microRNA sequencing(miRNA-seq), is the use of next-generation sequencing or massively parallel high-throughput
DNA sequencing to sequence microRNAs, also called miRNAs. miRNA-seq differs from other forms of RNA-seq in that
input material is often enriched for small RNAs.
Step 1. Reads Alignment
Step 2. Quantify known and novel micro RNA (miRNA) from small RNA sequencing (RNAseq).
Step 3. Statistical analysis: estimate variance-mean dependence in miRNA count data and test for differential expression.
Step 4. miRNA expression Analysis.
Step 5. Normalization of count datasets.
Step 6. Samples clustering.
Step 7. Target Gene prediction
Step 8. Functional Annotation (GO and pathway analysis)
****Receive full package: mapped bam files, FastQC quality insight, count expression table, and differential
miRNAs analysis, and targeted genes annotation.
At USU’s high-performance computing and bioinformatics facility, we have developed a series of parallel, multicore, CPU-based,
open-source pipelines for large-scale -omics data analysis, which enables efficient and parallel analysis of multiple datasets
in a short period of time.