Entering edit mode
6.1 years ago
Calangoa
▴
30
Hi I am really confused with my data. Since I have 12 gene expression data set from 12 different condition and I want to know active madules and co expression genes after finding relative TFs for differentially expressed genes. Moreover, I want to use this result to compare these 12 individuale data for finding more about similarities and differences . Is there any way in R or Cytoscape to analyze and visualiz this goal?
Many thanks in advance
Which type of data? - RNA-seq or microarray? From where did you obtain the data? How have you processed the data?
Hi kevin I have sets of microarray data, all these data are affymatrix and gene expression for each of them achived by R bioconductor package. Then interaction between differentially expressed genes with TFs were extracted by online tools. The gene_TF networks were constructed using cytoscape but my desire goal is to use a plugin from cytoscape to find activemodules or differential modole since I extracted gene expression from differention condition to show what condotion is better and closer to reality than otbers? Or maybe we don't need modules so what is another way to this goal?
With multiple datasets, you will have an issue with batch. I am not sure that you have managed that, sufficiently. If you are processing the datasets in an entirely independent fashion, then it should not matter, of course.
Regarding the identification of modules / clusters / communities, take a look at these for starting:
There is nothing special about these algorithms at all - they are just a re-hash of functions that have been in existence for decades, much like AI and machine learning algorithms.
I am not sure what you mean by this...
Thanks Kevin for your useful information.