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uShuffle specifications

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Unique identifier OMICS_17456
Name uShuffle
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages C, Java, Perl, Python
Computer skills Advanced
Stability Stable
Maintained Yes

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Maintainer


  • person_outline Minghui Jiang

Information


Unique identifier OMICS_17456
Name uShuffle
Interface Web user interface
Restrictions to use None
Programming languages C, Java, Perl, Python
Computer skills Basic
Stability Alpha
Maintained Yes

Maintainer


  • person_outline Minghui Jiang

Publication for uShuffle

uShuffle citations

 (23)
library_books

Structural signatures of thermal adaptation of bacterial ribosomal RNA, transfer RNA, and messenger RNA

2017
PLoS One
PMCID: 5598986
PMID: 28910383
DOI: 10.1371/journal.pone.0184722

[…] s. Using dinucleotide frequencies, rather than mononucleotide frequencies, for generating random sequences is necessary because RNA secondary structure depends on pairwise stacking energies []. Using Ushuffle [], we randomly shuffled dinucleotide within each original RNA sequence to obtain the corresponding random RNA sequence. These random RNA sequences have the same length, GC content and other […]

library_books

A sensitivity analysis of RNA folding nearest neighbor parameters identifies a subset of free energy parameters with the greatest impact on RNA secondary structure prediction

2017
Nucleic Acids Res
PMCID: 5449625
PMID: 28334976
DOI: 10.1093/nar/gkx170

[…] gth. The shuffled RNA sequences were randomly selected from the archive and shuffled such that the dinucleotide frequency was maintained. The shuffled sequences were generated using the Python module uShuffle, which implements the Euler algorithm to randomly permute a sequence while maintaining k-let frequencies for an arbitrary k (). […]

library_books

FEELnc: a tool for long non coding RNA annotation and its application to the dog transcriptome

2017
Nucleic Acids Res
PMCID: 5416892
PMID: 28053114
DOI: 10.1093/nar/gkw1306

[…] omputed their predictor scores in comparison with the true set of 5000 HL lncRNAs. For the shuffle strategy, it is essential to determine a priori which given k-mer frequencies should be preserved by Ushuffle to maximize classification accuracy. We thus shuffled HL mRNA sequences for different sizes of k and showed that preserving 7-mer frequencies gave the best MCC values on the HT set while sust […]

library_books

Overlapping Regions in HIV 1 Genome Act as Potential Sites for Host–Virus Interaction

2016
Front Microbiol
PMCID: 5095123
PMID: 27867372
DOI: 10.3389/fmicb.2016.01735

[…] e of that SLiM in shuffled set is 0.01. Next, we classified those SLiMs as true SLiMs which has a probability of occurrence in the shuffled set is less than 0.1. The sequences were shuffled using the Ushuffle program () with seed 10-4. Experimentally validated SLiMs that are involved in interaction with host proteins were retrieved from the published dataset of and .We calculated SLiMs which are […]

library_books

Alu repeats as transcriptional regulatory platforms in macrophage responses to M. tuberculosis infection

2016
Nucleic Acids Res
PMCID: 5159539
PMID: 27604870
DOI: 10.1093/nar/gkw782

[…] of false positive that could come from compositional bias or low-complexity regions in the >2 kb regions identified by MACS. Background sequences were generated from the histone marks sequences with uShuffle using parameters n = 5 and k = 3 (). GREAT () was used to identify genes near the histone marks regions and GO analysis. Gene set enrichment analysis was performed using a greedy algorithm ba […]

library_books

High throughput analysis of the satellitome illuminates satellite DNA evolution

2016
Sci Rep
PMCID: 4935994
PMID: 27385065
DOI: 10.1038/srep28333

[…] ry, i.e., genome proportion.We estimated the frequency of random occurrence for some short satDNA monomers. For this purpose, we generated 1,000 Gb, i.e., ~159 genomes, shuffling nucleotides with the uShuffle program preserving the dinucleotide frequencies of the assembled genome of L. migratoria, accession number AVCP000000000. In addition, we analyzed the abundance of some satDNA families in the […]


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uShuffle institution(s)
Department of Computer Science, Utah State University, Logan, UT, USA
uShuffle funding source(s)
This work was supported by National Science Foundation grant DBI-0743670 and Utah State University grant A13501.

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