High-quality analyses
AltraBio deploys its recognized expertise in bioinformatics, biostatistic and biology to provide services in the analysis and interpretation of all types of omics data (genomics, epigenomics, transcriptomics, proteomics…).
For each project, AltraBio’s team works in interaction with its clients/partners in order to reach their goals.
Expertise in biostatistics and bioinformatics
Prior to performing differential analyses, various methods are implemented to assess the quality of the data and their agreement with the experimental design. We specifically control for outliers and for effects unrelated to the design in order to correct them with the agreement of our client/partner. Thus the relevance of the performed analysis is guaranteed.
Experimental designs may consist of multiple factors (donor, cell type, treatment, dose, timepoints…) and thus can be analyzed from multiple angles. To answer the biological question(s) of the study, AltraBio determines the most suitable statistical model (paired design, batch effect correction, hidden factor estimation, weighting of outliers…).
AltraBio possesses the know-how to integrate different types of data (multi-omics, cytometry, medical data…). Supervised and unsupervised machine learning can be implemented for various applications: biomarker identification, classification, predictive models for diagnostic or response to treatment. Thus our clients benefit from our strong expertise in using up-to-date machine learning algorithms to extract the maximum value from their data.
Expertise in biology
Biological processes and pathways are identified thanks to the implementation of various and complementary methods of functional categories enrichment. These automatic results are then reviewed to assess their relevance with the biological context of the study.
Beyond providing lists of molecules and biological pathways, AltraBio’s role is also to extract meaning. To this end, the interpretation phase takes into account the biological question(s) at the origin of the study and assesses the results while integrating the biological knowledge available in the scientific literature and databases. The goal is to understand the biological mechanisms at play and to formulate new hypotheses to be validated (examples of synthetic diagrams produced by AltraBio in figures S8A and S9A of this article).
Reporting
All of the work carried out is summarized in a complete report transferred to our client/partner and explained during a video conference. This exchange makes it possible to explain the chosen methodological approaches and their results as well as to ensure that our client/partner has the best understanding of their data.
Statistical analysis results are also available in the WikiBioPath web interface which provides our clients/partners a set of visualisation and analysis tools which enables them to continue the exploration of their data. They can easily generate new volcano plots, heat maps, PCA and enrichment analyses on gene selections.
Our publications in Omics Data Analysis
2014
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.},
keywords = {},
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}
}
2013
Altintas, Dogus Murat; Allioli, Nathalie; Decaussin, Myriam; de Bernard, Simon; Ruffion, Alain; Samarut, Jacques; Vlaeminck-Guillem, Virginie
Differentially expressed androgen-regulated genes in androgen-sensitive tissues reveal potential biomarkers of early prostate cancer Journal Article
In: PLoS One, vol. 8, no. 6, pp. e66278, 2013, ISSN: 1932-6203.
@article{pmid23840433,
title = {Differentially expressed androgen-regulated genes in androgen-sensitive tissues reveal potential biomarkers of early prostate cancer},
author = {Dogus Murat Altintas and Nathalie Allioli and Myriam Decaussin and Simon de Bernard and Alain Ruffion and Jacques Samarut and Virginie Vlaeminck-Guillem},
doi = {10.1371/journal.pone.0066278},
issn = {1932-6203},
year = {2013},
date = {2013-01-01},
urldate = {2013-01-01},
journal = {PLoS One},
volume = {8},
number = {6},
pages = {e66278},
abstract = {BACKGROUND: Several data favor androgen receptor implication in prostate cancer initiation through the induction of several gene activation programs. The aim of the study is to identify potential biomarkers for early diagnosis of prostate cancer (PCa) among androgen-regulated genes (ARG) and to evaluate comparative expression of these genes in normal prostate and normal prostate-related androgen-sensitive tissues that do not (or rarely) give rise to cancer.
METHODS: ARG were selected in non-neoplastic adult human prostatic epithelial RWPE-1 cells stably expressing an exogenous human androgen receptor, using RNA-microarrays and validation by qRT-PCR. Expression of 48 preselected genes was quantified in tissue samples (seminal vesicles, prostate transitional zones and prostate cancers, benign prostatic hypertrophy obtained from surgical specimens) using TaqMan® low-density arrays. The diagnostic performances of these potential biomarkers were compared to that of genes known to be associated with PCa (i.e. PCA3 and DLX1).
RESULTS AND DISCUSSION: By crossing expression studies in 26 matched PCa and normal prostate transitional zone samples, and 35 matched seminal vesicle and PCa samples, 14 genes were identified. Similarly, 9 genes were overexpressed in 15 benign prostatic hypertrophy samples, as compared to PCa samples. Overall, we selected 8 genes of interest to evaluate their diagnostic performances in comparison with that of PCA3 and DLX1. Among them, 3 genes: CRYAB, KCNMA1 and SDPR, were overexpressed in all 3 reference non-cancerous tissues. The areas under ROC curves of these genes reached those of PCA3 (0.91) and DLX1 (0.94).
CONCLUSIONS: We identified ARG with reduced expression in PCa and with significant diagnostic values for discriminating between cancerous and non-cancerous prostatic tissues, similar that of PCA3. Given their expression pattern, they could be considered as potentially protective against prostate cancer. Moreover, they could be complementary to known genes overexpressed in PCa and included along with them in multiplex diagnostic tools.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
METHODS: ARG were selected in non-neoplastic adult human prostatic epithelial RWPE-1 cells stably expressing an exogenous human androgen receptor, using RNA-microarrays and validation by qRT-PCR. Expression of 48 preselected genes was quantified in tissue samples (seminal vesicles, prostate transitional zones and prostate cancers, benign prostatic hypertrophy obtained from surgical specimens) using TaqMan® low-density arrays. The diagnostic performances of these potential biomarkers were compared to that of genes known to be associated with PCa (i.e. PCA3 and DLX1).
RESULTS AND DISCUSSION: By crossing expression studies in 26 matched PCa and normal prostate transitional zone samples, and 35 matched seminal vesicle and PCa samples, 14 genes were identified. Similarly, 9 genes were overexpressed in 15 benign prostatic hypertrophy samples, as compared to PCa samples. Overall, we selected 8 genes of interest to evaluate their diagnostic performances in comparison with that of PCA3 and DLX1. Among them, 3 genes: CRYAB, KCNMA1 and SDPR, were overexpressed in all 3 reference non-cancerous tissues. The areas under ROC curves of these genes reached those of PCA3 (0.91) and DLX1 (0.94).
CONCLUSIONS: We identified ARG with reduced expression in PCa and with significant diagnostic values for discriminating between cancerous and non-cancerous prostatic tissues, similar that of PCA3. Given their expression pattern, they could be considered as potentially protective against prostate cancer. Moreover, they could be complementary to known genes overexpressed in PCa and included along with them in multiplex diagnostic tools.