Biology subjects

Parmigiani, L.

Publications and source records attributed to Parmigiani, L..

3 recordsLinked to original sources

bioRxiv2024

Panacus: fast and exact pangenome growth and core size estimation

MotivationUsing a single linear reference genome poses a limitation to exploring the full genomic diversity of a species. The release of a draft human pangenome underscores the increasing relevance of pangenomics to overcome these limitations. Pangenomes are commonly represented as graphs, which can represent billions of base pairs of sequence. Presently, there is a lack of scalable software able to perform key tasks on pangenomes, such as quantifying universally shared sequence across genomes (the core genome) and measuring the extent of genomic variability as a function of sample size (pangenome growth). ResultsWe introduce Panacus (pangenome-abacus), a tool designed to rapidly perform these tasks and visualize the results in interactive plots. Panacus can process GFA files, the accepted standard for pangenome graphs, and is able to analyze a human pangenome graph with 110 million nodes in less than one hour. AvailabilityPanacus is implemented in Rust and is published as Open Source software under the MIT license. The source code and documentation are available at https://github.com/marschall-lab/panacus. Panacus can be installed via Bioconda at https://bioconda.github.io/recipes/panacus/README.html. ContactLuca Parmigiani (luca.parmigiani@uni-bielefeld.de), Daniel Doerr (daniel.doerr@hhu.de).

bioinformatics↗

bioRxiv2023

EasyCircR:Detection and reconstruction of circular RNAs post-transcriptional regulatory interaction networks

Circular RNAs (circRNAs) are regulatory RNAs that play a crucial role in various biological activities and have been identified as potential biomarkers for the development of neurological disorders and cancer. CircRNAs have emerged as significant regulators of gene expression through different mechanisms, including regulation of transcription and splicing, modulation of translation, and post-translational modification. Additionally, some circRNAs function as microRNA (miRNA) sponges in the cytoplasm, enhancing the expression of target genes by suppressing miRNA activity. Although existing pipelines reconstruct circRNAs, identify miRNAs sponged by them, retrieve cascade-regulated mRNAs, and represent the regulatory interactions as complex circRNA-miRNA-mRNA networks, none of the state-of-the-art approaches can discriminate the biological level at which the mRNAs involved in the interactions are regulated. EasyCircR is a novel R package that combines circRNA detection and reconstruction with post-transcriptional gene expression analysis (exon-intron split analysis) and miRNA response element prediction. The package enables estimation and visualization of circRNA-miRNA-mRNA interactions through an intuitive Shiny application, taking advantage of the post-transcriptional regulatory nature of circRNAs and excluding unrealistic regulatory outcomes. EasyCircR source code, Docker container and user guide are available at: https://github.com/InfOmics/EasyCircR

bioinformatics↗

bioRxiv2022

Revisiting pangenome openness with k-mers

Pangenomics is the study of related genomes collectively, usually from the same species or closely related taxa. Originally, pangenomes were defined for bacterial species. After the concept was extended to eukaryotic genomes, two definitions of pangenome evolved in parallel: the gene-based approach, which defines the pangenome as the union of all genes, and the sequence-based approach, which defines the pangenome as the set of all nonredundant genomic sequences. Estimating the total size of the pangenome for a given species has been subject of study since the very first mention of pangenomes. Traditionally, this is performed by predicting the ratio at which new genes are discovered, referred to as the openness of the species. Here, we abstract each genome as a set of items, which is entirely agnostic of the two approaches (gene-based, sequence-based). Genes are a viable option for items, but also other possibilities are feasible, e.g., genome sequence substrings of fixed length k (k-mers). In the present study, we investigate the use of k-mers to estimate the openness as an alternative to genes, and compare the results. An efficient implementation is also provided.

bioinformatics↗