Closed neocaleb closed 6 years ago
Hi, what is your data? Is it scRNA-seq? Usually all genes are removed when there are no zero values in the expression matrix. Can you share your data with me?
Hi wikiselev,
Thank you for your answer. I used Pancreas scRNA-seq data obtained from Wang's 2016 diabetes paper.
As you mentioned, I found there is no zero in my input data. I think there was a normalization problem. I ran again with same data with different normalization (there exist zero now) and it well works.
Thanks for your help.
Great, I am glad it worked! Yes, Wang data has some strange normalisation. However, in general you can switch off the gene filter by setting gene_filter = FALSE
in the sc3
function. Then all genes will be used for distance calculations. Some normalisation/imputation methods completely remove zeros from the expression matrix (sometimes even introduce negative values). It makes it hard to deal with in a very general way.
Thanks. I appreciate your help.
I ran SC3 a few weeks ago. At that time, it well works and I successfully found clusters.
However, after I update R and reinstalled the SC3, I cannot run SC3 with exactly same code and same data.
I got a message "All genes were removed after the gene filter! Stopping now...".
My R version is 3.4.2 and I install recent version of SC3.
Does anyone know this problem? My script is as follows:
ann <- data.frame(cell_type1 = rep(1,dim(temp2)[2])) pd <- new("AnnotatedDataFrame", data = ann)
colnames(temp2) <- rownames(ann) sceset <- newSCESet(countData = temp2, phenoData = pd, logExprsOffset = 1) is_exprs(sceset) <- exprs(sceset) >0.1 sceset <- calculateQCMetrics(sceset) sceset <- sc3(sceset, ks = 2:10, biology = TRUE) p_data <- pData(sceset)