I am conducting an RNA-seq analysis for miRNAs of the GSE177044 dataset using a standard pipeline, which consists of quality control using FastQC, mapping by STAR, and counting using featureCounts. I am using the hg38 reference genome as the index file. The purpose of analyzing this dataset is to perform differential expression analysis (DEA) for miRNAs. I have heard that for DEA of miRNA RNA-seq data, everything is similar to mRNA RNA-seq data analysis except for the gtf file, which should be obtained from miRBase. So, I am using the hsa.gff3 file from the miRBase database as the annotation file in featureCounts. In mRNA RNA-seq data analysis, there is a rule that states the percentage of assigned reads to the total reads should not be lower than 50%. I want to know if it is also true for the pipeline I mentioned for RNA-seq analysis of miRNA data. I get a mapping rate higher than 90% but a counting percentage lower than 1% for each sample. I thought maybe this is normal because only miRNA reads are assigned when we use the miRNA gff file for counting. What do you think? Is it normal?