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

Options for batch effect in data #10

Closed
lpantano opened this issue Apr 25, 2024 · 0 comments
Closed

Options for batch effect in data #10

lpantano opened this issue Apr 25, 2024 · 0 comments
Labels
enhancement New feature or request RNAseq

Comments

@lpantano
Copy link
Contributor

RUVseq vs SVA/CombatSeq vs other -- if we are going to have a standardized option for finding and removing sources of unknown variability, we may want to first determine which of these method is best
○ Along those lines, there are QC steps that can/should be done which should be included in determining which unknown source of variation might correspond to known sources of variation in the data; this is important to avoid overfitting the model, if confounding variables are included (known or not)
§ For example, correlating SVs (or equivalent in RUVSeq) with principal components and aspects of metadata

@lpantano lpantano added enhancement New feature or request RNAseq labels Apr 25, 2024
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement New feature or request RNAseq
Projects
None yet
Development

No branches or pull requests

1 participant