1 Sample Information

Analysis from the results of a label free mass spectrometry experiment on paraffin embedded samples stratified as follows:

1.1 First Batch of Samples

  • Red Blood Cells rich clot analogues (RBC): n = 3
  • Fibrin rich clot analogues (FIB): n = 4

2 Coverage Analysis

The coverage analysis result was conducted here on both the first batch of samples, and the summary statistics of the coverage score for each sample is shown on the table below.

First batch of samples
Fib1 Fib2 Fib3 Fib4 RBC1 RBC2 RBC3
Min. 0.23000 0.23000 0.19000 0.27000 0.05000 0.17000 0.19000
1st Qu. 4.37000 5.18500 4.81500 4.75500 5.17500 5.26500 6.11500
Median 12.94500 11.45500 11.83000 12.30000 12.40000 11.70000 12.59000
Mean 18.50433 16.80495 17.79908 17.26768 16.64189 16.17239 17.05987
3rd Qu. 26.50000 23.47250 25.30500 22.75500 23.10000 22.35000 23.66750
Max. 100.00000 91.55000 100.00000 93.50000 100.00000 100.00000 100.00000

3 Overlapping proteins

The Venn Diagram below was generated using the first data set show that 145 proteins are overlapping between the RBC and FIB Groups - and this intersection is used for comparison between groups, 240 proteins are unique to the RBC samples, and 95 proteins are unique to the FIB samples.

4 RBC Analysis

4.1 Pearson correlation



4.2 Network analysis

Using the correlation matrix above to extract information on the abundancy profile of the top 50 highly correlated proteins with a threshold of +/- 0.80, the network analysis was carried out and resulted in the graph below. The node size is proportional with the degree (how connected the protein is), the red edges represent positive correlation and blue edges represent negative correlation. The optimal community structure was calculated for the graph, in using the maximal modularity score. This analysis resulted in the communities represented as the node colours and shown in the table below.





5 FIB Analysis

5.1 Pearson correlation analysis



5.2 Network analysis

The same method for constructing the co-expression network used on the RBC samples was applied to the FIB dataset here, in this case using the 95 proteins unique to FIB samples from the first batch. The optimal community analysis resulted in the communities listed in the table below.

6 Differential Analysis

Here I used a linear model approach to assess differential abundance/expression between the two groups - this analysis resulted in 58 differentially abundant proteins. The tables below show the metrics of the top-ranked proteins from the linear model fit. The data was pre-processed with log-transformation and quantile normalisation to ensure that the expression distributions of each sample are similar across the entire experiment and not skewed.

6.1 Common proteins network

The differentially abundant protein scores were used to perform the coexpression analysis on the comparison between groups. The heatmap below show differentially abundant proteins and resulted in clusters that are correspondent with the sample groups.

7 Pathway Enrichment Analysis

Pathway enrichment analysis were conducted on differentially abundant proteins related RBC and FIB using the InterMineR R package. Here the pathways were tested for over-representation in each of the proteins with fold change related with RBC and FIB relative to what is expected by chance and a p-value is computed for each pathway. The plots below represent the top 10 enriched pathways for the aforementioned communities - you can hover the bars for p-value information.