Hello everyone,
I would appreciate some help with my data. I want to do Differential Expression profiling for miRNA samples.
Using the miRDeep2 program and algorithm, I'm in trouble when dealing with results to make a proper table in order to use it as input for DE software such as EdgeR or DEseq2.
Which .csv should be used for read count?
miRNAs_expressed_all_samples_15_09_2017_t_07_26_27.csv
or
miRNA_expressed.csv
Also, there are duplicate values in the miRNA_expressed.csv. Should I consider the average or only one of them with highest value?
miRNA read_count precursor
ssc-let-7a 66271 ssc-let-7a-1
ssc-let-7a 66388 ssc-let-7a-2
ssc-let-7c 22747 ssc-let-7c
1 answer
You should use the miRNAs_expressed_all_samples_15_09_2017_t_07_26_27.csv as input for edgeR or DESeq.
miDeep2 runs bowtie with -a (report all alignments) and --best --strata, which means the same read will be mapped to multiple precursor miRNAs, so I believe you should use only one of the counts for each mature miRNA - I would use the one with higher counts.
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