error from estimateDispersions

[yang-william]

pd = new("AnnotatedDataFrame", data=cell) fd = new("AnnotatedDataFrame", data=gene) test = newCellDataSet(data,phenoData = pd, featureData = fd, expressionFamily=negbinomial.size()) test = estimateSizeFactors(test) test = estimateDispersions(test)

this yield the error

Error in [.data.frame(*tmp*, res$mu == 0) : undefined columns selected In addition: Warning message: Deprecated, use tibble::rownames_to_column() instead.

Any particular reason for this? Thanks.

[samvidav]

I've been getting the same error with my UMI counts matrix even after removing genes that have 0 expression.

[cakirb]

I also have the same error after using relative2abs function, converting NaN's to zero and introduce this matrix to the new CellDataSet object.

[jgarces02]

Hi Monocle's team,

I'm working with a counts matrix and I'm getting the same error (but without the tibble's warning). I've check if there is any NA, zero or Inf value but all seems to be correct, any idea that could be happening?

Thanks in advance! Best.

EDIT: I've solved it, there was a (rebel) cell with no counts (not a non-expressed gene, that I filtering previously)... but I've got this problem now:

data_monseur <- estimateDispersions(data_monseur)

Error in parametricDispersionFit(disp_table, verbose) : 
  Parametric dispersion fit failed. Try a local fit and/or a pooled estimation. (See '?estimateDispersions')

Any idea, please? I've tried add the parameter fitType = local because helped some DESeq users but it's not working for me. Thanks again!

[du822]

Hi, when I run HSMM <- estimateDispersions(HSMM), it yields this error Error in [.data.frame(*tmp*, res$mu == 0) : undefined columns selected How to solve this problem? Thanks!