Pavel P. Kuksa's Publications

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SPAR: small RNA-seq portal for analysis of sequencing experiments

Pavel P Kuksa, Alexandre Amlie-Wolf, \v Zivadin Katani\'c, Otto Valladares, Li-San Wang, and Yuk Yee Leung. SPAR: small RNA-seq portal for analysis of sequencing experiments. Nucleic Acids Research, 46(W1):W36–W42, 05 2018.

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Abstract

The introduction of new high-throughput small RNA sequencing protocols that generate large-scale genomics datasets along with increasing evidence of the significant regulatory roles of small non-coding RNAs (sncRNAs) have highlighted the urgent need for tools to analyze and interpret large amounts of small RNA sequencing data. However, it remains challenging to systematically and comprehensively discover and characterize sncRNA genes and specifically-processed sncRNA products from these datasets. To fill this gap, we present Small RNA-seq Portal for Analysis of sequencing expeRiments (SPAR), a user-friendly web server for interactive processing, analysis, annotation and visualization of small RNA sequencing data. SPAR supports sequencing data generated from various experimental protocols, including smRNA-seq, short total RNA sequencing, microRNA-seq, and single-cell small RNA-seq. Additionally, SPAR includes publicly available reference sncRNA datasets from our DASHR database and from ENCODE across 185 human tissues and cell types to produce highly informative small RNA annotations across all major small RNA types and other features such as co-localization with various genomic features, precursor transcript cleavage patterns, and conservation. SPAR allows the user to compare the input experiment against reference ENCODE/DASHR datasets. SPAR currently supports analyses of human (hg19, hg38) and mouse (mm10) sequencing data. SPAR is freely available at https://www.lisanwanglab.org/SPAR.

BibTeX

@article{spar2018narweb,
	Abstract = {{The introduction of new high-throughput small RNA sequencing protocols that generate large-scale genomics datasets along with increasing evidence of the significant regulatory roles of small non-coding RNAs (sncRNAs) have highlighted the urgent need for tools to analyze and interpret large amounts of small RNA sequencing data. However, it remains challenging to systematically and comprehensively discover and characterize sncRNA genes and specifically-processed sncRNA products from these datasets. To fill this gap, we present Small RNA-seq Portal for Analysis of sequencing expeRiments (SPAR), a user-friendly web server for interactive processing, analysis, annotation and visualization of small RNA sequencing data. SPAR supports sequencing data generated from various experimental protocols, including smRNA-seq, short total RNA sequencing, microRNA-seq, and single-cell small RNA-seq. Additionally, SPAR includes publicly available reference sncRNA datasets from our DASHR database and from ENCODE across 185 human tissues and cell types to produce highly informative small RNA annotations across all major small RNA types and other features such as co-localization with various genomic features, precursor transcript cleavage patterns, and conservation. SPAR allows the user to compare the input experiment against reference ENCODE/DASHR datasets. SPAR currently supports analyses of human (hg19, hg38) and mouse (mm10) sequencing data. SPAR is freely available at https://www.lisanwanglab.org/SPAR.}},
	Author = {Kuksa, Pavel P and Amlie-Wolf, Alexandre and Katani{\'c}, {\v Z}ivadin and Valladares, Otto and Wang, Li-San and Leung, Yuk Yee},
	Bib2Html_Pubtype = {Journal},
	Date-Added = {2020-03-04 12:38:03 -0500},
	Date-Modified = {2020-03-06 13:14:34 -0500},
	Doi = {10.1093/nar/gky330},
	Eprint = {https://academic.oup.com/nar/article-pdf/46/W1/W36/25110341/gky330.pdf},
	Issn = {0305-1048},
	Journal = {Nucleic Acids Research},
	Month = {05},
	Number = {W1},
	Pages = {W36-W42},
	Title = {{SPAR}: small RNA-seq portal for analysis of sequencing experiments},
	Url = {https://doi.org/10.1093/nar/gky330},
	Volume = {46},
	Year = {2018},
	Bdsk-Url-1 = {https://doi.org/10.1093/nar/gky330}}

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