diff options
Diffstat (limited to 'wqflask')
| -rwxr-xr-x | wqflask/wqflask/marker_regression/marker_regression.py | 45 | ||||
| -rw-r--r-- | wqflask/wqflask/my_pylmm/pyLMM/lmm.py | 3 |
2 files changed, 43 insertions, 5 deletions
diff --git a/wqflask/wqflask/marker_regression/marker_regression.py b/wqflask/wqflask/marker_regression/marker_regression.py index 140da0c5..64d3ef3d 100755 --- a/wqflask/wqflask/marker_regression/marker_regression.py +++ b/wqflask/wqflask/marker_regression/marker_regression.py @@ -229,10 +229,42 @@ 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") + ro.r(""" + getGenoCode <- function(header, name = 'unk'){ + mat = which(unlist(lapply(header,function(x){ length(grep(paste('@',name,sep=''), x)) })) == 1) + return(strsplit(header[mat],'')[[1]][6]) + } + + GENOtoCSVR <- function(genotypes = 'BXD.geno', out = 'cross.csvr', phenotype = NULL, sex = NULL, verbose = FALSE){ + header = readLines(genotypes, 40) + 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 + + genodata <- read.csv(genotypes, sep='\t', skip=toskip, header=TRUE, na.strings=getGenoCode(header,'unk'), colClasses='character', comment.char = '#') + cat('Genodata:', toskip, " ", dim(genodata), '\n') + if(is.null(phenotype)) phenotype <- runif((ncol(genodata)-4)) # If there isn't a phenotype, generate a random one + if(is.null(sex)) sex <- rep('m', (ncol(genodata)-4)) # If there isn't a sex phenotype, treat all as males + outCSVR <- rbind(c('Pheno', '', '', phenotype), # Phenotype + c('sex', '', '', sex), # Sex phenotype for the mice + 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) + return(read.cross(file=out, 'csvr', genotypes=genocodes)) # Load it using R/qtl read.cross + } + """) + def run_rqtl_geno(self): print("Calling R/qtl from python") + #TODO: Need to get this working for other groups/inbred sets, calculating file on the fly + 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 @@ -244,9 +276,14 @@ class MarkerRegression(object): calc_genoprob = ro.r["calc.genoprob"] # Map the calc.genoprob function read_cross = ro.r["read.cross"] # Map the read.cross function write_cross = ro.r["write.cross"] # Map the write.cross function + GENOtoCSVR = ro.r["GENOtoCSVR"] # Map the write.cross function + + genofilelocation = webqtlConfig.HTMLPATH + "genotypes/" + self.dataset.group.name + ".geno" + crossfilelocation = webqtlConfig.HTMLPATH + "genotypes/" + self.dataset.group.name + ".cross" + print("Conversion of geno to cross at location:", genofilelocation, " to ", crossfilelocation) - cross_object = read_cross(file = "BXD.csvr", format = "csvr", dir="/home/zas1024/PLINK2RQTL/test", genotypes = r_c("B","H","D")) + cross_object = GENOtoCSVR(genofilelocation, crossfilelocation) # TODO: Add the SEX if that is available if self.manhattan_plot: cross_object = calc_genoprob(cross_object) @@ -268,10 +305,10 @@ class MarkerRegression(object): if int(self.num_perm) > 0: # Do permutation if(self.control.replace(" ", "") != ""): - covar = self.create_covariatesShort(cross_object) - perm_data_frame = scanone(cross_object, pheno = "the_pheno", addcovar = covar, n_perm=int(self.num_perm)) + covar = self.create_covariates(cross_object) + perm_data_frame = scanone(cross_object, pheno_col = "the_pheno", addcovar = covar, n_perm=int(self.num_perm)) else: - perm_data_frame = scanone(cross_object, pheno = "the_pheno", n_perm=int(self.num_perm)) + perm_data_frame = scanone(cross_object, pheno_col = "the_pheno", n_perm=int(self.num_perm)) self.suggestive, self.significant = self.process_rqtl_perm_results(perm_data_frame) diff --git a/wqflask/wqflask/my_pylmm/pyLMM/lmm.py b/wqflask/wqflask/my_pylmm/pyLMM/lmm.py index 99a5a940..a9744e72 100644 --- a/wqflask/wqflask/my_pylmm/pyLMM/lmm.py +++ b/wqflask/wqflask/my_pylmm/pyLMM/lmm.py @@ -733,12 +733,13 @@ def gn2_redis(key,species): tempdata = temp_data.TempData(params['temp_uuid']) - print('kinship', np.array(params['kinship_matrix'])) + print('pheno', np.array(params['pheno_vector'])) # sys.exit(1) if species == "human" : + print('kinship', np.array(params['kinship_matrix'])) ps, ts = run_human(pheno_vector = np.array(params['pheno_vector']), covariate_matrix = np.array(params['covariate_matrix']), plink_input_file = params['input_file_name'], |