BiomiX, a user-friendly bioinformatic tool for democratized analysis and integration of multiomics data
Abstract Background Interpreting biological system changes requires interpreting vast amounts of multi-omics data. While user-friendly tools exist for single-omics analysis, integrating multiple omics still requires bioinformatics expertise, limiting accessibility for the broader scientific communit...
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-01-01
|
| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-024-06022-y |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841544239715975168 |
|---|---|
| author | Cristian Iperi Álvaro Fernández-Ochoa Guillermo Barturen Jacques-Olivier Pers Nathan Foulquier Eleonore Bettacchioli Marta Alarcón-Riquelme PRECISESADS Flow Cytometry Study Group, PRECISESADS Clinical Consortium Divi Cornec Anne Bordron Christophe Jamin |
| author_facet | Cristian Iperi Álvaro Fernández-Ochoa Guillermo Barturen Jacques-Olivier Pers Nathan Foulquier Eleonore Bettacchioli Marta Alarcón-Riquelme PRECISESADS Flow Cytometry Study Group, PRECISESADS Clinical Consortium Divi Cornec Anne Bordron Christophe Jamin |
| author_sort | Cristian Iperi |
| collection | DOAJ |
| description | Abstract Background Interpreting biological system changes requires interpreting vast amounts of multi-omics data. While user-friendly tools exist for single-omics analysis, integrating multiple omics still requires bioinformatics expertise, limiting accessibility for the broader scientific community. Results BiomiX tackles the bottleneck in high-throughput omics data analysis, enabling efficient and integrated analysis of multiomics data obtained from two cohorts. BiomiX incorporates diverse omics data, using DESeq2/Limma packages for transcriptomics, and quantifying metabolomics peak differences, evaluated via the Wilcoxon test with the False Discovery Rate correction. The metabolomics annotation for Liquid Chromatography-Mass Spectrometry untargeted metabolomics is additionally supported using the mass-to-charge ratio in the CEU Mass Mediator database and fragmentation spectra in the TidyMass package. Methylomics analysis is performed using the ChAMP R package. Finally, Multi-Omics Factor Analysis (MOFA) integration identifies shared sources of variation across omics data. BiomiX also generates statistics, report figures and integrates EnrichR and GSEA for biological process exploration and subgroup analysis based on user-defined gene panels enhancing condition subtyping. BiomiX fine-tunes MOFA models, to optimize factors number selection, distinguishing between cohorts and providing tools to interpret discriminative MOFA factors. The interpretation relies on innovative bibliography research on Pubmed, which provides the articles most related to the discriminant factor contributors. Furthermore, discriminant MOFA factors are correlated with clinical data, and the top contributing pathways are explored, all with the aim of guiding the user in factor interpretation. Conclusions The analysis of single-omics and multi-omics integration in a standalone tool, along with MOFA implementation and its interpretability via literature, represents significant progress in the multi-omics field in line with the “Findable, Accessible, Interoperable, and Reusable” data principles. BiomiX offers a wide range of parameters and interactive data visualization, allowing for personalized analysis tailored to user needs. This R-based, user-friendly tool is compatible with multiple operating systems and aims to make multi-omics analysis accessible to non-experts in bioinformatics. |
| format | Article |
| id | doaj-art-9110093b12c242cb997be542d763bff6 |
| institution | Kabale University |
| issn | 1471-2105 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj-art-9110093b12c242cb997be542d763bff62025-01-12T12:41:55ZengBMCBMC Bioinformatics1471-21052025-01-0126112510.1186/s12859-024-06022-yBiomiX, a user-friendly bioinformatic tool for democratized analysis and integration of multiomics dataCristian Iperi0Álvaro Fernández-Ochoa1Guillermo Barturen2Jacques-Olivier Pers3Nathan Foulquier4Eleonore Bettacchioli5Marta Alarcón-Riquelme6PRECISESADS Flow Cytometry Study Group, PRECISESADS Clinical ConsortiumDivi Cornec7Anne Bordron8Christophe Jamin9LBAI, UMR1227, Univ Brest, InsermDepartment of Analytical Chemistry, University of GranadaGENYO, Centre for Genomics and Oncological Research Pfizer, University of Granada, Andalusian Regional Government, PTS GranadaLBAI, UMR1227, Univ Brest, Inserm, Laboratory of Immunology, CHU BrestLBAI, UMR1227, Univ Brest, Inserm, Laboratory of Immunology, CHU BrestLBAI, UMR1227, Univ Brest, Inserm, Laboratory of Immunology, CHU BrestGENYO, Centre for Genomics and Oncological Research Pfizer, University of Granada, Andalusian Regional Government, PTS GranadaLBAI, UMR1227, Univ Brest, Inserm, Laboratory of Immunology, CHU BrestLBAI, UMR1227, Univ Brest, InsermLBAI, UMR1227, Univ Brest, Inserm, Laboratory of Immunology, CHU BrestAbstract