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miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data
miRDeep and its varieties are widely used to quantify known and novel micro RNA (miRNA) from small RNA sequencing (RNAseq). This article describes miRDeep*, our integrated miRNA identification tool, which is modeled off miRDeep, but the precision of detecting novel miRNAs is improved by introducing...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3553977/ https://www.ncbi.nlm.nih.gov/pubmed/23221645 http://dx.doi.org/10.1093/nar/gks1187 |
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author | An, Jiyuan Lai, John Lehman, Melanie L. Nelson, Colleen C. |
author_facet | An, Jiyuan Lai, John Lehman, Melanie L. Nelson, Colleen C. |
author_sort | An, Jiyuan |
collection | PubMed |
description | miRDeep and its varieties are widely used to quantify known and novel micro RNA (miRNA) from small RNA sequencing (RNAseq). This article describes miRDeep*, our integrated miRNA identification tool, which is modeled off miRDeep, but the precision of detecting novel miRNAs is improved by introducing new strategies to identify precursor miRNAs. miRDeep* has a user-friendly graphic interface and accepts raw data in FastQ and Sequence Alignment Map (SAM) or the binary equivalent (BAM) format. Known and novel miRNA expression levels, as measured by the number of reads, are displayed in an interface, which shows each RNAseq read relative to the pre-miRNA hairpin. The secondary pre-miRNA structure and read locations for each predicted miRNA are shown and kept in a separate figure file. Moreover, the target genes of known and novel miRNAs are predicted using the TargetScan algorithm, and the targets are ranked according to the confidence score. miRDeep* is an integrated standalone application where sequence alignment, pre-miRNA secondary structure calculation and graphical display are purely Java coded. This application tool can be executed using a normal personal computer with 1.5 GB of memory. Further, we show that miRDeep* outperformed existing miRNA prediction tools using our LNCaP and other small RNAseq datasets. miRDeep* is freely available online at http://www.australianprostatecentre.org/research/software/mirdeep-star. |
format | Online Article Text |
id | pubmed-3553977 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-35539772013-01-24 miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data An, Jiyuan Lai, John Lehman, Melanie L. Nelson, Colleen C. Nucleic Acids Res Computational Biology miRDeep and its varieties are widely used to quantify known and novel micro RNA (miRNA) from small RNA sequencing (RNAseq). This article describes miRDeep*, our integrated miRNA identification tool, which is modeled off miRDeep, but the precision of detecting novel miRNAs is improved by introducing new strategies to identify precursor miRNAs. miRDeep* has a user-friendly graphic interface and accepts raw data in FastQ and Sequence Alignment Map (SAM) or the binary equivalent (BAM) format. Known and novel miRNA expression levels, as measured by the number of reads, are displayed in an interface, which shows each RNAseq read relative to the pre-miRNA hairpin. The secondary pre-miRNA structure and read locations for each predicted miRNA are shown and kept in a separate figure file. Moreover, the target genes of known and novel miRNAs are predicted using the TargetScan algorithm, and the targets are ranked according to the confidence score. miRDeep* is an integrated standalone application where sequence alignment, pre-miRNA secondary structure calculation and graphical display are purely Java coded. This application tool can be executed using a normal personal computer with 1.5 GB of memory. Further, we show that miRDeep* outperformed existing miRNA prediction tools using our LNCaP and other small RNAseq datasets. miRDeep* is freely available online at http://www.australianprostatecentre.org/research/software/mirdeep-star. Oxford University Press 2013-01 2012-12-04 /pmc/articles/PMC3553977/ /pubmed/23221645 http://dx.doi.org/10.1093/nar/gks1187 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com. |
spellingShingle | Computational Biology An, Jiyuan Lai, John Lehman, Melanie L. Nelson, Colleen C. miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data |
title | miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data |
title_full | miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data |
title_fullStr | miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data |
title_full_unstemmed | miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data |
title_short | miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data |
title_sort | mirdeep*: an integrated application tool for mirna identification from rna sequencing data |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3553977/ https://www.ncbi.nlm.nih.gov/pubmed/23221645 http://dx.doi.org/10.1093/nar/gks1187 |
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