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.
Australian Prostate Cancer Research Centre-Queensland, Institute of Health and Biomedical Innovation (IHBI), Queensland University of Technology, Princess Alexandra Hospital, Queensland, QLD 4102, Australia. j.an@qut.edu.au
%0 Journal Article
%1 An2013
%A An, Jiyuan
%A Lai, John
%A Lehman, Melanie L.
%A Nelson, Colleen C.
%D 2013
%J Nucleic Acids Res
%K highthroughput gene-expression
%N 2
%P 727--737
%R 10.1093/nar/gks1187
%T miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data.
%U http://dx.doi.org/10.1093/nar/gks1187
%V 41
%X 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.
@article{An2013,
abstract = {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.},
added-at = {2013-03-07T22:04:20.000+0100},
author = {An, Jiyuan and Lai, John and Lehman, Melanie L. and Nelson, Colleen C.},
biburl = {https://www.bibsonomy.org/bibtex/25ab767c5258acae18fce437ac89dc85d/aorchid},
doi = {10.1093/nar/gks1187},
file = {:allorejection/NucleicAcidsRes.41.727.pdf:PDF},
groups = {public},
institution = {Australian Prostate Cancer Research Centre-Queensland, Institute of Health and Biomedical Innovation (IHBI), Queensland University of Technology, Princess Alexandra Hospital, Queensland, QLD 4102, Australia. j.an@qut.edu.au},
interhash = {512478671cece5f91e0db7e85067e44d},
intrahash = {5ab767c5258acae18fce437ac89dc85d},
journal = {Nucleic Acids Res},
keywords = {highthroughput gene-expression},
language = {eng},
medline-pst = {ppublish},
month = Jan,
number = 2,
pages = {727--737},
pii = {gks1187},
pmid = {23221645},
timestamp = {2013-03-07T22:04:20.000+0100},
title = {miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data.},
url = {http://dx.doi.org/10.1093/nar/gks1187},
username = {aorchid},
volume = 41,
year = 2013
}