Developer

This pipeline is developed by the BMAP team.

Public Dataset

4 epithelial ovarian cancer (EOC) samples, 4 ovarian surface epithelium (OSE) samples and 5 fallopian tube epithelium (FTE) samples. These original datasets were downloaded from:
Proteins data ;
Phosphorylated Sites

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Introduction

Among gynecological tumor, ovarian cancer (Epithelial Ovarian Cancer, EOC) is the second most common disease and the first leading cause of death. Epithelial ovarian cancer is believed to be caused by malignant transformation of the ovarian surface, peritoneum, or fallopian tube epithelium. In recent years, the characterization of molecular determinants of cancer has advanced tremendously. Here, we reproduced some of the results of the original study.

Methods

A total of 13 independent samples were analyzed. The analysis includes unsupervised clustering of phosphorylated proteome data and unsupervised clustering and PLS-DA of differentially expressed protein data.

Results

Figure a. Unsupervised clustering of phosphorylated proteins.
Figure b. Unsupervised clustering of 49 differentially expressed proteins.
Figure c. PLS-DA (Partial Least Squares Discriminant Analysis).

Reference

Francavilla C, Lupia M, Tsafou K, et al. Phosphoproteomics of primary cells reveals druggable kinase signatures in ovarian cancer. Cell reports. 2017, 18: 3242-3256.

Versions

v2.0: Linked up with the repository system. The code and Docker image associated with this pipeline are CRS1078664142564634624 and SRS1078665690975842304, respectively.
v1.0: Contains basic analysis steps such as hierarchical clustering, correlation analysis, and partial least squares discriminant analysis.

Reproducibility

The pipeline utilizes code CRS1078664142564634624 and Docker image SRS1078665690975842304, both of which are stored in the BMAP repositories.

Usage

1. Select the application 'Proteomics analysis platform'
2. Click on the 'Analysis' button
3. Click on the 'Dowstream analysis'
4. Fill in the request parameters

5. Upload the compressed data in gz or rar format.

6. View the results