Biology subjects

Lubiana, T.

Publications and source records attributed to Lubiana, T..

7 recordsLinked to original sources

bioRxiv2026

scFAIR Consortium: a decentralized hub for single-cell RNA-Seq data standardization and unification

The rapid accumulation of single-cell RNA-Seq (scRNA-seq) data across multiple repositories presents major challenges for data accessibility, integration, and reproducibility. While primary repositories provide raw data, they rarely include structured cell-type annotations or descriptions of analytical workflows, limiting the ability to reuse and integrate datasets in a FAIR (Findable, Accessible, Interoperable, Reusable) manner. Here we present scFAIR, a consortium of single-cell data resources that has developed a unified metadata schema and common curation framework to improve the FAIRness of scRNA-seq data. Building on and extending the CZ CELLxGENE Discover metadata schema, the scFAIR consortium has been instrumental in driving key schema improvements, including the expansion of supported organisms, richer biological context, and structured reporting of computational workflows. To provide unified access to decentralized datasets, the consortium developed the sc-fair.org portal, which currently aggregates 2,346 datasets across partner resources through ontology-aware semantic search. We demonstrate the practical value of FAIR-compliant datasets through a cross-species validation between human and mouse Allen Brain Atlases, showing that standardized ontology annotations enable reliable annotation transfer across species, with 90% of neuronal clusters receiving an exact or equivalent label. Together, the scFAIR schema, validator, and portal constitute a community-driven framework that advances single-cell data standardization and lays the foundation for reproducible, large-scale integration of single-cell datasets.

bioinformatics↗

bioRxiv2024

Bringing PanglaoDB to 5-star Linked Open Data using Wikidata

PanglaoDB is a database of cell-type markers widely used for single-cell RNA sequencing data analysis. However, cell types and genes in the database are encoded by free text, lacking proper identifiers. Wikidata, is a freely editable knowledge graph database useful for integrating biomedical knowledge. We thus reasoned that porting PanglaoDBs markers to the platform could improve their reusability and overall technical quality (FAIRness). We mapped 188 cell types from PanglaoDB to species-neutral terms on Wikidata and created 376 species-specific terms for cell types in Homo sapiens and Mus musculus. These terms were enriched with marker information via the has marker (P8872) property, totaling over 15.000 cell type X marker associations (w.wiki/9iw6). We explored this new subset of the graph via SPARQL queries, illustrating the discovery potential of structured, integrated knowledge. For example, we found a previously unexplored link between rosehip neurons, clozapine, and schizophrenia via the HRH1 marker. Besides the graph-based insights, we took time to describe the details of the reconciliation process, hoping to stimulate more resources for a move to a 5-star linked open data format.

bioinformatics↗

bioRxiv2022

Mapping the content of comments on bioRxiv and medRxiv preprints

IntroductionPreprints have been increasingly used in biomedical sciences, providing the opportunity for research to be publicly assessed before journal publication. With the increase in attention over preprints during the COVID-19 pandemic, we decided to assess the content of comments left on preprint platforms. MethodsPreprints posted on bioRxiv and medRxiv in 2020 were accessed through each platforms API, and a random sample of preprints that had received between 1 and 20 comments was analyzed. Comments were evaluated in triplicate by independent evaluators using an instrument that assessed their features and general content. Results7.3% of preprints received at least 1 comment during a mean follow-up of 7.5 months. Analyzed comments had a median size of 43 words. Criticisms, corrections or suggestions were the most prevalent type of content, followed by compliments or positive appraisals and questions. Most critical comments regarded interpretation, data collection and methodological design, while compliments were usually about relevance and implications. ConclusionsOnly a small percentage of preprints posted in 2020 in bioRxiv and medRxiv received comments in these platforms. When present, however, these comments address content that is similar to that analyzed by traditional peer review. A more precise taxonomy of peer review functions would be desirable to describe whether post-publication peer review fulfills these roles.

