AltraBio combines over 20 years of expertise in bioinformatics, biostatistics, and systems biology to analyze complex biological datasets. Based in Lyon, France, and operating globally, we support biopharma, dermo-cosmetics, and clinical researchers in transcriptomics, proteomics, epigenomics, and multi-omics integration. Whether for target discovery, mechanism-of-action deciphering, or biomarker identification, we align our analytical pipelines with your biological endpoints.
Comprehensive Omics Analytics: From Raw Sequences to Biological Discovery
Bioinformatics & Biostatistical Core Expertise
Experimental design validation, batch-effect correction, normalization, and outlier detection (RNA-Seq, proteomics) to ensure data integrity before statistical modeling.
Complex experimental designs involving multiple variables (donor, cell type, treatment, time points). We build statistical models adapted to your specific R&D questions.
Leveraged AI and machine learning techniques to cross-analyze omics, cytometry, and clinical datasets for predictive molecular signatures.
Omics Analysis Capabilities by Modality
Identification of regulated genes, alternative splicing, cell-type heterogeneity, and spatial gene regulation. Extended services: Access to NGS data generation via trusted European platform partnerships.
Protein quantification, differential expression, and post-translational modification analysis for target identification and biomarker validation.
Identification of SNPs, insertions/deletions, and structural mutations linked to phenotypic traits or drug responses.
DNA methylation profiling and chromatin accessibility analysis (ATAC-Seq) to decipher gene regulation in disease models and aging.
Systems biology approaches combining transcriptomics, proteomics, and metabolomics datasets into cohesive biological networks.
Biological Interpretation & Functional Annotation
Gene Ontology (GO), KEGG, and Reactome pathway enrichment analysis to identify key biological processes.
Moving beyond raw gene lists to provide mechanistic insights, drug target validation, and testable biological hypotheses.
Interactive Tools & Deliverables
Comprehensive documentation featuring high-resolution visualizations (volcano plots, heatmaps, PCA) and clear biological conclusions.
Dynamic exploration of your statistical results (enrichment, pathway maps, clustering) through our proprietary web interface WikiBioPath.
Two Decades of Data Science Applied to Life Sciences
Bridging the gap between raw sequencing data and actionable biological mechanisms.
« Even in the age of generative AI, Altrabio’s two decades of expertise in maths, stats, biology, and medical science remain invaluable. They don’t just talk, they do. No flashy marketing, no inflated costs, just solid, thoughtful work from study design to actionable insights. A trusted partner, for twenty years, in a world full of noise. Highly recommend working with them to make real sense of your complex biomedical and omics data. »
Accelerate Your Omics Research Today
Discuss your project requirements with our bioinformatics team.
Peer-Reviewed Publications in Omics & Systems Biology
2014
Daussy, Cécile; Faure, Fabrice; Mayol, Katia; Viel, Sébastien; Gasteiger, Georg; Charrier, Emily; Bienvenu, Jacques; Henry, Thomas; Debien, Emilie; Hasan, Uzma A; Marvel, Jacqueline; Yoh, Keigyou; Takahashi, Satoru; Prinz, Immo; de Bernard, Simon; Buffat, Laurent; Walzer, Thierry
T-bet and Eomes instruct the development of two distinct natural killer cell lineages in the liver and in the bone marrow Journal Article
In: J Exp Med, vol. 211, no. 3, pp. 563–577, 2014, ISSN: 1540-9538.
@article{pmid24516120,
title = {T-bet and Eomes instruct the development of two distinct natural killer cell lineages in the liver and in the bone marrow},
author = {Cécile Daussy and Fabrice Faure and Katia Mayol and Sébastien Viel and Georg Gasteiger and Emily Charrier and Jacques Bienvenu and Thomas Henry and Emilie Debien and Uzma A Hasan and Jacqueline Marvel and Keigyou Yoh and Satoru Takahashi and Immo Prinz and Simon de Bernard and Laurent Buffat and Thierry Walzer},
doi = {10.1084/jem.20131560},
issn = {1540-9538},
year = {2014},
date = {2014-03-01},
urldate = {2014-03-01},
journal = {J Exp Med},
volume = {211},
number = {3},
pages = {563--577},
abstract = {Trail(+)DX5(-)Eomes(-) natural killer (NK) cells arise in the mouse fetal liver and persist in the adult liver. Their relationships with Trail(-)DX5(+) NK cells remain controversial. We generated a novel Eomes-GFP reporter murine model to address this question. We found that Eomes(-) NK cells are not precursors of classical Eomes(+) NK cells but rather constitute a distinct lineage of innate lymphoid cells. Eomes(-) NK cells are strictly dependent on both T-bet and IL-15, similarly to NKT cells. We observed that, in the liver, expression of T-bet in progenitors represses Eomes expression and the development of Eomes(+) NK cells. Reciprocally, the bone marrow (BM) microenvironment restricts T-bet expression in developing NK cells. Ectopic expression of T-bet forces the development of Eomes(-) NK cells, demonstrating that repression of T-bet is essential for the development of Eomes(+) NK cells. Gene profile analyses show that Eomes(-) NK cells share part of their transcriptional program with NKT cells, including genes involved in liver homing and NK cell receptors. Moreover, Eomes(-) NK cells produce a broad range of cytokines, including IL-2 and TNF in vitro and in vivo, during immune responses against vaccinia virus. Thus, mutually exclusive expression of T-bet and Eomes drives the development of different NK cell lineages with complementary functions.},
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pubstate = {published},
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Samarut, Eric; Gaudin, Cyril; Hughes, Sandrine; Gillet, Benjamin; de Bernard, Simon; Jouve, Pierre-Emmanuel; Buffat, Laurent; Allot, Alexis; Lecompte, Odile; Berekelya, Liubov; Rochette-Egly, Cécile; Laudet, Vincent
Retinoic acid receptor subtype-specific transcriptotypes in the early zebrafish embryo Journal Article
In: Mol Endocrinol, vol. 28, no. 2, pp. 260–272, 2014, ISSN: 1944-9917.
