Comments (4)
Yes. you can input count matrix to BITFAM. You need some way to merge the data at least. You could use cbind to concatenate the matrices from the two condition. Please make sure the order of genes are matched to each other.
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Actually, BITFAM_preprocess will also do data normalization with the same idea in Seurat.
from bitfam.
Thank you for your interest in on our model! Technically, the answer is yes. You can integrate the two datasets using the Seurat function: merge or IntegrateData. Then input the normalized data to BITFAM.
But please note that this of course depends on the question you are asking. If you are primarily interested in the difference between control and stimulation, and comparing the varying inferred TF activities, then this would be a valid approach. Let us know if you have more questions. We will gladly help.
from bitfam.
Thank you for your prompt reply! Yes, the goal is to compare TF activities between control and treatment. I was under the impression that normalization in Seurat is not required and can be done using BITFAM_preprocess function. Thank you!
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Related Issues (17)
- tiss@data HOT 2
- BITFAM_weights HOT 2
- BITFAM taking way too much time HOT 1
- Error after finishing chain1 HOT 1
- org.Mm.egPFAM is defunct. Please use select() if you need access to PFAM or PROSITE accessions. HOT 1
- Error in if (p$diagnostics$pareto_k > 1)
- Issue with BITFAM function
- BITFAM() error when interseted_TF argument is a vector of multiple genes
- Uploading your own Chip-Seq Matrix into BITFAM
- Picking a license? HOT 3
- Error while using BITFAM: Sys.setenv(R_MAKEVARS_USER = NULL) : wrong length for argument HOT 1
- BITFAM_weights HOT 2
- BITFAM doesn't run parallel HOT 1
- Error in eval(predvars, data, env) HOT 1
- Error in compileCode(f, code, language = language, verbose = verbose) HOT 1
- interseted_TFs HOT 3
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