[6] Chion, M. & Leroy, A. (2023). A Bayesian Framework for Multivariate Differential Analysis accounting for Missing Data. arXiv:2307.08975.
[5] Chion, M., Carapito, C. & Bertrand, F. (2023). Towards a more accurate differential analysis of multiple imputed proteomics data with mi4limma. In: Burger, T. (eds) Statistical Analysis of Proteomic Data: Methods and Tools. Vol. 2426, Methods in Molecular Biology, Humana Press, New York, NY.
[4] Chion, M., Carapito, C. & Bertrand, F. (2022). Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics. PLOS Computational Biology. 18(8): e1010420.
[3] Bons, J., Husson, G., Chion, M., Bonnet, M., Maumy‐Bertrand, M., Delalande, F., Cianférani, S., Bertrand, F., Picard, B. & Carapito, C. (2021). Combining label‐free and label‐based accurate quantifications with SWATH‐MS: comparison with SRM and PRM for the evaluation of bovine muscle type effects. Proteomics. 21:e2000214.
[2] Quibel, L., Helluy, P., Chion, M. & Ricka, P. (2019). Mélanger des gaz raides pour créer de nouvelles lois d’état. hal-02114552.
[1] Muller, L., Fornecker, L., Chion, M., Van Dorsselaer, A., Cianférani, S., Rabilloud, T. & Carapito, C. (2018). Extended investigation of tube-gel sample preparation: a versatile and simple choice for high throughput quantitative proteomics. Scientific Reports. 8:8260.
ProteoBayes: Bayesian Statistical Tools for Quantitative
Proteomics
Webpage |
GitHub |
R package |
Web app
mi4p: Multiple Imputation for Proteomics
Webpage |
GitHub |
R package
Chion, M. & Leroy, A. ProteoBayes: a Bayesian framework for differential proteomics analysis. BSPR-EuPA Conference – July 17-20, 2023 – Newcastle-upon-Tyne, UK.
Chion, M., Bons, J., Bonnet, M., Maumy-Bertrand, M., Carapito, C. & Bertrand, F.: Modèle de régression par spline monotone pour données de protéomique quantitative. 52e Journées de Statistique – June 7-11, 2021 – Online.
Chion, M., Bons, J., Bonnet, M., Maumy-Bertrand, M., Carapito, C. & Bertrand, F.: Using monotone spline smoothing to combine label-free and label-based accurate quantifications with DIA-MS: application to bovine muscle samples. e-Chimiométrie 2021 – February 2-3, 2021 – Online.
Chion, M., Carapito, C. & Bertrand, F.: Dealing with imputation-caused variance using moderated t-test. UseR! 2020 – Cancelled due to COVID-19.
Chion, M., Carapito, C. & Bertrand, F.: Imputation multiple et prise en compte de l'incertitude pour les données de protéomique quantitative. 51e Journées de Statistique – June 3-7, 2019 – Nancy, France.
Chion, M. Getting involved in the scientific community as an early career researcher. 3rd EuPA ECR Day – October 5, 2023 – Online.
Chion, M. & Leroy, A. ProteoBayes: a Bayesian framework for differential proteomics analysis. Lilley Lab Seminar – July 27, 2023 – Cambridge, UK.
Chion, M.: Enseigner la statistique aux non-spécialistes: retour d'expérience en sciences de la vie et en psychologie. 54e Journées de Statistique – July 3-7, 2023 – Brussels, Belgium.
Chion, M.: Missing values and multiple imputation: application to quantitative proteomics. Applied Statistics Workshop - November 4, 2022 - UCLouvain, Belgium.
Chion, M.: From multiple imputation to Bayesian framework in quantitative proteomics. Journée Statistique et Sciences de la Santé – June 26, 2022 – Lille, France.
I also had the opportunity to present the work I have done during my PhD studies at several seminars.
Chion, M., Carapito, C. & Bertrand, F.: Dealing with imputation-caused variance in label-free quantitative proteomics data. May Institute on Computation and statistics for mass spectrometry and proteomics at Northeastern University – April 27 - May 8, 2020 – Boston, MA, États-Unis.
Chion, M., Carapito, C. & Bertrand, F.: Imputation multiple et prise en compte de l'incertitude pour les données de protéomique quantitative. Journées Statistique & Santé – October 10-11, 2019 – Paris, France.
Chion, M., Muller, L., Pythoud, N., Bertrand, F. & Carapito, C.: Dealing with imputation-caused variance in label-free quantitative proteomics data. SMAP 2019 – September 16-19, 2019 – Strasbourg, France.
Chion, M., Carapito, C. & Bertrand, F.: Imputation multiple et prise en compte de l'incertitude pour les données de protéomique quantitative. 1er Symposium du Groupement de Recherche MaDICS – June 26-28, 2019 – Rennes, France.