Automated analysis of small RNA datasets with RAPID. Karunanithi, S., Simon, M., & Schulz, M. H. PeerJ, 7:e6710, 2019. doi abstract bibtex Understanding the role of short-interfering RNA (siRNA) in diverse biological processes is of current interest and often approached through small RNA sequencing. However, analysis of these datasets is difficult due to the complexity of biological RNA processing pathways, which differ between species. Several properties like strand specificity, length distribution, and distribution of soft-clipped bases are few parameters known to guide researchers in understanding the role of siRNAs. We present RAPID, a generic eukaryotic siRNA analysis pipeline, which captures information inherent in the datasets and automatically produces numerous visualizations as user-friendly HTML reports, covering multiple categories required for siRNA analysis. RAPID also facilitates an automated comparison of multiple datasets, with one of the normalization techniques dedicated for siRNA knockdown analysis, and integrates differential expression analysis using DESeq2. AVAILABILITY AND IMPLEMENTATION: RAPID is available under MIT license at https://github.com/SchulzLab/RAPID. We recommend using it as a conda environment available from https://anaconda.org/bioconda/rapid.
@article{karunanithi_automated_2019,
title = {Automated analysis of small {RNA} datasets with {RAPID}},
volume = {7},
issn = {2167-8359},
doi = {10.7717/peerj.6710},
abstract = {Understanding the role of short-interfering RNA (siRNA) in diverse biological processes is of current interest and often approached through small RNA sequencing. However, analysis of these datasets is difficult due to the complexity of biological RNA processing pathways, which differ between species. Several properties like strand specificity, length distribution, and distribution of soft-clipped bases are few parameters known to guide researchers in understanding the role of siRNAs. We present RAPID, a generic eukaryotic siRNA analysis pipeline, which captures information inherent in the datasets and automatically produces numerous visualizations as user-friendly HTML reports, covering multiple categories required for siRNA analysis. RAPID also facilitates an automated comparison of multiple datasets, with one of the normalization techniques dedicated for siRNA knockdown analysis, and integrates differential expression analysis using DESeq2.
AVAILABILITY AND IMPLEMENTATION: RAPID is available under MIT license at https://github.com/SchulzLab/RAPID. We recommend using it as a conda environment available from https://anaconda.org/bioconda/rapid.},
language = {eng},
journal = {PeerJ},
author = {Karunanithi, Sivarajan and Simon, Martin and Schulz, Marcel H.},
year = {2019},
pmid = {30993044},
pmcid = {PMC6462184},
keywords = {Automated sRNA analysis, Comparative analysis, Computational sRNA analysis, Eukaryotic sRNA, siRNA analysis, siRNA quantification, Small RNA analysis, sRNA, sRNA tool},
pages = {e6710},
file = {Volltext:/Users/mschulz/Zotero/storage/82RBEVVX/Karunanithi et al. - 2019 - Automated analysis of small RNA datasets with RAPI.pdf:application/pdf},
}
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