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3

If you already have a reference transcriptome assembly, then you may run the Salmon tool for quantification using your RNA-seq samples. It has an automated library type inference function (https://salmon.readthedocs.io/en/latest/salmon.html#what-s-this-libtype). It might help you to determine whether the libs are stranded or not.


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Unfortunately, the stranded nature of cDNA sequencing is not typically included in the metadata attached to a project, which means that downloading a small subset of the data and checking for strand consistency (as suggested by the other answer) is often the quickest way to work that out (when that information isn't included in the methods section of the ...


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The data processing section doesn't mention using UMIs at all, so it's likely there were none (whether they'll be present depends on how the libraries are made, with lower throughput methods being less likely to include them). The values are stated as being expected counts from RSEM, which is why they're not always integers.


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Sadly the 'contact us' email at GEO didn't help at all. I ended up probably re-inventing the wheel with this script: https://gist.github.com/CholoTook/60968e3ab6d90cb8fd19be55a25592f1 YMMV


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I am sure the data is legit, you are just approaching it incorrectly. getGEO is an application for microarray data, not for digital count data such as (sc)RNA-seq, therefore what you aim to do is simply not possible by design. Unless you want to start from the raw reads why not taking the at the file named GSE116237_scRNAseq_expressionMatrix.txt.gz provided ...


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You can use Entrez Direct for this. The following returns Unique Identifiers which are just bare integers. $ geo_query='"Expression profiling by high throughput sequencing"[DataSet Type] AND ("Homo sapiens"[Organism] OR "Mus musculus"[Organism] OR "rattus norvegicus"[Organism]) AND ("2020/01/01"[PDAT] : "...


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Use GSEMatrix=FALSE, the information you want appears to be in the soft file, rather than the matrix. Yes, this is moderately annoying since it means you need two objects to describe this particular dataset.


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