Question

can DESeq2 be used to compare these miRNA read counts from 9 samples?

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susannehoward • 0

@susannehoward-14871

Last seen 6.2 years ago

I have RNAseq data from 9 different plant samples, different cultivars of one species. I have a table of miRNA read counts for each and would like to compare the counts(expression) of these miRNAs. Can I use DESeq2 for that?

if yes:

I am essentially a non-programmer, got as far as installing the DESeq2 package in R, but the instructions on how to set up the DESeqDataSet from my excel-txt-exported table leave me completely confused, in part because I do not have timepoints or conditions. I am at a tiny university outpost, so there is nobody I can ask questions about this, any help that tells me specifically what steps are needed for my specific table would be very ,very greatly appreciated, even if this forum seems to be more for advanced questions.

	VFM131	AMP1	shv	shc	vfm411	lbc
miR156	206	256	209	215	168	243
miR159	100	100	100	100	100	100
miR160	0	2	100	105	112	104
miiR162	98	98	100	100	100	100
miR164	97	100	100	100	100	100
miR166	200	200	200	200	200	200
miR167	114	104	300	276	223	243
miR168	99	100	100	100	43	100

deseq2 rnaseq • 986 views

ADD COMMENT • link updated 6.2 years ago by Michael Love 41k • written 6.2 years ago by susannehoward • 0

score 0 · Answer 1 · 2018-01-30

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Michael Love 41k

@mikelove

Last seen 1 hour ago

United States

DESeq2 is designed for high throughput assays. Much of the statistical method involves estimation of parameters over eg 1000s of “genes”, although you can substitute there peaks, or taxa, etc. What is the dimension here? If it is not a high throughput assay, DESeq2 is not for you.

ADD COMMENT • link 6.2 years ago Michael Love 41k

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it is only about 200 miRNAs. I am trying this because it was used with miRNA in several papers that were relevant.

Is there another way to compare them, rather than just saying, this miRNA is high in this sample and low in this other sample? Anything else that I can think of for comparison would require repeated measures, but of course I have only one RNAseq result per cultivar.

ADD REPLY • link 6.2 years ago susannehoward • 0

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I’d recommend applying the vst() transformation and then looking at the simple difference btwn samples, which will represent a reliable log2 fold change (where noise at small count range is squashed). You can’t compute meaningful pvalues here.