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I think both these programs are just adding the same tag to every line. I don't think either cares whether it's called RG or CB
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Even if this was real data, the tiny numbers for the PC1 and PC2 indicate that the differences between the samples are all absolutely tiny.…
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Thanks for the input. I'll continue to think of more ideas that may be achievable.
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You could also try kernel PCA, which is a non-linear form of PCA, although this will be more time-consuming.
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I have unstranded RNA-seq data. Please share the tool with me, if you do not mind.
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Everything that @f1f58aed said, plus that there may be no data manipulation that will give you the clusters you expected. Sometimes there a…
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It is a good idea, though I don't see how it would work in practice.
I think you will encounter at least additional problem on top of da…
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Right now, the WT samples are clustering together, but you have one mutant sample off by itself, which could be an outlier. How did you sc…
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@yokofakun had written this: https://www.biostars.org/p/336965/
https://github.com/ruqianl/appendCB may also be useful.
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Please post information about your tool as a `tools` category post. Don't wait/ask other users to ask you.
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Sorry for the delay in my answer, I got sidetracked.
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We just developed a R package to tackle this problem.
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`bbduk.sh` can use the transcripts as input. There is a `adapters.fa` included in the `resources` directory of the distribution. You can do…
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Cross posted here (including the code used to make up the counts):
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RSEM returns a kind of p-value if you run it with the "prior-enhanced" option. Did you do that? Are you completely sure that's the value y…
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