Scaffold 2

Scaffold 2 is an intuitive software package for visualizing and validating MS/MS protein identification data from any mass spectrometer. It allows Users to perform the following functions to increase the value of their protein spectra:

Visualize
Scaffold displays a complete, experiment-wide view of the proteins identified in a tandem mass spectrometry experiment. The side-by-side display of all the samples allows you to understand which proteins are differentially expressed. Protein identification results are displayed as probability scores, allowing you to balance the number of proteins and the confidence level of each identification. Automatic annotation of the proteins aids you in interpreting the biological relevance of your data.

Validate
Identify proteins from MS/MS data by validating Mascot*/Sequest*/X! Tandem*/Phenyx*/OMSSA, SpectraMill and other search engines. Scaffold uses proven statistical algorithms (PeptideProphet and ProteinProphet) to calculate the probability that proteins are actually in your biological samples. Detailed results help detect false positives by allowing you to focus on a protein and examine the peptide and spectra evidence supporting the identification.

Collaborate
Organize and share key MS/MS data with colleagues. With its free viewer, Scaffold makes it easy to share experimental results with colleagues. Scaffold also helps you prepare for publication, by capturing the information proteomics journals require in a paper’s methods section.

Additional features include:
- Tie protein identifications to key biological annotations
- Quantitative framework based on spectral counting
- Post-translational modification and mass tolerance filtering
- Advanced peptide assignment for protein grouping
- Improved false discovery rate estimation
- Export in ProtXML format

Scaffold Q+

Scaffold Q+ is an additional module for Scaffold 2 that enables relative quantitation across multiple iTRAQ and TMT experiments.

This module enables Users to perform the following on their quantitation data:
- Viewing of experimental trends.
- Production of heat maps highlighting up & down regulated proteins.
- Filtering and sorting of differentially expressed proteins.
- Identification of proteins that deviate from the norm.

Further Information
See Downloadable Resources for further information.

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