UNLABELLED: The eukaryotic transcriptome is composed of thousands of coding and long non-coding RNAs (lncRNAs). However, we lack a software platform to identify both RNA classes in a given transcriptome. Here we introduce Annocript, a pipeline that combines the annotation of protein coding transcripts with the prediction of putative lncRNAs in whole transcriptomes. It downloads and indexes the needed databases, runs the analysis and produces human readable and standard outputs together with summary statistics of the whole analysis. AVAILABILITY AND IMPLEMENTATION: Annocript is distributed under the GNU General Public License (version 3 or later) and is freely available at https://github.com/frankMusacchia/Annocript. CONTACT: [email protected].

This paper presents an efficient blind watermark detection scheme for additive embedding (AE) based on underdetermined independent component analysis (ICA) framework. The proposed detector assumes that the host signal and the watermark obey non-Gaussian distributions and watermark embedding follows AE model. The proposed blind watermark detector employs blind source separation (BSS) for underdetermined mixtures for watermark estimation. Simulation results are presented showing that the proposed detector performs significantly better than existing correlation based blind detectors operating without suppressing the host signal interference at the detector.