derived from bulk-tissue gene expression profiling of a variety of brain tissues and cell types, increasing the overall number of predicted triplets (gene, function, cell type) by 46.73%.
Publication: Modeling multifunctionality of genes with secondary gene co-expression networks in human brain provides novel disease insights.
View Code
IntroVerse
IntroVerse is a relational database that offers an extensive catalogue on the usage of 332,571 annotated introns and a linked set of 4,679,474 novel junctions and their implied novel introns covering 32,669 different genes. IntroVerse has been generated through the analysis of 17,510 human control RNA samples across 54 tissues provided by the Genotype-Tissue Expression Consortium v8.
Publication: IntroVerse: a comprehensive database of introns across human tissues.
Visit App View Code Docker
MitoNuclearCOEXPlorer
MitoNuclearCOEXPlorer is a web tool designed to allow users to interrogate and visualise key mitochondrial-nuclear relationships in multi-dimensional brain data. MitoNuclearCOEXPlorer uses brain regions data from GTEx v6p project.
Publication: Human brain mitochondrial-nuclear cross-talk is cell-type specific and is perturbed by neurodegeneration.
Visit App View Code
ODER
The aim of ODER is to identify previously unannotated expressed regions (ERs) using RNA-sequencing data. For this purpose, ODER defines and optimises the definition of ERs, then connected these ERs to genes using junction data. In this way, ODER improves gene annotation. Gene annotation is a staple input of many bioinformatic pipelines and a more complete gene annotation can enable more accurate interpretation of disease associated variants.
Bioconductor View Code
RytenLab API
The RytenLab team also provides with a REST API, whereby it is possible to request different methods from the CoExp R framework.
Visit API View Code
vizER
vizER is a platform that enables the visualisation of individual genes for evidence of reannotation. We have two main publications associated to this app (Zhang et al. Science Advances 2020. doi: 10.1126/sciadv.aay8299) and (Nat Commun 12, 2076 (2021). doi: https://doi.org/10.1038/s41467-021-22262-5). The primary aim of vizER is to facilitate more accurate interpretation of variants and therefore, improve genetic diagnosis. vizER also allows to download complete, annotation-agnostic transcriptome definitions for 41 GTEx tissues.
Publication: Incomplete annotation has a disproportionate impact on our understanding of Mendelian and complex neurogenetic disorders .
Visit App Back-end Code Front-end Code Docker