SSN Version 1
SSN: Sample-Specific Network (SSN) method, is a statistical method to construct individual-specific networks based on molecular expressions of a single sample. This method can characterize various human diseases at a network level. In particular, such SSNs can lead to the identification of individual-specific disease modules as well as driver genes, even without gene sequencing information.
Input Parameters
How to cite
[1] Yu X, Zhang J, Sun S, Zhou X, Zeng T, Chen L. Individual-specific edge-network analysis for disease prediction.Nucleic Acids Res. 2017 Nov 16;45(20):e170. doi: 10.1093/nar/gkx787. [PMID=28981699]
[2] Liu X, Wang Y, Ji H, Aihara K, Chen L. Personalized characterization of diseases using sample-specific networks. Nucleic Acids Res. 2016 Dec 15;44(22):e164. Epub 2016 Sep 4. [PMID=27596597]
Help information

Version 1
/share_bio/nas4/leofs/biocloud/script/SSN_construction_code/ -ref -background -sample -pvalue|-threshold -out
-ref                    The expression profile of reference samples
-background     Background network to calculate the deltaPCC of edges based on the network
-sample            The expression profile for the sample to be constructed the SSN
-pvalue             Set the threshold of p-value [0..1], if the -pvalue set 1, all edges will be outputted to the SSN
-threshold        Set the threshold value of the absolute value of deltaPCC [0..2]

Parameters Description
-Ref Reference sample
the expression profile of reference samples
-B background network
background network to calculate the deltaPCC of edges based on the network
-S Profile for sample
the expression profile for the sample to be constructed the SSN
-P Pvalue
set the threshold of p-value [0..1], if the -pvalue set 1, all edges will be outputted to the SSN
-T: Threshold
set the threshold value of the absolute value of deltaPCC [0..2]