scientific communication and education↗

bioRxiv2022

WikiGOA: Gene set enrichment analysis based on Wikipedia and the Gene Ontology

O_LIGene sets curated to Gene Ontology terms are widely used by the transcriptomics community C_LIO_LIPresence in Wikipedia is a common proxy for the relevance of a concept. C_LIO_LIIn this work, we describe the use of Wikidata to generate a dataset comprising only gene sets with a corresponding Wikipedia page. C_LIO_LIWe refer to the dataset as "WikiGOA", standing for "Wikipedia Gene Ontology Annotations" C_LIO_LIWe use the dataset to analyze gene expression data and show that it provides readily understandable results. C_LIO_LIWe envision WikiGOA to be useful for exploring complex biological datasets both in academic research and educational contexts. C_LI NoteThis report was written in a non-standard, experimental format, where assertions are expressed in bullet points. This was done to clarify statements and assumptions, simplify reading and pave the way for conversion to structured formats (e.g., nanopublications). [1]

bioinformatics↗

bioRxiv2022

The Bioregistry: Unifying the Identification of Biomedical Entities through an Integrative, Open, Community-driven Metaregistry

The standardized identification of biomedical entities is a cornerstone of interoperability, reuse, and data integration in the life sciences. Several registries have been developed to catalog resources maintaining identifiers for biomedical entities such as small molecules, proteins, cell lines, and clinical trials. However, existing registries have struggled to provide sufficient coverage and metadata standards that meet the evolving needs of modern life sciences researchers. Here, we introduce the Bioregistry, an integrative, open, community-driven metaregistry that synthesizes and substantially expands upon 23 existing registries. The Bioregistry addresses the need for a sustainable registry by leveraging public infrastructure and automation, and employing a progressive governance model centered around open code and open data to foster community contribution. The Bioregistry can be used to support the standardized annotation of data, models, ontologies, and scientific literature, thereby promoting their interoperability and reuse. The Bioregistry can be accessed through https://bioregistry.io and its source code and data are available under the MIT and CC0 Licenses at https://github.com/biopragmatics/bioregistry.

bioinformatics↗

bioRxiv2021

Using coexpression to explore cell-type diversity with the fcoex package

Here, we present the fcoex package, which infers coexpression from scRNA-seq data and yields multiple, overlapping classes of cells based on coexpression modules. The tool extends the current scRNA-seq toolbox, providing a multi-hierarchy view on cell functionality and enabling the development of more complete cell atlases. Single-cell RNA sequencing (scRNA-seq) captures details of the cellular landscape, basing a fine-grained view on biological processes. Current pipelines, however, are restricted to single-label perspectives, missing details of the classification landscape. In the pbmc3k blood cell dataset, fcoex detects known classes, like antigen-presenting cells and a new theoretical group of cells, marked by the expression of FCGR3A (CD16). Fcoex extends the current scRNA-seq toolbox, providing a multi-hierarchy view on cell functions as a tool to develop complete cell type atlases. Availability and ImplementationFcoex is written in R and openly available in Bioconductor (https://bioconductor.org/packages/fcoex/). Supplementary informationSupplementary data is available at the end of the manuscript. Source code for analysis is available at https://github.com/csbl-inovausp/fcoex_analysis;

systems biology↗

bioRxiv2018

Zebrafish sp7 mutants show tooth cycling independent of attachment, eruption and poor differentiation of teeth

The capacity to fully replace teeth continuously makes zebrafish an attractive model to explore regeneration and tooth development. The requirement of attachment bone for the appearance of replacement teeth has been hypothesized but not yet investigated. The transcription factor sp7 (osterix) is known in mammals to play an important role during odontoblast differentiation and root formation. Here we study tooth replacement in the absence of attachment bone using sp7 zebrafish mutants. We analysed the pattern of tooth replacement at different stages of development and demonstrated that in zebrafish lacking sp7, attachment bone is never present, independent of the stage of tooth development or fish age, yet replacement is not interrupted. Without bone of attachment we observed abnormal orientation of teeth, and abnormal connection of pulp cavities of predecessor and replacement teeth. Mutants lacking sp7 show arrested dentinogenesis, with non-polarization of odontoblasts and only a thin layer of dentin deposited. Osteoclast activity was observed in sp7 mutants; due to the lack of bone of attachment, remodelling was diminished but nevertheless present along the pharyngeal bone. We conclude that tooth replacement is ongoing in the sp7 mutant despite poor differentiation and defective attachment. Without bone of attachment tooth orientation and pulp organization are compromised.

developmental biology↗