Nick Cox asked how egen rank and egen corr compares to using spearman
in the context of statsby. It turns out to be at least 10 times
faster. Thanks Nick.
// Break file into subfiles of 500 "by groups" (genes),
// because Stata "statsby" command is so slow across 22K by groups,
// then calculate and save out spearman correlation stats
// for iso_VSV and gene expression and append into a file 22K rows long
// and apply FDR
// This version comments out statsby and uses egen rank and egen corr
// and consequently is 10 times fast, doing 22K spearman correlations
// in about 50 seconds (along with file creation, etc.).
set more off
set rmsg on
clear
set memory 200M
// sabatini_merged is a long format file
// merging expression data and editing data
use "/Users/dairey/Desktop/primate_editing/sabatini_merged.dta"
preserve
local start = 1
forvalues stop = 6000(6000)267396 {
keep if _n >= `start' & _n <= `stop'
save sabatini_`stop'.dta, replace
egen rank_1 = rank(expression), by(ssrownum)
egen rank_2 = rank(iso_VSV), by(ssrownum)
egen corr = corr(rank_1 rank_2), by(ssrownum)
collapse (mean) spearman=corr (count) count=corr, by(ssrownum)
gen t = spearman*((count-2)/(1-spearman^2))^0.5
gen p = 2*ttail(count-2,abs(t))
save spearman_`stop'.dta, replace
local start = `stop'+1
restore, preserve
}
clear
use "/Users/dairey/Desktop/primate_editing/sabatini_merged.dta"
keep if _n > 264000 & _n <= 267396
save sabatini_267396.dta, replace
keep ssrow expression iso_VSV
egen rank_1 = rank(expression), by(ssrownum)
egen rank_2 = rank(iso_VSV), by(ssrownum)
egen corr = corr(rank_1 rank_2), by(ssrownum)
collapse (mean) spearman=corr (count) count=corr, by(ssrownum)
gen t = spearman*((count-2)/(1-spearman^2))^0.5
gen p = 2*ttail(count-2,abs(t))
save spearman_267396.dta, replace
// append the statsby results into one file
use spearman_6000.dta
forvalues stop = 12000(6000)267396 {
append using spearman_`stop'.dta
erase spearman_`stop'.dta
}
append using spearman_267396.dta
erase spearman_267396.dta
save iso_VSV.dta, replace
erase spearman_6000.dta
// see if there is significance after FDR
multproc, pvalue(p) method(simes) puncor(0.05) rank(rank)
// keep top 100 and bring in gene information against ssrownum key id
sort rank
keep if rank < 101
sort ssrownum
merge ssrownum using "/Users/dairey/Desktop/primate_editing/
sabatini_genes.dta"
keep if _merge == 3
// list gene information
sort rank
list gene_title
set rmsg off
set more on
/*
// use a forvalues loop to make smaller files and do statsby
preserve
local start = 1
forvalues stop = 6000(6000)267396 {
keep if _n >= `start' & _n <= `stop'
save sabatini_`stop'.dta, replace
statsby n=r(N) spearman=r(rho) p=r(p), by(ssrownum): ///
spearman iso_VSV expression
save spearman_`stop'.dta, replace
local start = `stop'+1
restore, preserve
}
// above, the forvalues misses data after row 264000 so
// those are picked up here
clear
use "/Users/dairey/Desktop/primate_editing/sabatini_merged.dta"
keep if _n > 264000 & _n <= 267396
save sabatini_267396.dta, replace
statsby n=r(N) spearman=r(rho) p=r(p), by(ssrownum): ///
spearman iso_VSV expression
save spearman_267396.dta, replace
*/
--
David C. Airey, Ph.D.
Research Assistant Professor
