diff options
Diffstat (limited to 'wqflask')
| -rw-r--r-- | wqflask/wqflask/collect.py | 17 | ||||
| -rw-r--r-- | wqflask/wqflask/marker_regression/marker_regression.py | 194 | ||||
| -rw-r--r-- | wqflask/wqflask/marker_regression/rqtl_mapping.py | 193 | ||||
| -rw-r--r-- | wqflask/wqflask/templates/collections/add.html | 2 | ||||
| -rw-r--r-- | wqflask/wqflask/templates/show_trait_mapping_tools.html | 16 |
5 files changed, 216 insertions, 206 deletions
diff --git a/wqflask/wqflask/collect.py b/wqflask/wqflask/collect.py index 7e7aba89..81d03d6c 100644 --- a/wqflask/wqflask/collect.py +++ b/wqflask/wqflask/collect.py @@ -164,7 +164,7 @@ class UserCollection(object): if not uc: return create_new("Default") else: - uc = model.UserCollection.query.get(params['existing_collection']) + uc = model.UserCollection.query.get(params['existing_collection'].split(":")[0]) members = list(uc.members_as_set()) #set(json.loads(uc.members)) len_before = len(members) @@ -218,7 +218,6 @@ def collections_add(): anon_collections = user_manager.AnonUser().get_collections() collection_names = [] for collection in anon_collections: - print("COLLECTION:", collection) collection_names.append({'id':collection['id'], 'name':collection['name']}) return render_template("collections/add.html", traits = traits, @@ -229,21 +228,17 @@ def collections_add(): @app.route("/collections/new") def collections_new(): params = request.args - #print("request.args in collections_new are:", params) - - collection_name = params['new_collection'] - if "anonymous_add" in params: - AnonCollection(name=collection_name).add_traits(params, "Default") - return redirect(url_for('view_collection')) if "sign_in" in params: return redirect(url_for('login')) if "create_new" in params: print("in create_new") + collection_name = params['new_collection'] return create_new(collection_name) elif "add_to_existing" in params: print("in add to existing") + collection_name = params['existing_collection'].split(":")[1] if g.user_session.logged_in: return UserCollection().add_traits(params, collection_name) else: @@ -251,7 +246,6 @@ def collections_new(): ac.add_traits(params) return redirect(url_for('view_collection', collection_id=ac.id)) else: - print("ELSE") CauseAnError @@ -288,7 +282,6 @@ def create_new(collection_name): ac = AnonCollection(collection_name) ac.changed_timestamp = datetime.datetime.utcnow().strftime('%b %d %Y %I:%M%p') ac.add_traits(params) - print("Collection ID:", ac.id) return redirect(url_for('view_collection', collection_id=ac.id)) @app.route("/collections/list") @@ -367,7 +360,6 @@ def view_collection(): uc_id = params['uc_id'] uc = model.UserCollection.query.get(uc_id) traits = json.loads(uc.members) - print("traits are:", traits) else: user_collections = json.loads(Redis.get(user_manager.AnonUser().key)) this_collection = {} @@ -384,7 +376,6 @@ def view_collection(): json_version = [] for atrait in traits: - print("atrait is:", atrait) name, dataset_name = atrait.split(':') trait_ob = trait.GeneralTrait(name=name, dataset_name=dataset_name) @@ -393,8 +384,6 @@ def view_collection(): json_version.append(trait_ob.jsonable()) - print("trait_obs:", trait_obs) - if "uc_id" in params: collection_info = dict(trait_obs=trait_obs, uc = uc) diff --git a/wqflask/wqflask/marker_regression/marker_regression.py b/wqflask/wqflask/marker_regression/marker_regression.py index d7c78db0..f28407b3 100644 --- a/wqflask/wqflask/marker_regression/marker_regression.py +++ b/wqflask/wqflask/marker_regression/marker_regression.py @@ -35,7 +35,7 @@ from utility import helper_functions from utility import Plot, Bunch from utility import temp_data from utility.benchmark import Bench -from wqflask.marker_regression import gemma_mapping +from wqflask.marker_regression import gemma_mapping, rqtl_mapping from utility.tools import locate, locate_ignore_error, PYLMM_COMMAND, GEMMA_COMMAND, PLINK_COMMAND, TEMPDIR from utility.external import shell @@ -169,7 +169,10 @@ class MarkerRegression(object): self.model = start_vars['mapmodel_rqtl_geno'] if start_vars['pair_scan'] == "true": self.pair_scan = True - results = self.run_rqtl_geno() + if self.permCheck and self.num_perm > 0: + perm_output, self.suggestive, self.significant, results = rqtl_mapping.run_rqtl_geno(self.vals, self.dataset, self.method, self.model, self.permCheck, self.num_perm, self.do_control, self.control_marker, self.manhattan_plot, self.pair_scan) + else: + results = rqtl_mapping.run_rqtl_geno(self.vals, self.dataset, self.method, self.model, self.permCheck, self.num_perm, self.do_control, self.control_marker, self.manhattan_plot, self.pair_scan) elif self.mapping_method == "reaper": if "startMb" in start_vars: #ZS: Check if first time page loaded, so it can default to ON if "additiveCheck" in start_vars: @@ -353,193 +356,6 @@ 