diff options
Diffstat (limited to 'wqflask')
| -rwxr-xr-x | wqflask/wqflask/marker_regression/marker_regression.py | 30 |
1 files changed, 15 insertions, 15 deletions
diff --git a/wqflask/wqflask/marker_regression/marker_regression.py b/wqflask/wqflask/marker_regression/marker_regression.py index d2df5cd1..45361117 100755 --- a/wqflask/wqflask/marker_regression/marker_regression.py +++ b/wqflask/wqflask/marker_regression/marker_regression.py @@ -244,7 +244,7 @@ class MarkerRegression(object): count, p_values = self.parse_rqtl_output(plink_output_filename) def geno_to_rqtl_function(self): # TODO: Need to figure out why some genofiles have the wrong format and don't convert properly - print("Adding a function to the R environment") + print("Adding some custom helper functions to the R environment") ro.r(""" trim <- function( x ) { gsub("(^[[:space:]]+|[[:space:]]+$)", "", x) } @@ -254,7 +254,7 @@ class MarkerRegression(object): } GENOtoCSVR <- function(genotypes = 'BXD.geno', out = 'cross.csvr', phenotype = NULL, sex = NULL, verbose = FALSE){ - header = readLines(genotypes, 40) + header = readLines(genotypes, 40) # Assume a geno header is not longer than 40 lines toskip = which(unlist(lapply(header, function(x){ length(grep("Chr\t", x)) })) == 1)-1 # Major hack to skip the geno headers genocodes <- c(getGenoCode(header, 'mat'), getGenoCode(header, 'het'), getGenoCode(header, 'pat')) # Get the genotype codes @@ -268,9 +268,9 @@ class MarkerRegression(object): cbind(genodata[,c('Locus','Chr', 'cM')], genodata[, 5:ncol(genodata)])) # Genotypes write.table(outCSVR, file = out, row.names=FALSE, col.names=FALSE,quote=FALSE, sep=',') # Save it to a file require(qtl) - cross = read.cross(file=out, 'csvr', genotypes=genocodes) - if(type == 'riset') cross <- convert2riself(cross) - return(cross) # Load it using R/qtl read.cross + cross = read.cross(file=out, 'csvr', genotypes=genocodes) # Load the created cross file using R/qtl read.cross + if(type == 'riset') cross <- convert2riself(cross) # If its a RIL, convert to a RIL in R/qtl + return(cross) } """) @@ -280,11 +280,11 @@ class MarkerRegression(object): self.geno_to_rqtl_function() ## Get pointers to some common R functions - r_library = ro.r["library"] # Map the library function - r_c = ro.r["c"] # Map the c function - r_sum = ro.r["sum"] # Map the sum function + r_library = ro.r["library"] # Map the library function + r_c = ro.r["c"] # Map the c function + r_sum = ro.r["sum"] # Map the sum function - print(r_library("qtl")) # Load R/qtl + print(r_library("qtl")) # Load R/qtl ## Get pointers to some R/qtl functions scanone = ro.r["scanone"] # Map the scanone function @@ -299,7 +299,7 @@ class MarkerRegression(object): print("Conversion of geno to cross at location:", genofilelocation, " to ", crossfilelocation) - cross_object = GENOtoCSVR(genofilelocation, crossfilelocation) # TODO: Add the SEX if that is available + cross_object = GENOtoCSVR(genofilelocation, crossfilelocation) # TODO: Add the SEX if that is available if self.manhattan_plot: cross_object = calc_genoprob(cross_object) @@ -314,7 +314,7 @@ class MarkerRegression(object): covar = self.create_covariates(cross_object) # Create the additive covariate matrix if self.pair_scan: - if(r_sum(covar)[0] > 0): + if(r_sum(covar)[0] > 0): # If sum(covar) > 0 we have a covariate matrix print("Using covariate"); result_data_frame = scantwo(cross_object, pheno = "the_pheno", addcovar = covar) else: print("No covariates"); result_data_frame = scantwo(cross_object, pheno = "the_pheno") @@ -328,13 +328,13 @@ class MarkerRegression(object): else: print("No covariates"); result_data_frame = scanone(cross_object, pheno = "the_pheno", model=self.model, method=self.method) - if int(self.num_perm) > 0: # Do permutation (if requested by user) + if int(self.num_perm) > 0: # Do permutation (if requested by user) if(r_sum(covar)[0] > 0): perm_data_frame = scanone(cross_object, pheno_col = "the_pheno", addcovar = covar, n_perm = int(self.num_perm), model=self.model, method=self.method) else: perm_data_frame = scanone(cross_object, pheno_col = "the_pheno", n_perm = int(self.num_perm), model=self.model, method=self.method) - self.process_rqtl_perm_results(perm_data_frame) # Functions that sets the thresholds for the webinterface + self.process_rqtl_perm_results(perm_data_frame) # Functions that sets the thresholds for the webinterface return self.process_rqtl_results(result_data_frame) @@ -346,14 +346,14 @@ class MarkerRegression(object): def create_covariates(self, cross): ro.globalenv["the_cross"] = cross ro.r('genotypes <- pull.geno(the_cross)') # Get the genotype matrix - userinputS = self.control.replace(" ", "").split(",") # TODO sanitize user input, Never Ever trust a user + userinputS = self.control.replace(" ", "").split(",") # TODO: sanitize user input, Never Ever trust a user covariate_names = ', '.join('"{0}"'.format(w) for w in userinputS) print("Marker names of selected covariates:", covariate_names) ro.r('covnames <- c(' + covariate_names + ')') ro.r('covInGeno <- which(covnames %in% colnames(genotypes))') ro.r('covnames <- covnames[covInGeno]') ro.r("cat('covnames (purged): ', covnames,'\n')") - ro.r('covariates <- genotypes[,covnames]') # Get the covariate matrix by using the marker name as index to the genotype file + ro.r('covariates <- genotypes[,covnames]') # Get the covariate matrix by using the marker name as index to the genotype file print("R/qtl matrix of covariates:", ro.r["covariates"]) return ro.r["covariates"] |