Tspair statistics

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Citations per year

Number of citations per year for the bioinformatics software tool Tspair

Tool usage distribution map

This map represents all the scientific publications referring to Tspair per scientific context
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Associated diseases


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Tspair specifications


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
R(>=2.10), Biobase(>=2.4.0)
Maintained Yes




No version available



  • person_outline Jeffrey T. Leek

Publication for Top Scoring Pairs

Tspair citations


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

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

[…] P, 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% of the […]


Evolutionary Approach for Relative Gene Expression Algorithms

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

[…] specialized operators to mutate and cross-over individuals and a fitness function that helps mitigating the overfitting problem. With the new weighted gene pairs voting and extended representation of top-scoring pairs that involve different variants of TSP, we were able to significantly improve TSP accuracy with still relatively small size of classification model. Application of EAs allows explori […]

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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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