mathramp, 2014 Oct 28

Rstudio was not moved into "Application".

Went over R code for simulating aging in permuted networks.

Went over R code for generating histogram of CV

Network configuration on gompertz and weibull fitting (need follow up)

When p=0.6, pop=2000, original GINDIP fits much better to Gompertz with regards to Weibull, as compared to the ms02 permutated network. 

I need to generate a distribution using 100 ms02 networks.

Gompertz and Weibull fitting, yGINDIP vs ms02, repliminary

lapbio-hq:mathramp hqin$ pwd

/Users/hqin/github/mactower-network-failure-simulation/mathramp

ms02 network aging, preliminary

I run preliminary analysis on network aging, and found that ms02 network tend to have short maximum network lifespan, even though their average lifespan is more or less the same with the yeast GIN/PPI. This seem to suggests that ms02 network has a more homogenous aging process. It seems to make sense that power-law increase heterogeneity in the yeast network. 

Population size of 500 did not good p-value using wilcox.test().

mathramp, 2014 Feb 17

The student used link-switch to generate random network.  I went over '20131221.DIPandGIN.sim.aging_v2.R' with the student. The code is 5 1/2 pages, much longer than I thought.

ms02 R, batch run

# ms02-2014Feb12.R
#permuate merged yeast PPI+GIN

#2014 Feb 12, re-name function to ms02_singlerun
#2014 Jan 31, fixed a bug that inserted "NA" into new network. The bug seems to be caused by spliting the
# arrays. I rewrote the spliting portion.



#require(igraph)
rm(list=ls())
debug = 0
setwd("~/projects/0.ginppi.reliability.simulation/ms02GINPPI")
#set.seed(2014)

#permute.pairs.wo.selfpairs = function( inpairs,  ncycles=10, debug=1 ) { 
ms02_singlerun = function( inpairs,  ncycles=10, indebug=0 ) { # Renamed, 2014 Feb 12
  if (ncycles >= 1 ) {
    if(indebug>0) {
      print(paste('ncycles=', ncycles))
    }
    longids = c(as.character(inpairs[,1]), as.character(inpairs[,2]) )
    longids = sample(longids)
    len = length(inpairs[,1])
    newpairs = data.frame( cbind( longids[1:len], longids[(len+1): (2*len)]) )
    names(newpairs) = c('id1', 'id2')
    newpairs$id1 = as.character( newpairs$id1)
    newpairs$id2 = as.character( newpairs$id2)   
    newpairs$selfpairs = ifelse( newpairs$id1 == newpairs$id2, 1, 0 )
    self.tb = newpairs[ newpairs$selfpairs==1, ]
    nonself.tb = newpairs[newpairs$selfpairs==0, ]
    if(indebug>0) {
      print(paste("===selfpairs===="),NULL)
      print(self.tb)
      print(paste("================="),NULL)
    }
    if( length(self.tb[,1])>=1 ) {
      if ( ncycles == 0) {
        #return (c(NA,NA, NA) );
        print(paste("ncycles reached zero, ncycles"),ncycles)
        print(paste("Abort!"),NULL)
        stop;
      } else {
        ncycles = ncycles - 1
        splitPos = round( length(self.tb[,1]) * sqrt(ncycles) ) + 5  #2014Jan31 change
        splitPos = min( splitPos, (length(nonself.tb[,1])-1 ) )
        selectedpairs = rbind(self.tb,  nonself.tb[1: splitPos, ] )
        restpairs = nonself.tb[ (splitPos + 1): length(nonself.tb[,1]), ]
        #return( rbind(restpairs, permute.pairs.wo.selfpairs(selectedpairs, ncycles)))
        return( rbind(restpairs, ms02_singlerun(selectedpairs, ncycles)))  #2014 Feb 12
      }
    } else { 
      return (newpairs)
    }
  } else {
    return( c(NA,NA,NA ))
  }
}

#net = read.table("repeat.tab")
#write.table(pairs, "merged_PPIGIN_2014Jan20.tab", quote=F, row.names=F, col.names=F, sep='\t')
net = read.table( "merged_PPIGIN_2014Jan20.tab", header=F, sep="\t", colClass = c("character", "character") )
head(net)
if(debug==9) {
  #net = read.table('pair.tab',header=F)
 net = net[1:90000,]
}

for( i in 1:100) {
 net.ms02 = ms02_singlerun( net, indebug=0 )
 cmnd = paste( "mkdir dipgin.ms02.output/", i, sep="")
 system( cmnd )
 outputname = paste( 'dipgin.ms02.output/', i, '/', "ms02_",i,".tab", sep="")
 write.csv(net.ms02, outputname)
}

#do they have the same degree?
#t1 = table(c(net[,1],net[,2]))
#t2 = table(c(net.ms02[,1],net.ms02[,2]))
#comp <- t1 == t2
#table(comp)
#tf = comp[comp==F]; tf
#t1[names(tf)[1]]
#t1[names(tf)]
#t2[names(tf)]

GAS 2014 annual meeting prep, math ramp research

Friday and Saturday, 28-29 March, 2014 at Georgia Regents University, Augusta, GA. 

meeting registration site
http://www.gru.edu/trends/gas/accommodations.php
http://www.gaacademy.org/annualmeeting10.htm

hotel:
Hilton Garden Inn Augusta Meeting rate ($89) but not available anymore. 
1065 Stevens Creek Road, Augusta, Georgia, 30907

Sheraton Augusta Hotel  , prepaid rate $107 per night, refundable rate $119
1069 Stevens Creek Road, Augusta, GA 30907

Sheraton Augusta Hotel

1069 Stevens Creek Road

Augusta, Georgia 30907 United States

Phone: (706) 396-1000 Fax: (706) 396-1001

Parking?

-------------------------
Prepare of a 10 minutes talk.

Research talk:

10 slides.

1. background, gene network, essential and non-essential,
2. background, what is aging, our quantitative definition
3. specific aim: how reliable is the yeast gene interaction network.
4. method: how to generate random networks.
5. method: evaluate the failure rates of original and random networks
6. method: how network failure is simulated and evaluated
7. result: histogram of failure rate, average lifespan of random networks, with original network
8. result: Gompertz versus Weibull (biological versus machine aging)
9. summary and conclusions
10. future directions:

acknowledge, funding support

things to do:
->flow chart to generate 100 random networks and simulate their failures.
-> run the two R codes on network aging simulation and network permutation.