Introduction

Genome-wide miRNA expression data can be used to study miRNA dysregulation comprehensively. Although many open-source tools for microRNA (miRNA)-seq data analyses are available, challenges remain in accurate miRNA quantification from large-scale miRNA-seq dataset. We implemented a pipeline called QuickMIRSeq for accurate quantification of known miRNAs and miRNA isoforms (isomiRs) from multiple samples simultaneously.QuickMIRSeq considers the unique nature of miRNAs and combines many important features into its implementation. First, it takes advantage of high redundancy of miRNA reads and introduces joint mapping of multiple samples to reduce computational time. Second, it incorporates the strand information in the alignment step for more accurate quantification. Third, reads potentially arising from background noise are filtered out to improve the reliability of miRNA detection. Fourth, sequences aligned to miRNAs with mismatches are remapped to a reference genome to further reduce false positives. Finally, QuickMIRSeq generates a rich set of QC metrics and publication-ready plots.The rich visualization features implemented allow end users to interactively explore the results and gain more insights into miRNA-seq data analyses. The high degree of automation and interactivity in QuickMIRSeq leads to a substantial reduction in the time and effort required for miRNA-seq data analysis.

Publications

  1. QuickMIRSeq: a pipeline for quick and accurate quantification of both known miRNAs and isomiRs by jointly processing multiple samples from microRNA sequencing.
    Cite this
    Zhao S, Gordon W, Du S, Zhang C, He W, Xi L, Mathur S, Agostino M, Paradis T, von Schack D, Vincent M, Zhang B, 2017-03-01 - BMC bioinformatics

Credits

  1. Shanrong Zhao
    Developer

    Early Clinical Development, Pfizer Worldwide Research and Development, United States of America

  2. William Gordon
    Developer

    Early Clinical Development, Pfizer Worldwide Research and Development, United States of America

  3. Sarah Du
    Developer

    Early Clinical Development, Pfizer Worldwide Research and Development, United States of America

  4. Chi Zhang
    Developer

    Early Clinical Development, Pfizer Worldwide Research and Development, United States of America

  5. Wen He
    Developer

    Early Clinical Development, Pfizer Worldwide Research and Development, United States of America

  6. Li Xi
    Developer

    Early Clinical Development, Pfizer Worldwide Research and Development, United States of America

  7. Sachin Mathur
    Developer

    Business Technology, Pfizer Worldwide Research and Development, United States of America

  8. Michael Agostino
    Developer

    Business Technology, Pfizer Worldwide Research and Development, United States of America

  9. Theresa Paradis
    Developer

    Early Clinical Development, Pfizer Worldwide Research and Development, United States of America

  10. David von Schack
    Developer

    Early Clinical Development, Pfizer Worldwide Research and Development, United States of America

  11. Michael Vincent
    Developer

    I&I Research Unit, Pfizer Worldwide Research and Development, United States of America

  12. Baohong Zhang
    Investigator

    Early Clinical Development, Pfizer Worldwide Research and Development, United States of America

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Summary
AccessionBT001353
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesPerl, R
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByBaohong Zhang