One-stop proteomics data analysis platform

From protein identification to functional analysis, data analysis is at your fingertips

Run on a single computer, local HPC computing or cloud computing. It's your choice.

Run data analysis from anywhere without software installation

Our Partners

Organize your data in one place and never lose them

Maximize Protein Identification

Xu T, et al. ProLuCID: An improved SEQUEST-like algorithm with enhanced sensitivity and specificity. Journal of Proteomics, 2015
Xu T, et al. ProLuCID, a fast and sensitive tandem mass spectra-based protein identification program, Mol Cell Proteomics, 5, S174 (2006)

Label-free analysis

  • Retention time and accurate mass based alignment
  • Ion Injection Time correction
  • Curve fitting
  • Compare multiple samples to find regulated proteins

IP2 vs. MaxQuant vs. Spectral Count comparison

Protein log2(ratio) distribution
Data: Hela sample 1ug vs 100 ng, Thermo Orbitrap Fusion, single phase 2 hrs run

Isobaric Labeling TMT/iTRAQ analysis

  • User defined number of reporter ions (e.g. 10-plex TMT)
  • MS3-based multi-notch analysis (support Thermo Orbitrap Fusion Lumos)
  • Single and multiple experiment normalization

multiple peptides for each protein

Labeling Analysis (SILAC, 15N, Dimethyl, etc.)

Statistically compare multiple samples at the protein, peptide or PTM level, and group proteins in genes

Clustering Analysis

Easily cluster/group proteins using expression patterns for different conditions (time course, different treatments, drug dosage, etc.)

PTM Analysis

  • Localization score
  • PTM sites comparison among different samples
  • PTM vs non-PTM peptide comparison
  • Click to find more info

Data Quality Control

Data quality is important for reliable data analysis. IP2 software includes tools to help maximize data quality, such as delta mass corrector

* precursor purity within isolation window (m/z)
* precursor charge state
* precursor m/z
* precursor M+H+
* precursor intensity
* average precursor intensity by retention time
* number of ms2 by retention time
* ms2 base peak intensity
* average intensity of peaks with S/N > 3 in ms2 scan
* number of ms1 scans
* number of ms2 scans
* ms1 ion injection time
* ms2 ion injection time
* average ms1 ion injection time by retention time
* average ms2 ion injection time by retention time
* number of peaks in ms1 scan
* number of peaks in ms2 scan
* average number of peaks in ms1 scan by retention time
* average number of peaks in ms2 scan by retention time

Functional Analysis

  • Pathway Analysis
  • Gene Ontology
  • BioGPS

Robinson PN, et. al., Bioinformatics. 2004 Apr 12
Wu C., et.al., Nucl. Acids Res. 2016, 44
Fabregat A, et.al., Nucleic Acids Res. 2016 Jan

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