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Tspair specifications

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Unique identifier OMICS_12484
Name Tspair
Alternative name Top Scoring Pairs
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data Either (i) a gene expression matrix or an expression set and a group indicator vector, or (ii) an expression set object and a column number, indicating which column of the annotation data to use as the group indicator.
Output data A tsp object which gives the TSP score, indices, gene expression data and group labels for the TSP. If there are multiple pairs that achieve the top score, then the tie-breaking score developed by Tan et al. (2005) is reported.
Operating system Unix/Linux, Mac OS, Windows
License GNU General Public License version 2.0
Computer skills Advanced
Version 1.38.0
Stability Stable
Requirements
R(>=2.10), Biobase(>=2.4.0)
Maintained Yes

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Maintainer


  • person_outline Jeffrey T. Leek

Publication for Top Scoring Pairs

Tspair citations

 (5)
call_split

Transcriptome profiles in peripheral white blood cells at the time of artificial insemination discriminate beef heifers with different fertility potential

2018
BMC Genomics
PMCID: 5807776
PMID: 29426285
DOI: 10.1186/s12864-018-4505-4
call_split See protocol

[…] level of 0.1., fragments per kilobase per million reads (fpkm) were calculated using the function “rpkm()” from “edger”. fpkm was the used as input for the calculation of tsp using the package “tspair” []. the tsp approach [] identifies genes whose transcript abundance ratios within each individual can classify subjects into binary categories. the ratios of the 20 tsp were used as input […]

library_books

Quantitative or qualitative transcriptional diagnostic signatures? A case study for colorectal cancer

2018
BMC Genomics
PMCID: 5789529
PMID: 29378509
DOI: 10.1186/s12864-018-4446-y

[…] could be applied to the data measured by different laboratories or platforms. here, we additionally evaluated other rank based approaches using the same training and validation datasets. using the tspair r package (version 3.3.3), we trained the tsp classifier in the training samples directly combined from data measured by the affymetrix and illumina platforms. in the training set, 97.0% […]

call_split

Whole blood microRNA expression may not be useful for screening non small cell lung cancer

2017
PLoS One
PMCID: 5526508
PMID: 28742859
DOI: 10.1371/journal.pone.0181926
call_split See protocol

[…] a value set of 0.1, 0.2, 0.5, 1, 2, 5, 10, 20, 50 for cost [], and consisted of 15 most differentially expressed micrornas (genes) identified by the limma method. the cma [] (version 1.12.0) and tspair [] (version 1.12.0) bioconductor packages for r were used for the classification analyses. cross-validations in these analyses used the leave-one-out (loocv) and monte carlo (mccv) methods. […]

library_books

Evolutionary Approach for Relative Gene Expression Algorithms

2014
Sci World J
PMCID: 3982252
PMID: 24790574
DOI: 10.1155/2014/593503

[…] is to improve classification accuracy and identification of marker genes interactions. we let the ea to search for the best multiple pairwise comparisons of the gene expression values. the number of top-scoring pairs k is determined also by the evolution and with no restrictions on disjoint gene pairs; evotsp may compare relationships for more than two genes like in tsn. application of ea […]

library_books

MicroRNA Expression Profiles of Whole Blood in Lung Adenocarcinoma

2012
PLoS One
PMCID: 3460960
PMID: 23029380
DOI: 10.1371/journal.pone.0046045

[…] analyses of microarray signals for expressed micrornas were done in r using the cma bioconductor package (version 1.8.1) for the support vector machines (svm; linear kernel) method, and the tspair bioconductor package (version 1.8) for the top-scoring pairs (tsp) method . internal validation was performed using the leave-one-out and monte carlo cross-validation methods (loocv and mccv, […]


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Tspair institution(s)
Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD, USA
Tspair funding source(s)
National Science Foundation (DMS034211); National Institutes of Health (1UL1RR025005-01).

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