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. 2017 Mar 21;8:322. doi: 10.3389/fpls.2017.00322

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Copyright © 2017 Yang, Sablok, Qiao, Nie and Wen.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Integrated workflow of the isomiR detection and functional analysis in isomiR2Function. (A) Shows the seed corrupt algorithm; (B) Displays the KS plots for canonical miRNAs with more than one detected isomiRs. The x-axis indicates different types of isomiRs, the y-axis indicates the abundance ratio of corresponding isomiR to the total isomiRs; (C) Shows the alignment view of isomiR detection, where the top sequence is the pre-miRNA followed by the canonical miRNA. Non-templated bases are indicated with lower case. Mod suggests the terminal drift of isomiRs; (D) Shows the differential expression analysis module using DESeq and EBSeq or intersection of the two algorithms; (E) isomiR2Function supports target prediction using CleaveLand for the PARE and transcript data both or Targetfinder for transcript data only and (F) shows the functional enrichment module of the predicted targets using the TopGO package.