The ICAnnoLncRNA Pipeline for a Long-Non-coding-RNA Search and Annotation in Transcriptomic Data: an Application to Maize
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Long non-coding RNAs (lncRNAs) are RNA molecules longer than 200 nucleotides that do not encode proteins. Experimental studies have shown the diversity and importance of lncRNA functions in plants. To expand knowledge about lncRNAs in other species, computational pipelines that allow for standardised data-processing steps in a mode that does not require user control up to the final result were actively developed recently. These advancements enable wider functionality for lncRNA data identification and analysis. In the present work, we propose the ICAnnoLncRNA pipeline for automatic identification, classification and annotation of plant lncRNAs in transcriptomic sequences assembled from high-throughput RNA sequencing (RNA-seq) data. In the present work, we proposed a pipeline ICAnnoLncRNA for automatic prediction, classification, and annotation of plant lncRNAs. We analysed sequences from 15 maize transcriptome libraries from different plant tissues/organs.



