1 Intro
This report provides some basic description of the peptide identificaiton from database search.
This report can be used to quickly check the overal quality of the experiment
2 Quick Message
Number of qualified peptides: 102242
Number of experiments: 13
Experiments: F01_Fraction1, F01_Fraction2, F01_Fraction3, F01_Fraction4, F02_FractionCyto, F02_FractionEnv, F04, F05, F06, F07_Fraction1, F07_Fraction2, F07_Fraction3, F07_Fraction4
Grouping 1: group1; group2; group7
Grouping 2: control; treamtment
3 Peptide property profiling
3.1 Intensity
About this plot
- A distribution of the density across samples/experiment
- A direct and rough evidence to tell if needed to normalize across samples
3.2 Length
Why peptide length do you expect?
- Averge length of tryptic peptide is around 10.
- refer to this page for peptide length.
3.3 Score
Why peptide score do you expect?
- Different search engine usually have different score range
- High score usually means better matching quality
- Score can be used to assist spectra selection for downstream analysis
- The average score from Andromeda (from Maxquant) should be around 50
3.4 Charge States
Why charge state?
- Peptide Charge distribution is a good sign of trypsin digestion and electric spray ionization.
In a typical ESI analysis of trytic digest, most of the peptides should have 2 charges, less peptides have 3 charges, because tryptic peptides have a lysine/arginie at the C-terminal, along with N-terminal contributing another charge. A possible miscleavage will contribute the third charge.
- In the ESI procedure, peptides with 2 and more charges are easier to fragment and then identified by MS. However, too many charges will make the m/z of the peptides too small to escape the scan range, further more, it will also complicate the ms2 spectra.
- if you see more peptides with charge 3 than charge 2 state
It might indicate in-sufficient trypsin digesion, check the percentage of peptides with miss-cleavage site.
It might indicate the ESI is not sufficient/good enough.Check the distance between the ESI tip and MS oriface, if the ESI tip is dirty, if there is droplet occasionally.
3.5 Sparsity/Presence
The more peptides of Q100(100% presence across all experiment) the better quality of the data
Figure shows the number of peptide in total with more than N presence, which helps to set the presence cutoff
4 Heatmap and Hierarchical clustering
- There are 102242 features.
- With 436 100% presence across experiments (Q100).
4.1 Interactive heatmap
About this plot
- If there are more than 100 Q100 features, only the top100 will be used for this interactive plot
- if there are no Q100 features, top100 will be used with +1
- data is transformed by log10
- Scale on feature wise to be mean as 0, and sd as 1
- plot was generated by heatmaply::heatmaply
4.2 Static Heatmap
About this plot
- All Q100 features are used for this static plot, if there are no Q100, Q50 will be used, by +1
- transform by log10
- Scale on feature wise to be mean as 0, and sd as 1
- Plot was generated by complexheatmap::pheatmap
4.3 Hierarchical cluster
About this plot
- All intensity values +1
- transform by log10
- Scale on feature wise to be mean as 0, and sd as 1
- Calculate the distance between features, using euclidean method
- Do Hierarchical cluster analysis, with method = “complete”
5 PCA Analysis
5.1 PCA Contribution
- Screeplot
- Contribution
5.2 PCA without Grouping
5.2.1 2D plot
5.2.2 3D Scatterplot
5.3 Grouping: group1; group2; group7
5.3.1 2D plot
5.3.2 3D plot
5.3.3 All PC pairs
5.4 Grouping: control; treamtment
5.4.1 2D plot
5.4.2 3D plot
5.4.3 All PC pairs
6 Differential Analysis
About this section
- t-test will be performed for two samples setting, while annova will be performed for 3 and more samples
- Note that this Differential Analysis is performed on only Q100 peptides for quick profiling
- Only do analysis 1 with more than (including) two groups, 2: each group has replicates.