MSight

MSight transforms liquid chromatography-mass spectrometry (LC-MS) datasets into image representations to enable visualization, quality control, experimental monitoring, and comparative analysis of proteomics data.


Key Features:

  • Image construction and manipulation: Transforms raw LC-MS spectral data into detailed images and provides image-manipulation functions for focused inspection.
  • Comparative analysis of MS images: Enables systematic comparison of LC-MS images to detect differential signals across datasets.
  • Quality control and experimental monitoring: Processes LC-MS datasets as images to support quality-control checks and monitoring of experimental runs.
  • Knowledge extraction from proteomic images: Uses visualization of large-scale MS images to extract patterns and generate hypotheses from proteomic datasets.

Scientific Applications:

  • Proteomic differential analysis: Supports differential analysis of proteomic LC-MS data analogous to comparisons previously achieved with two-dimensional gels.
  • Pattern discovery in LC-MS data: Reveals patterns and differences across high-throughput LC-MS datasets that may be missed when examining individual spectra.
  • Experimental quality assessment: Facilitates assessment and monitoring of LC-MS experimental quality over time and across runs.

Methodology:

Transformation of LC-MS data into visual image formats, processing LC-MS datasets as images, and interactive navigation including zooming into specific regions of interest within those images.

Topics

Collections

Details

Tool Type:
web application
Operating Systems:
Linux, Windows, Mac
Added:
12/6/2017
Last Updated:
11/24/2024

Operations

Data Inputs & Outputs

Other operations do not define inputs or outputs.

Publications

Palagi PM, Walther D, Quadroni M, Catherinet S, Burgess J, Zimmermann‐Ivol CG, Sanchez J, Binz P, Hochstrasser DF, Appel RD. MSight: An image analysis software for liquid chromatography‐mass spectrometry. PROTEOMICS. 2005;5(9):2381-2384. doi:10.1002/pmic.200401244. PMID:15880814.

Documentation