You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I'm trying to make cn_Proc with my own data which has 1 cell type and all have the same description.
At the step to construct C/T-specific GRNs, it is throwing an error.
The command that I'm using grnProp<-cn_make_grn(stQuery, expList, species='Hs', tfs=hsTFs)
The output I get
`healthy_liver : 24
Number of samples per CT: 24
Error in expDat[, rownames(stGRN)] : incorrect number of dimensions
In addition: Warning message:
In if (is.na(tfs)) { :
the condition has length > 1 and only the first element will be used`
The text was updated successfully, but these errors were encountered:
We have now created a web application that takes as input an expression matrix (counts, TPM, or FPKM), and sample meta-data, and performs CellNet analysis. Additionally, this tool includes analysis of many state-of-the-art differentiation protocols, so that you can benchmark your results against those commonly used methods:
I'm trying to make cn_Proc with my own data which has 1 cell type and all have the same description.
At the step to construct C/T-specific GRNs, it is throwing an error.
The command that I'm using
grnProp<-cn_make_grn(stQuery, expList, species='Hs', tfs=hsTFs)
The output I get
`healthy_liver : 24
Number of samples per CT: 24
Error in expDat[, rownames(stGRN)] : incorrect number of dimensions
In addition: Warning message:
In if (is.na(tfs)) { :
the condition has length > 1 and only the first element will be used`
The text was updated successfully, but these errors were encountered: