Rnm =
Inm/Mean(Im)
Where n represents the sample and m represents the
protein. The raw MS data have been uploaded to the ProteomeXchange
Consortium (PXD039974) via the iProX
partner[8].
Mass spectrometry quality control detection and sample
repeatability test
To test the the quantitative repeatability of samples was tested by
three statistical analysis methods, including Pearson’s correlation
coefficient (PCC), principal component analysis (PCA), and coefficient
of variation (CV).
Bioinformatic analyses
Single sample gene set enrichment analysis (ssGSEA)
The estimation scores of the specific signaling pathways was acquired by
R package GSVA package with ssGSEA
algorithm[9]. The differences among
the three groups were identified by the Kruskal-Wallis test.
Assessment of protein expression pattern by fuzzy c-means
The overall identified proteins and the differentially expressed
proteins with similar expression patterns were grouped into different
clusters using ClusterGVis package in R
(https://github.com/junjunlab/ClusterGVis). Metascape and DAVID
databases were applied for functional enrichment. The identified
transcription factors were screened according to the earlier-published
review[10].
Weighted gene co-expression network analysis (WGCNA)
R package WGCNA is applied to identify the interested protein sets and
establish the association between protein modules and clinical
traits[11].