Sofie Van Gassen
Gent
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Articles by Sofie Van Gassen
Old data, new tricks: Comprehensive computational analysis of 10 years of multi-center EuroFlow acute myeloid leukemia diagnostic immunophenotypic data
1 INTRODUCTION Acute myeloid leukemia (AML) is the second-most common type of leukemia in adults and corresponds to 5% of pediatric cancer. AML is a heterogeneous malignancy, with high inter- and intra-patient heterogeneity, both at the level of genetics and immunophenotypes, posing challenges in diagnosis, classification, risk-stratification and treatment (Dohner et al., 2022; Khoury et al., 2022).
Unraveling genotype-phenotype associations and predictive modeling of outcome in acute myeloid leukemia
1 INTRODUCTION Acute myeloid leukemia (AML) is the second-most common type of leukemia in adults. The disease's etiology involves chromosomal translocations (e.g. t[8;21][q22;q22], inv [14][p13.1;q22]), genetic mutations (e.g. NPM1, RUNX1) and epigenetic changes (e.g. demethylation) (Arber et al., 2016; Bennett et al., 1985; Döhner et al., 2010; Döhner et al., 2017; Döhner et al., 2022).
CytoNorm 2.0: A flexible normalization framework for cytometry data without requiring dedicated controls
1 INTRODUCTION Cytometry is an established technique to generate high-throughput single cell data at high speed, with relatively low costs and high accuracy [1]. However, different measurement times, cytometers and reagents, or other technical artifacts might cause large variations [2]. These technical variations are called batch effects and they complicate subsequent data analysis.
CytoNormPy enables a fast and scalable removal of batch effects in cytometry datasets.
Abstract Motivation: We present a python implementation of the widely used CytoNorm algorithm for the removal of batch effects. Results Our implementation ran up to 85% faster than its R counterpart, while being fully compatible with common single-cell data structures and -frameworks of python. We extend the previous functionality by adding common clustering algorithms and provide key visualizations of the algorithm and its evaluation.
Systemic autoimmune disease patients′ blood immunome reveals specificities and commonalities among different diagnostic entities
Abstract Background: Systemic autoimmune diseases (SADs) are characterized by internal heterogeneity, overlapping clinical symptoms, and shared molecular pathways. Therefore, they are difficult to diagnose and new tools allowing precise diagnosis are needed. Molecular-based reclassification studies enable to find patterns in a diagnosis-independent way. Objective: To evaluate the possibility of using high-content immunophenotyping for detecting patient subgroups in the context of precise treatment.
Myelodysplastic neoplasms dissected into indolent, leukaemic and unfavourable subtypes by computational clustering of haematopoietic stem and progenitor cells | Leukemia
Abstract Myelodysplastic neoplasms (MDS) encompass haematological malignancies, which are characterised by dysplasia, ineffective haematopoiesis and the risk of progression towards acute myeloid leukaemia (AML). Myelodysplastic neoplasms are notorious for their heterogeneity: clinical outcomes range from a near-normal life expectancy to leukaemic transformation or premature death due to cytopenia.
Dysregulation of developmental and cell type-specific expression of glycoconjugates on hematopoietic cells: a new characteristic of myelodysplastic neoplasms (MDS) | Leukemia
To the Editor Myelodysplastic neoplasms (MDS) are age-associated hematopoietic neoplasms characterized by myeloid dysplasia and cytopenias. Patients with MDS have a diverse clinical course, ranging from indolent conditions to acute myeloid leukemia (AML) [1]. Sequencing of leukocytes from MDS patients revealed somatic mutations that correlated with their clinical outcome.
The ORMDL3 asthma susceptibility gene regulates systemic ceramide levels without altering key asthma features in mice
To view the full text, please login as a subscribed user or purchase a subscription. Click here to view the full text on ScienceDirect. Abstract Background Genome-wide association studies in asthma have repeatedly identified single nucleotide polymorphisms in the ORM (yeast)-like protein isoform 3 (ORMDL3) gene across different populations.
Response to Orlova et al. “Science not art: statistically sound methods for identifying subsets in multi-dimensional flow and mass cytometry data sets” | Nature Reviews Immunology
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