Marie Chion

University of Cambridge | Cam · MRC Biostatistics Unit

Blood transfusion is a life-saving treatment for people with sickle cell disorder (SCD). Presently, blood is matched manually for transfusion using incomplete red cell blood type information, to minimize the immunological incompatibility between donor and patient. We are investigating alternative approaches to blood allocation that exploit extended...

Background There is interest in strategies to match recipients to red blood cell (RBC) units for transfusion using antigens beyond ABO/Rh/K with the aim of reducing rates of alloantibody formation in heavily transfused people, for example sickle cell disease (SCD) and thalassemia (THAL). However, the efficacy of different strategies, often defined...

Current statistical methods in differential proteomics analysis generally leave aside several challenges, such as missing values, correlations between peptide intensities and uncertainty quantification. Moreover, they provide point estimates, such as the mean intensity for a given peptide or protein in a given condition. The decision of whether an...

Imputing missing values is common practice in label-free quantitative proteomics. Imputation aims at replacing a missing value with a user-defined one. However, the imputation itself may not be optimally considered downstream of the imputation process, as imputed datasets are often considered as if they had always been complete. Hence, the uncertai...

Imputing missing values is a common practice in label-free quantitative proteomics. Imputation replaces a missing value by a user-defined one. However, the imputation itself is not optimally considered downstream of the imputation process. In particular, imputed datasets are considered as if they had always been complete. The uncertainty due to the...

Proteomic analysis consists of studying all the proteins expressed by a given biological system, at a given time and under given conditions. Recent technological advances in mass spectrometry and liquid chromatography make it possible to envisage large-scale and high-throughput proteomic studies.This thesis work focuses on developing statistical me...

Imputing missing values is common practice in label-free quantitative proteomics. Imputation aims at replacing a missing value with a user-defined one. However, the imputation itself may not be optimally considered downstream of the imputation process, as imputed datasets are often considered as if they had always been complete. Hence, the uncertai...

Mass spectrometry has proven to be a valuable tool for the accurate quantification of proteins. In this study, the performances of three targeted approaches, namely Selected Reaction Monitoring (SRM), Parallel Reaction Monitoring (PRM) and Sequential Windowed Acquisition of Theoretical Mass Spectra (SWATH‐MS), to accurately quantify ten potential b...

Sample preparation for quantitative proteomics is a crucial step to ensure the repeatability and the accuracy of the results. However, there is no universal method compatible with the wide variety of protein extraction buffers currently used. We have recently demonstrated the compatibility of tube-gel with SDS-based buffers and its efficiency for l...