Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Identifying differentially mutated subnetworks #4

Open
jhrcook opened this issue Dec 8, 2018 · 1 comment
Open

Identifying differentially mutated subnetworks #4

jhrcook opened this issue Dec 8, 2018 · 1 comment

Comments

@jhrcook
Copy link

jhrcook commented Dec 8, 2018

Hello,
Thank you for developing this tool and making it open source. I have a question about how Hefree et al. actually identified the subnets mutated in each cluster. In the online methods, it says that the network-smoothed mutational profiles were analyzed with the non-parametric option of SAM. Were the "network-smoothed mutation profiles" produced on a per sample basis (ie. one per sample, starting with a 1 at each mutated node and RWR-smoothing from there), or were the mutational frequencies of the genes in each sample smoothed? In other words, was a network-smoothed mutational profile made for each sample separately, or was one network-smoothed mutational profile made for each cluster (more like HotNet)?

Thank you for any help you can offer,
Josh Cook

@justinkhuang
Copy link
Collaborator

Hi Josh,
If I recall correctly, a network-smoothed mutational profile is generated for each sample individually and then differential values were calculated by measuring the differential values between each cluster and all other samples not in a cluster.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants