Scran functions not found
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alva.james • 0
@alvajames-6967
Last seen 3.2 years ago
Germany

Dear All,

I am using R version 3.3.1 (R version 3.3.2 (2016-10-31)) , and trying to run the single cell workflow from here https://www.bioconductor.org/help/workflows/simpleSingleCell/#detecting-marker-genes-between-subpopulations  and when I used the functions from Scran library, its says function not found. For instance, the same happened to setSpike, findMarker functions

Any help would be great

Thank you

 

 

single-cell scran • 751 views
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Aaron Lun ★ 27k
@alun
Last seen 7 hours ago
The city by the bay

You need to use the latest version of scran (1.4.5), which requires the latest version of R (3.4.*) to be installed via biocLite. So upgrade your R installation - I always try to use the latest version of R as soon as it comes out.

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Thank you for your reply. Actually I wanted to use the FindMarker function on my RNA-seq Limma Voom result. Inorder to find the marker genes within the chosen set. Is there any channel where the Findmarker deposited like github or elsewhere ? Also I dont whether its a right apporoach to do so, my aim to get the marker genes from DE filtered set. Any suggestions on this would be great
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  1. I suggest upgrading R and installing the latest versions of all packages via biocLite. These updates often contain important bug fixes and improvements - not just for scran, but for other Bioconductor packages - and you are only hurting yourself by sticking to older versions. Sooner or later, you will need to do this, so why not now?
  2. findMarkers needs to be applied on the single-cell expression matrix, not on the limma results. The function will then identify the top set of marker genes that are DE in each group compared to each other group. (Note that the Top field in the output requires some care during interpretation, so read the documentation). You may also be interested in overlapExprs, which will give you an idea of how much the expression distributions overlap between two groups - good markers should exhibit very low overlap (values near 0 or 1).
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