Description Usage Arguments Value Author(s) References
Integrates statistics of differential DNA methylation and differential expression for a specified contrast with a network adjacency matrix. Output of this function is required input for DoFEMbi.
1 | DoIntFEM450k(statM.o,statR.o,adj.m,cM,cR,"dmaMode")
|
statM.o |
The output of GenStatM, or analogous object generated by user. |
statR.o |
The output of GenStatR, or analogous object generated by user. |
adj.m |
The adjacency matrix defining the network of gene relations, e.g. a PPI network, annotated to NCBI entrez gene IDs. |
cR |
An integer specifying the desired contrast, i.e. column of the contrast matrix. User needs to check which column of statR.o$cont is the one of interest. |
cM |
An integer specifying the desired contrast, i.e. column of the contrast matrix. User needs to check which column of statM.o$cont is the one of interest. Note that for this to make sense the contrast cM must correspond to the same one as specified by cR. |
dmaMode |
An parameter specifying the object mode for statM.o, "avbeta" for the average beta mode object generated by GenStatM, whereas "singleProbe" for the single probe mode object generated by the GenStatMsp, default for "avbeta" |
A list with following entries:
statM |
matrix of DNA methylation moderated t-statistics and P-values for the genes in the integrated network |
statR |
matrix of gene expression moderated t-statistics and P-values for the genes in the integrated network |
adj |
adjacency matrix of the maximally connected integrated network (at present only maximally connected subnetwork is used). |
avexp |
average expression data matrix mapped to unique Entrez IDs |
avbeta |
average DNA methylation data matrix mapped to unique Entrez IDs |
probeID |
vector of the probe IDs that most differentially methylated for each gene |
"Yinming Jiao"<20907099@zju.edu.cn>, "Andrew E Teschendorff"<andrew@picb.ac.cn>
A systems-level integrative framework for genome-wide DNA methylation and gene expression data identifies differential gene expression modules under epigenetic control. Jiao Y, Widschwendter M, Teschendorff AE. Bioinformatics. 2014;30(16):2360-2366
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