This is a test version of Biostars. For the public version, visit https://www.biostars.org.
a question about filtering and integrating data in Seurat3

Dear all,

I am following the analysis tutorials on Seurat 3 (on data integration and differential expression),

https://satijalab.org/seurat/v3.1/integration.html

https://satijalab.org/seurat/v3.1/immune_alignment.html

and i would have a question about the FILTERING STEP :

at which step shall I add the FILTERING (and if it makes a difference) ?

The R code that i could use is :

ctrl <- CreateSeuratObject(ctrl.data, project = CTRL)

(shall I add the Filtering at this point in the R code ?)

stim <- CreateSeuratObject(stim.data, project = STIM)

(shall I add the Filtering at this point in the R code ?)

and the next few steps :

samples.combined <- merge(x=ctrl, y = stim, project = NAME)

samples.combined.list <- SplitObject(samples.combined, split.by = "orig.ident")

samples.combined.list <- lapply(X = samples.combined.list, FUN = function(x) {

(shall I add the Filtering at this point in the R code ?)

    x <- NormalizeData(x)
    x <- FindVariableFeatures(x, selection.method = "vst", nfeatures = 2000)
})
seurat3 scrna-seq

There is no information what you want to filter.

yes, will get back with an extended piece of R code ..

0 answers

No answers yet.

Log in to answer this question.