Quantitative analysis can be largely divided into two different categories – label-free and labeling analysis. In this chapter, we will cover both labeling analysis and label-free analysis using peak area. For label-free analysis using spectral count, see “Identification Stat Compare” in Chapter 10. For labeling analysis, we will cover how to analyze the data in an individual experiment. To compare multiple samples statistically, users will need to employ comparison tools. The IP2 provides comprehensive statistical tools for users to find proteins/genes of interest quickly by using tables and visualization modules.
After protein identification, in the experiment page, a ‘run now’ link will appear. Click ‘run now’.
Figure 8.1.1: Quantitative analysis run
Click labeling type.
Figure 8.1.2: Select Labeling Type
Fill in quantitative parameters.
- All isotope peaks: use all isotope peaks for precursor mass
- Number of isotope peaks: users can define how many peaks to use. For example, 2 means only mono (m) and m+1 peaks are used
- High-resolution mode/Low-resolution mode: select high or low-resolution mode, and define mass tolerance.
- Enrichment: a.p.e. value is used only for 15N analysis. If users are unsure enrichment value for 15N labeled sample, try IP2 15N enrichment calculation tool.
- Maximum scan numbers: maximum number of scans for finding reconstructed chromatogram peaks. Default value 50 is recommended
- Proline conversion: If an arginine-to-proline conversion is expected in SILAC labeling, select this option (see Park SK & Liao L, Nat Methods, 2009 for more info).
- Amino acid atomic information: by default, atomic numbers are pre-defined. Please note that 57.02146 C for Carbamidomethylation was considered. Also, heavy R and K for SILAC option, for example, were considered.
Figure 8.1.3: Select Labeling Type
Click ‘view data’ to go to quant result page. Users can also click the ‘Launch Census’ button to visually navigate reconstructed chromatograms (Figure 8-4).
Figure 8.1.4: Quant view data
Figure 8.1.5:: Census viewer to interactively navigate results
In the quant result page, users can change post-parameters to re-filter the data, instead of re-running the whole quant analysis. Users can change default parameters.
- No filter: does not apply any filters
- Determinant factor: square of regression score (between heavy and light peptides) to control quality.
- Iterate outlier: apply outlier filter iteratively on peptides for the same protein
- Outlier p-value: p-value threshold to discard outlier peptides
- Correction value (natural log scale): mixing error from heavy and light samples can be corrected. To find the error, click on the ‘view ratio distribution’ link. Overall ratio distribution shows how much the graph shifts. By assuming the ratio is close to a normal distribution, users can see overall how much the graph shifts. The value can be used for correction value. Then, with a new value, click the ‘re-filter’ button. After correction, it is recommended to check changed ratio distribution
- Moving Average (Smoothing the curve): apply a smoothing function to chromatograms
- Singleton lower bound threshold: to detect singleton peptides, light/heavy ratio should be bigger than this value
- Singleton upper bound threshold: light/heavy ratio should be smaller than this value
- Singleton (Profile) score threshold: correction score between chromatogram (light and heavy combined) and normal distribution.
- Singleton peptide minimum number: minimum singleton peptide numbers per protein
- Profile score threshold: profile score for non-singleton peptides
- Discard reverse proteins: keep or discard decoy proteins
- Unique Peptide only: keep unique peptide only or not
- Retention time shift: consider retention time shift between heavy and light peptides. It may correct within this number of scans
Figure 8.1.6: Quant result page
Figure 8.1.7: Peptide Ratio
By clicking ‘Lane separator’ link, users can see an overall view of protein appearance and ratios among multiple raw files.