SAMNetWeb is a diverse platform that can integrate experimental data from a variety of experimental conditions. While originally designed to identify interactions between genetic screen 'hits' and resulting mRNA expression changes, it is a very flexible platform that can be used for multiple types of data. Here we provide examples of various ways to use SAMNetWeb using diverse data types.
|Cell Line||Phospho-proteomic hits||Differentially expressed genes|
When we run SAMNetWeb with a Gamma value of 15 using the IRefWeb interaction network and a transcriptional regulatory network derived from A549 cell lines using the Garnet protocol , we get the resulting network. From the link to the network you can visualize the proteins identified, download the original data and evaluate the DAVID enrichment of each cell line using the entire network as a background.
For this example uses mRNA and miRNA expression data from the cancer genome atlas  as inputs into SAMNetWeb. Specifically we collected predicted miRNA targets from TargetScan  of the top-expressed miRNAs in breast cancer that were highly correlated with patient prognosis. Because many miRNAs were significantly anti-correlated with mRNAs that were NOT direct targets, we used SAMNetWeb to identify putative interaction networks that can explain miRNA-mRNA anti-correlation beyond the effect miRNAs can have on predicted targets. Our inputs to SAMNet were as follows:
|microRNA||Number of predicted targets||Number of anti-correlated mRNA|
We ran SAMNet with the above inputs with a Gamma value of 18 using the IRefWeb interaction network and a transcriptional regulatory network derived from MCF7 cells . When you click to view the resulting network you can nagivate the interacting proteins as well as download the input files and view the DAVID enrichment.
1. Gosline S.J.C., Spencer S.J., Ursu O., Fraenkel E. (2012) SAMNet: a network-based approach to integrate multi-dimensional high throughput datasets, Integrative Biology, 4:1415-27.
3. Garnet Transcription Factor Regulatory Network. Code provided here
4. The TCGA Network (2012)ADD CITATION HERE
© Copyright The Fraenkel Lab 2012, Massachusetts Institute of Technology. For more information contact firstname.lastname@example.org