Biology subjects

Triantafyllidis, A.

Publications and source records attributed to Triantafyllidis, A..

4 recordsLinked to original sources

bioRxiv2024

SMARTER-database: a tool to explore genomic diversity in small ruminants

Underutilized sheep and goat breeds have the ability to adapt to challenging environments due to their genetic composition. Integrating publicly available genomic datasets with new data will facilitate genetic diversity analyses; however, this process is complicated by important data discrepancies, such as outdated assembly versions or different data formats. Here we present the SMARTER-database, a collection of tools and scripts to standardize genomic data and metadata mainly from SNP chips arrays on global small ruminant populations with a focus on reproducibility. SMARTER-database harmonizes genotypes for about 12,000 sheep and 6,000 goats to a uniform coding and assembly version. Users can access the genotype data via FTP and interact with the metadata through a web interface or programmatically using their custom scripts, enabling efficient filtering and selection of samples. These tools will empower researchers to focus on the crucial aspects of adaptation and contribute to livestock sustainability, leveraging the rich dataset provided by the SMARTER-database. Availability & ImplementationThe code is available as open source software under the MIT license at https://github.com/cnr-ibba/SMARTER-database.

bioinformatics↗

bioRxiv2022

Mass Dynamics 2.0: An improved modular web-based platform for accelerated proteomics insight generation and decision making

Data processing is essential to reliably generate knowledge from proteomics studies. The complexity of the proteomics data, as well as the ability of research teams to adopt complex analysis pipelines, have proven to be an obstacle to effective collaboration and more efficient biological insight generation. Here, we introduce MD 2.0, a cloud- and web-based platform for quantitative proteomics data, which implements a novel analysis workspace where statistical analyses, visualizations, and external knowledge generation are integrated into a modular framework. This modularity enables researchers the flexibility to test different hypotheses, and customize and template complex proteomics analyses, thereby expediting insight generation for complex datasets. The extensible MD 2.0 environment has been built with a scalable architecture to allow rapid development of future analysis modules and enhanced tools for remote collaboration, like experiment sharing and a live chat capability. The new drag-and-drop modules allow researchers to easily and quickly assess different aspects of an experiment, including quality control, differential expression and enrichment analysis. The modularity of MD 2.0 lays the foundation to support broader community-based analytical template generation and optimized sharing and collaboration between proteomics experts and biologists, thereby accelerating research teams abilities to extract knowledge from complex proteomics datasets.

bioinformatics↗

bioRxiv2021

Mass Dynamics 1.0: A streamlined, web-based environment for analyzing, sharing and integrating Label-Free Data.

Label Free Quantification (LFQ) of shotgun proteomics data is a popular and robust method for the characterization of relative protein abundance between samples. Many analytical pipelines exist for the automation of this analysis and some tools exist for the subsequent representation and inspection of the results of these pipelines. Mass Dynamics 1.0 (MD 1.0) is a web based analysis environment that can analyze and visualize LFQ data produced by software such as Maxquant. Unlike other tools, MD 1.0 utilizes cloud-based architecture to enable researchers to store their data, enabling researchers to not only automatically process and visualize their LFQ data but annotate and share their findings with collaborators and, if chosen, to easily publish results to the community. With a view toward increased reproducibility and standardisation in proteomics data analysis and streamlining collaboration between researchers, MD 1.0 requires minimal parameter choices and automatically generates quality control reports to verify experiment integrity. Here, we demonstrate that MD 1.0 provides reliable results for protein expression quantification, emulating Perseus on benchmark datasets over a wide dynamic range. The MD 1.0 platform is available globally via: https://app.massdynamics.com/. Contactwebb@wehi.edu.au

bioinformatics↗

bioRxiv2020

Genome-wide analysis clarifies the population genetic structure of wild Gilthead Sea Bream (Sparus aurata)

Gilthead sea bream is an important target for both recreational and commercial fishing in Europe, where it is also one of the most important cultured fish. Its distribution range goes from the Mediterranean to the African and European coasts of the North-East Atlantic. So far, the genetic structure of this species in the wild has been studied with microsatellite DNA, but the pattern of differentiation could not be fully clarified. In this study, almost 1000 wild sea bream from 23 locations in the Mediterranean Sea and Atlantic ocean where genotyped at 1159 SNP markers, of which 18 potentially under selection. Neutral markers suggested the presence of a weak subdivision into three genetic clusters: Atlantic, West and East Mediterranean. This last group could be further subdivided into an Ionian/Adriatic and an Aegean group using outlier markers. Seascape analysis suggested that this differentiation was mainly due to difference in salinity, and this was also supported by preliminary genomic functional analysis. These results are of fundamental importance for the development of proper management of this species in the wild and are a first step toward the study of the potential genetic impact of the sea bream aquaculture industry.View Full Text

ecology↗