MassDash: A Web-Based Dashboard for Data-Independent Acquisition Mass Spectrometry Visualization.
Justin C SingJoshua CharkowMohammed AlHigaylanIra HoreckaLeon XuHannes L RöstPublished in: Journal of proteome research (2024)
With the increased usage and diversity of methods and instruments being applied to analyze Data-Independent Acquisition (DIA) data, visualization is becoming increasingly important to validate automated software results. Here we present MassDash, a cross-platform DIA mass spectrometry visualization and validation software for comparing features and results across popular tools. MassDash provides a web-based interface and Python package for interactive feature visualizations and summary report plots across multiple automated DIA feature detection tools, including OpenSwath, DIA-NN, and dreamDIA. Furthermore, MassDash processes peptides on the fly, enabling interactive visualization of peptides across dozens of runs simultaneously on a personal computer. MassDash supports various multidimensional visualizations across retention time, ion mobility, m / z , and intensity, providing additional insights into the data. The modular framework is easily extendable, enabling rapid algorithm development of novel peak-picker techniques, such as deep-learning-based approaches and refinement of existing tools. MassDash is open-source under a BSD 3-Clause license and freely available at https://github.com/Roestlab/massdash, and a demo version can be accessed at https://massdash.streamlit.app.
Keyphrases
- deep learning
- machine learning
- mass spectrometry
- big data
- electronic health record
- artificial intelligence
- convolutional neural network
- high throughput
- data analysis
- loop mediated isothermal amplification
- high resolution
- high performance liquid chromatography
- psychometric properties
- capillary electrophoresis
- single cell
- tandem mass spectrometry
- simultaneous determination