i have raw read counts of miRNA gene of lung cancer downloaded from GEO. i want to analyze and want to find which genes are differentailly expressed genes among my 90 samples using DESeq2 package. i read about DESeq2 package from bioconductor tutorial and gone through the workflow. but, i didn't understand from where to start with my raw read counts? (also calculated p values)
What do you mean by "differentially expressed"? Please first explain the experimental setup of your study: how do these 90 samples differ from each other?
these 90 samples differ from each other by raw read counts. file looks like:(miRNA raw read count file)
GeneID sample1 sample2 sample3 sample4 sample5 hsa-let-7a-2-3p 24 15 23 31 19 hsa-let-7a-3p 1031 1050 1155 752 1132 hsa-let-7a-5p 922916.75 1019462.75 1147558.25 1252350.75 797239.25 hsa-let-7b-3p 901 1278 961 530 1144
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did you have the normal and and disease(e.g, cancer) dataset or not?
i hve only single file, which has this type of data
To be honest, I suspect that you might be unclear on what "differentially expressed" means.
A gene is called "differentially expressed", if it's expression strength in one type or group of samples is higher than in another type or group. So, you need at least two different groups of samples, so that you can compare one with the other.
Yeah, like @Simon said, you must have at least two types, normally, it includes normal samples and disease samples.
thank you @Simon @ huynguyen96.dnu now i havetwo file, normal file (contain 96 samples), and disease file( samples 96).