diff options
Diffstat (limited to 'wqflask')
| -rw-r--r-- | wqflask/wqflask/marker_regression/rqtl_mapping.py | 71 |
1 files changed, 57 insertions, 14 deletions
diff --git a/wqflask/wqflask/marker_regression/rqtl_mapping.py b/wqflask/wqflask/marker_regression/rqtl_mapping.py index e1aa290b..152bb5be 100644 --- a/wqflask/wqflask/marker_regression/rqtl_mapping.py +++ b/wqflask/wqflask/marker_regression/rqtl_mapping.py @@ -12,6 +12,7 @@ import utility.logger logger = utility.logger.getLogger(__name__ ) def run_rqtl_geno(vals, samples, dataset, method, model, permCheck, num_perm, perm_strata_list, do_control, control_marker, manhattan_plot, pair_scan, cofactors): + logger.info("Start run_rqtl_geno"); ## 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 @@ -21,6 +22,8 @@ def run_rqtl_geno(vals, samples, dataset, method, model, permCheck, num_perm, pe print(r_library("qtl")) # Load R/qtl + logger.info("QTL library loaded"); + ## Get pointers to some R/qtl functions scanone = ro.r["scanone"] # Map the scanone function scantwo = ro.r["scantwo"] # Map the scantwo function @@ -40,28 +43,35 @@ def run_rqtl_geno(vals, samples, dataset, method, model, permCheck, num_perm, pe genofilelocation = locate(dataset.group.genofile, "genotype") else: genofilelocation = locate(dataset.group.name + ".geno", "genotype") + logger.info("Going to create a cross from geno"); cross_object = GENOtoCSVR(genofilelocation, crossfilelocation) # TODO: Add the SEX if that is available - + logger.info("before calc_genoprob"); if manhattan_plot: cross_object = calc_genoprob(cross_object) else: - cross_object = calc_genoprob(cross_object, step=1, stepwidth="max") - + cross_object = calc_genoprob(cross_object, step=5, stepwidth="max") + logger.info("after calc_genoprob"); pheno_string = sanitize_rqtl_phenotype(vals) - + logger.info("phenostring done"); + names_string = sanitize_rqtl_names(samples) + logger.info("sanitized pheno and names"); cross_object = add_phenotype(cross_object, pheno_string, "the_pheno") # Add the phenotype - + cross_object = add_names(cross_object, names_string, "the_names") # Add the phenotype + logger.info("Added pheno and names"); # Scan for QTLs marker_covars = create_marker_covariates(control_marker, cross_object) # Create the additive covariate markers - + logger.info("Marker covars done"); if cofactors != "": cross_object, trait_covars = add_cofactors(cross_object, dataset, cofactors, samples) # Create the covariates from selected traits ro.r('all_covars <- cbind(marker_covars, trait_covars)') else: ro.r('all_covars <- marker_covars') - + #logger.info("Saving"); + #ro.r('save.image(file = "/home/dannya/gn2-danny/cross.RData")') + #logger.info("Saving Done"); covars = ro.r['all_covars'] - + #DEBUG to save the session object to file + #ro.r('save.image(file = "/home/dannya/gn2-danny/all.RData")') if pair_scan: if do_control == "true": logger.info("Using covariate"); result_data_frame = scantwo(cross_object, pheno = "the_pheno", addcovar = covars, model=model, method=method, n_cluster = 16) @@ -128,7 +138,7 @@ def generate_cross_from_geno(dataset): # TODO: Need to figure out why som if(type == '4-way'){ genocodes <- c('1','2','3','4') } else { - genocodes <- c(getGenoCode(header, 'mat'), getGenoCode(header, 'het'), getGenoCode(header, 'pat')) # Get the genotype codes + 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), genocodes, '\n') @@ -139,8 +149,17 @@ def generate_cross_from_geno(dataset): # TODO: Need to figure out why som 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) # 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 + if(type == '4-way'){ + cat('Loading in as 4-WAY\n') + cross = read.cross(file=out, 'csvr', genotypes=genocodes, crosstype="4way", convertXdata=FALSE) # Load the created cross file using R/qtl read.cross + }else{ + cat('Loading in as normal\n') + cross = read.cross(file=out, 'csvr', genotypes=genocodes) # Load the created cross file using R/qtl read.cross + } + if(type == 'riset'){ + cat('Converting to RISELF\n') + cross <- convert2riself(cross) # If its a RIL, convert to a RIL in R/qtl + } return(cross) } """ % (dataset.group.genofile)) @@ -176,9 +195,33 @@ def sanitize_rqtl_phenotype(vals): return pheno_as_string +def sanitize_rqtl_names(vals): + pheno_as_string = "c(" + for i, val in enumerate(vals): + if val == "x": + if i < (len(vals) - 1): + pheno_as_string += "NA," + else: + pheno_as_string += "NA" + else: + if i < (len(vals) - 1): + pheno_as_string += "'" + str(val) + "'," + else: + pheno_as_string += "'" + str(val) + "'" + pheno_as_string += ")" + + return pheno_as_string + def add_phenotype(cross, pheno_as_string, col_name): ro.globalenv["the_cross"] = cross - ro.r('the_cross$pheno <- cbind(pull.pheno(the_cross), ' + col_name + ' = '+ pheno_as_string +')') + ro.r('pheno <- data.frame(pull.pheno(the_cross))') + ro.r('the_cross$pheno <- cbind(pheno, ' + col_name + ' = as.numeric('+ pheno_as_string +'))') + return ro.r["the_cross"] + +def add_names(cross, names_as_string, col_name): + ro.globalenv["the_cross"] = cross + ro.r('pheno <- data.frame(pull.pheno(the_cross))') + ro.r('the_cross$pheno <- cbind(pheno, ' + col_name + ' = '+ names_as_string +')') return ro.r["the_cross"] def pull_var(var_name, cross, var_string): @@ -204,8 +247,8 @@ def add_cofactors(cross, this_dataset, covariates, samples): this_dataset.group.get_samplelist() trait_samples = this_dataset.group.samplelist trait_sample_data = trait_ob.data - for index, sample in enumerate(trait_samples): - if sample in samples: + for index, sample in enumerate(samples): + if sample in trait_samples: if sample in trait_sample_data: sample_value = trait_sample_data[sample].value this_covar_data.append(sample_value) |