Question: Smart-seq2 single-cell RNA-Seq
0
gravatar for wangdp123
4 months ago by
wangdp123140
Oxford
wangdp123140 wrote:

Hi there,

The data generated from Smart-seq2 single-cell RNA-Seq protocol seems to have very unbalanced gene expression values. For example, if you did the differential gene expression test, you would find out many genes are only present in one sample group. Is this normal?

I wonder if there are some specific pipelines including some normalization procedure to deal with these data?

Or alternatively, can we use the pipeline of handling the bulk RNA-Seq such as Tophat2 + Cufflink + Cuffdiff or STAR + Featurecount + DESeq2 to analyze the data from Smart-seq2 single-cell RNA-Seq protocol?

Many thanks,

Tom

ADD COMMENTlink modified 4 months ago by kristoffer.vittingseerup1.6k • written 4 months ago by wangdp123140
0
gravatar for kristoffer.vittingseerup
4 months ago by
European Union
kristoffer.vittingseerup1.6k wrote:

That depends on what a "sample group" is? How do you analyze the data now?

I would suggest you Salmon to quantify the data and use Seurat to do the QC with a special focus on batch correction!

For DE analysis tool I suggest you take a look at Soneson et al 2018's recent benchmark.

ADD COMMENTlink written 4 months ago by kristoffer.vittingseerup1.6k
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