Claire_6700 wrote:
Hello,
I need some help with the simulatedSNPs function from scrime package.
I am trying to simulate some genotype of a case/control disease locus. The allele frequence are cases/controls
Sample cases controls
2000 .5 .10
1500 .6 .40
In each of the row, i need to simulate 100 snp and calculate the pvalue
##############Download Scrime Package###########################
library(scrime)
n.obs<-1000
n.snp<-100
vec.ia<-1
simulateSNPs(n.obs, n.snp, vec.ia, prop.explain = 1,
list.ia.val = NULL, vec.ia.num = NULL, maf = c(0.1, 0.12),
prob.val = rep(1/3, 3), list.equal = NULL, prob.equal = 0.8,
rm.redundancy = TRUE, shuffle = FALSE, shuffle.obs = FALSE, rand = NA)
What is the right parameter. I am pretty new with R.
wrong result.
Interaction Cases Controls
1 SNP1 == 2 500 0
any help will be appreciated.
thanks
Claire
Check the help for the ?simulateSNPs() function. It provides clear examples of how to use it.
In this instance you need to assign the results of running simulateSNPs to an object. So, in your above code you need to have...
#### Start ####
> library(scrime)
> n.obs<-1000
> n.snp<-100
> vec.ia<-1
## Note the assignment in the below statement
> sim1<- simulateSNPs(n.obs, n.snp, vec.ia, prop.explain = 1, \\
list.ia.val = NULL, vec.ia.num = NULL, maf = c(0.1, 0.12), \\
prob.val = rep(1/3, 3), list.equal = NULL, prob.equal = 0.8, \\
rm.redundancy = TRUE, shuffle = FALSE, shuffle.obs = FALSE, rand = NA)
#### Finish ####
You now have an object 'sim1' that contains the results of the simulation. To find out what these are you type...
#### Start ####
> names(sim1)
[1] "data" "cl" "tab.explain" "ia" "maf"
#### Finish ####
What you are seeing with out assigning the results from calling simulateSNPs() to an object is sim1$tab.explain
To get the raw data from the simulations into its own object you can...
#### Start ####
> sim1.data <- sim1$data
## Print summary information on allele frequencies of simulated data
> sim1$maf
[1] 0.1019921 0.1166833 0.1162599 0.1032456 0.1144771 0.1067833 0.1023612
[8] 0.1168232 0.1066618 0.1172988 0.1049692 0.1006477 0.1124793 0.1086271
[15] 0.1181598 0.1038002 0.1150600 0.1029935 0.1196051 0.1015223 0.1045593
[22] 0.1089789 0.1180688 0.1006122 0.1196565 0.1131580 0.1131264 0.1022888
[29] 0.1158212 0.1118635 0.1077083 0.1151471 0.1023238 0.1012435 0.1044028
[36] 0.1047839 0.1007996 0.1030058 0.1180583 0.1003964 0.1051847 0.1183929
[43] 0.1061727 0.1118420 0.1192968 0.1040632 0.1051112 0.1186949 0.1042196
[50] 0.1009020 0.1113263 0.1130648 0.1094135 0.1168967 0.1187118 0.1085089
[57] 0.1199226 0.1143786 0.1159529 0.1014398 0.1104690 0.1050063 0.1009227
[64] 0.1102197 0.1030258 0.1109929 0.1001394 0.1106730 0.1054413 0.1044738
[71] 0.1080446 0.1003916 0.1094400 0.1086378 0.1059338 0.1039598 0.1043444
[78] 0.1102694 0.1017065 0.1154185 0.1177336 0.1095213 0.1171060 0.1103163
[85] 0.1089563 0.1080247 0.1088396 0.1157875 0.1179325 0.1041557 0.1095087
[92] 0.1013651 0.1044949 0.1084277 0.1163425 0.1061450 0.1015519 0.1029643
[99] 0.1126980 0.1023006
#### Start ####
Neil
