Thomas Naake and Wolfgang Huber
First-line data quality assessment and exploratory data analysis are integral parts of any data analysis workflow. In high-throughput quantitative omics experiments (e.g. transcriptomics, proteomics and metabolomics), after initial processing, the data are typically presented as a matrix of numbers (feature IDs × samples). Efficient and standardized data quality metrics calculation and visualization are key to track the within-experiment quality of these rectangular data types and to guarantee for high-quality datasets and subsequent biological question-driven inference.
We present MatrixQCvis, which provides interactive visualization of data quality metrics at the per-sample and per-feature level using R’s shiny framework. It provides efficient and standardized ways to analyze data quality of quantitative omics data types that come in a matrix-like format (features IDs × samples). MatrixQCvis builds upon the Bioconductor SummarizedExperiment S4 class and thus facilitates the integration into existing workflows.
MatrixQCVis is implemented in R. It is available via Bioconductor and released under the GPL v3.0 license.
Hosna is part of Strasbourg Medical School double degree programme and holds an MSc in bioinformatics from Paris-Saclay University. She joined the Huber group in January 2021 for her master’s thesis and focused on statistical method development for clustering single-cell data. Since September 2021 she is a PhD student in the group and will focus on analysing single-cell multi-omics data to study drug response in blood cancers.
Julia received her PhD in Molecular, Cell and Developmental Biology from the University of California, Santa Cruz for her work on alternative splicing and translational control in humans and primates. She joined the Huber group as data manager/ data scientist in July 2021. As a member of the DECODE project and the GHGA Team, she works on creating and maintaining research data infrastructure.
Tobias is a physician scientist and postdoctoral fellow. In April 2021, he joined a collaborative research project (SIMONA) between the Huber Group at EMBL and the Dietrich Group at the Heidelberg University Hospital. His current research focuses on understanding intratumor heterogeneity within the lymph node niche using multimodal single cell applications.
Thomas obtained his PhD in Biochemistry from the University of Potsdam, while conducting research at the Max Planck Institute of Molecular Plant Physiology in Potsdam-Golm. In November 2020 he joined the Huber group as a postdoctoral fellow. As a member of the SMART-CARE project, his research focuses on using proteomics and metabolomics data sets to understand better tumor biology, vulnerabilities, resistance mechanisms, and the recurrence of different cancer types.
Tümay studied Biotechnology at the University of Natural Resources and Life Sciences (BOKU) in Vienna. For his master thesis he worked on a high-throughput method for protein complex localization assignment at ETH Zurich. In October 2020 he joined the Huber group as a PhD student to work on the development of new statistical and machine-learning methods for the analysis of multi-omics data.
Sarah completed her PhD in Biology at Heidelberg University, where she developed mathematical models for gene expression in bacteria. Her role at EMBL is shared between the Huber group and Bio-IT (Center for Statistical Data Analysis). She will support EMBL’s scientific community in statistical data analysis by providing consulting and courses.
Alexandra obtained her BSc degree in Molecular Biotechnology from the University of Heidelberg. She wrote her Bachelor thesis at the Center for Molecular Biology of Heidelberg University (ZMBH) and is currently enrolled in the Molecular Biotechnology Master’s program of the University of Heidelberg. She joined the Huber group as a trainee in May 2020 and is working on viral sequence data in order to understand adaptive immune responses to viral infections.
Alex received his PhD in theoretical particle physics from the University of Heidelberg and the Max Planck Institute for Nuclear Physics before he joined the Huber group as postdoc fellow in February 2020. As a member of the DECODE project, his current research focuses on single-cell analyses and the development of statistical methods for biological data.
Alina has a BSc degree in Molecular Biotechnology from the University of Heidelberg. She wrote her Bachelor thesis at the Max-Planck-Institute (MPI) for Medical Research and is currently enrolled in the Molecular Biotechnology Masters program. After a research internship at the University of Queensland and an internship in the non-academic sector, Alina joined the Huber Group in January 2020. She is working on the integrative analysis of drug testing data in order to understand the mechanisms of drug response.