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Bioinformatic Analysis of MicroRNA Sequencing Data

Part of the Methods in Molecular Biology book series (MIMB,volume 1751)

Abstract

The vital role of microRNAs (miRNAs) involved in gene expression regulation has been confirmed in many biological processes. With the growing power and reducing cost of next-generation sequencing, more and more researchers turn to apply this high-throughput method to solve their biological problems. For miRNAs with known sequences, their expression profiles can be generated from the sequencing data. It also allows us to identify some novel miRNAs and explore the sequence variations under different conditions. Currently, there are a handful of tools available to analyze the miRNA sequencing data with separated or combined features, such as reads preprocessing, mapping and differential expression analysis. However, to our knowledge, a hands-on guideline for miRNA sequencing data analysis covering all steps is not available. Here we will utilize a set of published tools to perform the miRNA analysis with detailed explanation. Particularly, the miRNA target prediction and annotation may provide useful information for further experimental verification.

Key words

  • MicroRNAs
  • miRNAs
  • Bioinformatic
  • R
  • mirPRo
  • Small RNA sequencing

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Correspondence to Xiaonan Fu or Daoyuan Dong .

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Fu, X., Dong, D. (2018). Bioinformatic Analysis of MicroRNA Sequencing Data. In: Wang, Y., Sun, Ma. (eds) Transcriptome Data Analysis. Methods in Molecular Biology, vol 1751. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7710-9_8

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  • DOI: https://doi.org/10.1007/978-1-4939-7710-9_8

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7709-3

  • Online ISBN: 978-1-4939-7710-9

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