Description Usage Arguments Value See Also Examples
sis
is used to conduct sure independent screening across high-dimensional variables.
1 2 3 |
y.vect |
a vector of dependent variable. |
id.vect |
a vector of subjuect ID. |
M |
a data frame or matrix of genomic dataset. Rows represent samples, columns represent variables. |
COV |
a data frame or matrix of covariates dataset. |
method |
a character string specifying fitting method. For data contains >= 2 repeated measures, linear mixed-effect model ( |
corstr |
a character string specifying the correlation structure when |
parallel |
logical. Enable parallel computing feature? Default = |
ncore |
number of cores to run parallel. Effective when paralle = |
write |
logical. Export screening results to csv file in the working directory if |
sure independent screening results in a sis.obj
object.
see pgsfit
using the results from sis
as input to run PGS; see sis.obj
for class methods; see lmer
, geeglm
, and lm
for more details on "LMM"
,"GEE"
, and "MLR"
methods, respectively.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | ### Dataset preview
BJdata()
### Convert binary variables into factor type
BJlung$gender = factor(BJlung$gender)
BJlung$heat = factor(BJlung$heat)
BJlung$cigwear = factor(BJlung$cigwear)
### Merge miRNA and lung function dataset
BJdata <- merge(BJmirna, BJlung, by=c("SID","WD"))
### Data must be sorted by study subject ID and multiple measurements indicator
BJdata <- BJdata[with(BJdata, order(SID, WD)), ]
### Extract dependent variable (lung function)
y.vect<-BJdata$FEV1
### Extract subjuect ID variable indicating repeated measures
id.vect<-BJdata$SID
### Extract microRNA data matrix
M<-BJdata[,3:168]
### Extract covariate data matrix
COV<-BJdata[,170:179]
### LMM sure independent screening results
sis_LMM_par = sis(y.vect, id.vect, M, COV, method = "LMM")
### GEE sure independent screening results
sis_GEE_par = sis(y.vect, id.vect, M, COV, method = "GEE")
### Save the full site-by-site testing results into a csv file in current working directory
sis_LMM_par = sis(y.vect, id.vect, M, COV, method = "LMM", write = T)
sis_LMM_par # print summary of sure independent screening results
plot(sis_LMM_par) # plot histogram of raw p-values and Q-Q plot
coef(sis_LMM_par) # return coefficients from sure independent screening results
#For more information, please visit: https://github.com/YinanZheng/PGS/wiki/Example:-miRNA-expression-and-lung-function
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