exprs1


  Gene expression dataset, containing 1000 rows and 10 columns.


datasets

Elucidation of human disease similarities has emerged as an active research area, which is highly relevant to etiology, disease classification, and drug repositioning. This package was designed and implemented for identifying disease similarities. It contains five functions which are 'DCEA', 'DCpathway', 'DS', 'comDCGL' and 'comDCGLplot'. In 'DCEA' function, differentially co-expressed genes and differentially co-expressed links are extracted from disease vs. health samples. Then 'DCpathway' function assigns differential co-expression values of pathways to be the average differential co-expression value of their component genes. Then 'DS' employs partial correlation coefficient of pathways as the disease similarity for each disease pairs. And 'DS' contains a permutation process for evaluating the statistical significant of observed disease partial correlation coefficients. At last, 'comDCGL' and 'comDCGLplot' sort out shared differentially co-expressed genes and differentially co-expressed links with regulation information and visualize them.

Jing Yang

DSviaDRM

Exploring Disease Similarity in Terms of Dysfunctional
Regulatory Mechanisms

exprs1 function

A data frame with 1000 observations 10 variables.
<ul>
<li>exprs1 A data frame with 1000 observations 10 columns. The expression values. 
</li>
</ul> 

exprs1: Real dataset pulled down from GEO (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE22528)

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