@article{pmid24422634,
title = {Retinoic acid receptor subtype-specific transcriptotypes in the early zebrafish embryo},
author = {Eric Samarut and Cyril Gaudin and Sandrine Hughes and Benjamin Gillet and Simon de Bernard and Pierre-Emmanuel Jouve and Laurent Buffat and Alexis Allot and Odile Lecompte and Liubov Berekelya and Cécile Rochette-Egly and Vincent Laudet},
doi = {10.1210/me.2013-1358},
issn = {1944-9917},
year = {2014},
date = {2014-02-01},
urldate = {2014-02-01},
journal = {Mol Endocrinol},
volume = {28},
number = {2},
pages = {260--272},
abstract = {Retinoic acid (RA) controls many aspects of embryonic development by binding to specific receptors (retinoic acid receptors [RARs]) that regulate complex transcriptional networks. Three different RAR subtypes are present in vertebrates and play both common and specific roles in transducing RA signaling. Specific activities of each receptor subtype can be correlated with its exclusive expression pattern, whereas shared activities between different subtypes are generally assimilated to functional redundancy. However, the question remains whether some subtype-specific activity still exists in regions or organs coexpressing multiple RAR subtypes. We tackled this issue at the transcriptional level using early zebrafish embryo as a model. Using morpholino knockdown, we specifically invalidated the zebrafish endogenous RAR subtypes in an in vivo context. After building up a list of RA-responsive genes in the zebrafish gastrula through a whole-transcriptome analysis, we compared this panel of genes with those that still respond to RA in embryos lacking one or another RAR subtype. Our work reveals that RAR subtypes do not have fully redundant functions at the transcriptional level but can transduce RA signal in a subtype-specific fashion. As a result, we define RAR subtype-specific transcriptotypes that correspond to repertoires of genes activated by different RAR subtypes. Finally, we found genes of the RA pathway (cyp26a1, raraa) the regulation of which by RA is highly robust and can even resist the knockdown of all RARs. This suggests that RA-responsive genes are differentially sensitive to alterations in the RA pathway and, in particular, cyp26a1 and raraa are under a high pressure to maintain signaling integrity.},
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pubstate = {published},
tppubtype = {article}
}
Faugaret, Delphine; Amara, Amira Ben; Alingrin, Julie; Daumas, Aurélie; Delaby, Amélie; Lépolard, Catherine; Raoult, Didier; Textoris, Julien; Mège, Jean-Louis
Granulomatous response to Coxiella burnetii, the agent of Q fever: the lessons from gene expression analysis Journal Article
In: Front Cell Infect Microbiol, vol. 4, pp. 172, 2014, ISSN: 2235-2988.
@article{pmid25566510,
title = {Granulomatous response to Coxiella burnetii, the agent of Q fever: the lessons from gene expression analysis},
author = {Delphine Faugaret and Amira Ben Amara and Julie Alingrin and Aurélie Daumas and Amélie Delaby and Catherine Lépolard and Didier Raoult and Julien Textoris and Jean-Louis Mège},
doi = {10.3389/fcimb.2014.00172},
issn = {2235-2988},
year = {2014},
date = {2014-01-01},
urldate = {2014-01-01},
journal = {Front Cell Infect Microbiol},
volume = {4},
pages = {172},
abstract = {The formation of granulomas is associated with the resolution of Q fever, a zoonosis due to Coxiella burnetii; however the molecular mechanisms of granuloma formation remain poorly understood. We generated human granulomas with peripheral blood mononuclear cells (PBMCs) and beads coated with C. burnetii, using BCG extracts as controls. A microarray analysis showed dramatic changes in gene expression in granuloma cells of which more than 50% were commonly modulated genes in response to C. burnetii and BCG. They included M1-related genes and genes related to chemotaxis. The inhibition of the chemokines, CCL2 and CCL5, directly interfered with granuloma formation. C. burnetii granulomas also expressed a specific transcriptional profile that was essentially enriched in genes associated with type I interferon response. Our results showed that granuloma formation is associated with a core of transcriptional response based on inflammatory genes. The specific granulomatous response to C. burnetii is characterized by the activation of type 1 interferon pathway.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}