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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools

Published on: August 21, 2019

CAP-miRSeq: a comprehensive analysis pipeline for microRNA sequencing data.

Zhifu Sun¹, Jared Evans, Aditya Bhagwate

¹Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA. sun.zhifu@mayo.edu.

|June 5, 2014

Summary

This summary is machine-generated.

We developed CAP-miRSeq, a powerful pipeline for analyzing microRNA sequencing (miRNA-seq) data. This tool efficiently processes large-scale studies, offering flexibility and reliability for miRNA research and biomarker discovery.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

MicroRNAs (miRNAs) are crucial in physiology and disease.
miRNA sequencing (miRNA-seq) is vital for research and biomarker discovery.
Current analysis tools lack scalability and flexibility for large datasets.

Purpose of the Study:

To develop a comprehensive and scalable pipeline for miRNA sequencing data analysis.
To address the computational and expertise challenges in miRNA-seq data processing.
To provide a flexible and reliable tool for large-scale miRNA studies.

Main Methods:

Developed Comprehensive Analysis Pipeline for microRNA Sequencing data (CAP-miRSeq).
Integrated read pre-processing, alignment, miRNA detection/quantification, and variant analysis.
Offered local installation or cloud deployment (Amazon Cloud) for sequential/parallel processing.

Main Results:

CAP-miRSeq handles large sample numbers efficiently, enabling speedy analyses.
Generated summary and expression reports for quality assessment and downstream analysis.
Demonstrated superior performance, flexibility, and practical utility in research.

Conclusions:

CAP-miRSeq is a powerful, flexible tool for processing and analyzing miRNA-seq data.
Scalable from few to hundreds of samples, aiding investigators and analysts.
Facilitates further investigation and discovery in miRNA research.