  Hello Guys, 
  I'm using the package RankProduct to determine the differential expression of genes in 2 classes.
  The importance of the thing is to know:
   
  -          How can I determine which class is  the class of up-regulated genes and which to the down regulated gene
   
  -          How can i interpret the results :
   
  $pfp,    $RPs,              $RPrank,         
   
  Orirank,           
  $Orirank$"class1 > class 2"
  $Orirank$"class1 < class 2"
   
   $AveFC
   
  Table1: Genes called significant under class1 < class2
  Table2: Genes called significant under class1 > class2 
   
   
  Thanks for your help.
   
  Example:
   
  Formula:
  RP.out<-RP(data, pt.cl, g.names, num.perm = 100, logged = TRUE,
   na.rm = FALSE, plot = FALSE, rand =123)
   
   
   
                                                                                                
  $pfp
      class1 < class2 class1 > class 2
  1        0.97115385      0.002000000
   
   
  $RPs
      class1 < class2 class1 > class 2
  1          37.54242         21.63239
   
  $RPrank
      class1 < class2 class1 > class 2
  1              26.0              5.0
   
   
   
  Orirank
  $Orirank$"class1 < class2"
          [,1]  [,2]  [,3]  [,4]  [,5]  [,6]  [,7]  [,8]  [,9] [,10] [,11] [,12]
  ЕЕЕЕЕЕЕЕЕЕЕЕЕЕЕЕЕ..
    
  $Orirank$"class1 > class 2"
  ЕЕЕЕЕЕЕЕЕЕЕЕЕЕ..
     
   
  $AveFC
      log/unlog(class1/class2)
  1               0.0694052288
  ЕЕЕЕЕЕЕЕЕЕЕЕ
     
      
  #Genes by controlling pfp <0.05    
                                                                                                                                                                                                                                    &nbsp;                                                                                                                                                                                                                                                               &nbsp;                                                                                                                                                                                                                                                               &nbsp;                                                                                                                                                                                                                                                  
             &nbsp;                                                                                                                                                                                                                                                               &nbsp;                                                                                                                                                                                                                                                               &nbsp;                                                                                                                                                                                                                
  topGene(RP.out, cutoff = 0.05, logged = TRUE, logbase = 2, g.names)
   
  Table1: Genes called significant under class1 < class2
   
   
  Table2: Genes called significant under class1 > class2 
   
   
  $Table1
             gene.index RP/Rsum FC:(class1/class2)    pfp
  Gen n             51 15.8595             0.8204 0.0000
  Gen n-1          65 18.3764             0.9582 0.0250
  Gen n-2         75 18.6893             0.8916 0.0167
  Gen n-3             52 19.0778             0.8928 0.0150
  ЕЕЕЕЕЕЕЕЕЕЕЕЕЕЕЕЕ.
   
  $Table2
               gene.index RP/Rsum FC:(class1/class2)    pfp
  Gen n-3                 98 10.0913             1.4331 0.0000
  Gen n-2                 39 15.2657             1.4062 0.0000
  Gen n-1                  2 19.8796             1.1414 0.0000
  Gen n                     97 20.3225             1.1446 0.0000
ЕЕЕЕЕЕЕЕЕЕЕЕЕЕЕЕЕЕ...                            

		
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