Background Interpreting biological system changes requires interpreting vast amounts of multi-omics data. While user-friendly tools exist for single-omics analysis, integrating multiple omics still requires bioinformatics expertise, limiting accessibility for the broader scientific community. Results BiomiX tackles the bottleneck in high-throughput omics data analysis, enabling efficient and integrated analysis of multiomics data obtained from two cohorts. BiomiX incorporates diverse omics data, using DESeq2/Limma packages for transcriptomics, and quantifying metabolomics peak differences, evaluated via the Wilcoxon test with the False Discovery Rate correction. The metabolomics annotation for Liquid Chromatography-Mass Spectrometry untargeted metabolomics is additionally supported using the mass-to-charge ratio in the CEU Mass Mediator database and fragmentation spectra in the TidyMass package. Methylomics analysis is performed using the ChAMP R package. Finally, Multi-Omics Factor Analysis (MOFA) integration identifies shared sources of variation across omics data. BiomiX also generates statistics, report figures and integrates EnrichR and GSEA for biological process exploration and subgroup analysis based on user-defined gene panels enhancing condition subtyping. BiomiX fine-tunes MOFA models, to optimize factors number selection, distinguishing between cohorts and providing tools to interpret discriminative MOFA factors. The interpretation relies on innovative bibliography research on Pubmed, which provides the articles most related to the discriminant factor contributors. Furthermore, discriminant MOFA factors are correlated with clinical data, and the top contributing pathways are explored, all with the aim of guiding the user in factor interpretation. Conclusions The analysis of single-omics and multi-omics integration in a standalone tool, along with MOFA implementation and its interpretability via literature, represents significant progress in the multi-omics field in line with the “Findable, Accessible, Interoperable, and Reusable” data principles. BiomiX offers a wide range of parameters and interactive data visualization, allowing for personalized analysis tailored to user needs. This R-based, user-friendly tool is compatible with multiple operating systems and aims to make multi-omics analysis accessible to non-experts in bioinformatics.https://doi.org/10.1186/s12859-024-06022-yMultiomicsData integrationUser-friendlyMOFA |
| spellingShingle | Cristian Iperi Álvaro Fernández-Ochoa Guillermo Barturen Jacques-Olivier Pers Nathan Foulquier Eleonore Bettacchioli Marta Alarcón-Riquelme PRECISESADS Flow Cytometry Study Group, PRECISESADS Clinical Consortium Divi Cornec Anne Bordron Christophe Jamin BiomiX, a user-friendly bioinformatic tool for democratized analysis and integration of multiomics data BMC Bioinformatics Multiomics Data integration User-friendly MOFA |
| title | BiomiX, a user-friendly bioinformatic tool for democratized analysis and integration of multiomics data |
| title_full | BiomiX, a user-friendly bioinformatic tool for democratized analysis and integration of multiomics data |
| title_fullStr | BiomiX, a user-friendly bioinformatic tool for democratized analysis and integration of multiomics data |
| title_full_unstemmed | BiomiX, a user-friendly bioinformatic tool for democratized analysis and integration of multiomics data |
| title_short | BiomiX, a user-friendly bioinformatic tool for democratized analysis and integration of multiomics data |
| title_sort | biomix a user friendly bioinformatic tool for democratized analysis and integration of multiomics data |
| topic | Multiomics Data integration User-friendly MOFA |
| url | https://doi.org/10.1186/s12859-024-06022-y |
| work_keys_str_mv | AT cristianiperi biomixauserfriendlybioinformatictoolfordemocratizedanalysisandintegrationofmultiomicsdata AT alvarofernandezochoa biomixauserfriendlybioinformatictoolfordemocratizedanalysisandintegrationofmultiomicsdata AT guillermobarturen biomixauserfriendlybioinformatictoolfordemocratizedanalysisandintegrationofmultiomicsdata AT jacquesolivierpers biomixauserfriendlybioinformatictoolfordemocratizedanalysisandintegrationofmultiomicsdata AT nathanfoulquier biomixauserfriendlybioinformatictoolfordemocratizedanalysisandintegrationofmultiomicsdata AT eleonorebettacchioli biomixauserfriendlybioinformatictoolfordemocratizedanalysisandintegrationofmultiomicsdata AT martaalarconriquelme biomixauserfriendlybioinformatictoolfordemocratizedanalysisandintegrationofmultiomicsdata AT precisesadsflowcytometrystudygroupprecisesadsclinicalconsortium biomixauserfriendlybioinformatictoolfordemocratizedanalysisandintegrationofmultiomicsdata AT divicornec biomixauserfriendlybioinformatictoolfordemocratizedanalysisandintegrationofmultiomicsdata AT annebordron biomixauserfriendlybioinformatictoolfordemocratizedanalysisandintegrationofmultiomicsdata AT christophejamin biomixauserfriendlybioinformatictoolfordemocratizedanalysisandintegrationofmultiomicsdata |