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 - - ro.r(""" - trim <- function( x ) { gsub("(^[[:space:]]+|[[:space:]]+$)", "", x) } - - getGenoCode <- function(header, name = 'unk'){ - mat = which(unlist(lapply(header,function(x){ length(grep(paste('@',name,sep=''), x)) })) == 1) - return(trim(strsplit(header[mat],':')[[1]][2])) - } - - GENOtoCSVR <- function(genotypes = '%s', out = 'cross.csvr', phenotype = NULL, sex = NULL, verbose = FALSE){ - 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 - type <- getGenoCode(header, 'type') - 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') - 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) - 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) - } - """ % (self.dataset.group.name + ".geno")) - - def run_rqtl_geno(self): - 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 - plot = ro.r["plot"] # Map the plot function - postscript = ro.r["postscript"] # Map the postscript function - png = ro.r["png"] # Map the png function - dev_off = ro.r["dev.off"] # Map the device off function - - print(r_library("qtl")) # Load R/qtl - - ## Get pointers to some R/qtl functions - scanone = ro.r["scanone"] # Map the scanone function - scantwo = ro.r["scantwo"] # Map the scantwo function - 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 local GENOtoCSVR function - - crossname = self.dataset.group.name - genofilelocation = locate(crossname + ".geno", "genotype") - crossfilelocation = TMPDIR + crossname + ".cross" - - #print("Conversion of geno to cross at location:", genofilelocation, " to ", crossfilelocation) - - cross_object = GENOtoCSVR(genofilelocation, crossfilelocation) # TODO: Add the SEX if that is available - - if self.manhattan_plot: - cross_object = calc_genoprob(cross_object) - else: - cross_object = calc_genoprob(cross_object, step=1, stepwidth="max") - - cross_object = self.add_phenotype(cross_object, self.sanitize_rqtl_phenotype()) # Add the phenotype - - # for debug: write_cross(cross_object, "csvr", "test.csvr") - - # Scan for QTLs - covar = self.create_covariates(cross_object) # Create the additive covariate matrix - - if self.pair_scan: - if self.do_control == "true": # If sum(covar) > 0 we have a covariate matrix - print("Using covariate"); result_data_frame = scantwo(cross_object, pheno = "the_pheno", addcovar = covar, model=self.model, method=self.method, n_cluster = 16) - else: - print("No covariates"); result_data_frame = scantwo(cross_object, pheno = "the_pheno", model=self.model, method=self.method, n_cluster = 16) - - #print("Pair scan results:", result_data_frame) - - self.pair_scan_filename = webqtlUtil.genRandStr("scantwo_") + ".png" - png(file=TEMPDIR+self.pair_scan_filename) - plot(result_data_frame) - dev_off() - - return self.process_pair_scan_results(result_data_frame) - - else: - if self.do_control == "true": - print("Using covariate"); result_data_frame = scanone(cross_object, pheno = "the_pheno", addcovar = covar, model=self.model, method=self.method) - else: - print("No covariates"); result_data_frame = scanone(cross_object, pheno = "the_pheno", model=self.model, method=self.method) - - if self.num_perm > 0 and self.permCheck == "ON": # Do permutation (if requested by user) - if self.do_control == "true": - perm_data_frame = scanone(cross_object, pheno_col = "the_pheno", addcovar = covar, n_perm = self.num_perm, model=self.model, method=self.method) - else: - perm_data_frame = scanone(cross_object, pheno_col = "the_pheno", n_perm = 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 - - return self.process_rqtl_results(result_data_frame) - - def add_phenotype(self, cross, pheno_as_string): - ro.globalenv["the_cross"] = cross - ro.r('the_cross$pheno <- cbind(pull.pheno(the_cross), the_pheno = '+ pheno_as_string +')') - return ro.r["the_cross"] - - def create_covariates(self, cross): - ro.globalenv["the_cross"] = cross - ro.r('genotypes <- pull.geno(the_cross)') # Get the genotype matrix - userinputS = self.control_marker.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 - #print("R/qtl matrix of covariates:", ro.r["covariates"]) - return ro.r["covariates"] - - def sanitize_rqtl_phenotype(self): - pheno_as_string = "c(" - for i, val in enumerate(self.vals): - if val == "x": - if i < (len(self.vals) - 1): - pheno_as_string += "NA," - else: - pheno_as_string += "NA" - else: - if i < (len(self.vals) - 1): - pheno_as_string += str(val) + "," - else: - pheno_as_string += str(val) - pheno_as_string += ")" - return pheno_as_string - - def process_pair_scan_results(self, result): - pair_scan_results = [] - - result = result[1] - output = [tuple([result[j][i] for j in range(result.ncol)]) for i in range(result.nrow)] - #print("R/qtl scantwo output:", output) - - for i, line in enumerate(result.iter_row()): - marker = {} - marker['name'] = result.rownames[i] - marker['chr1'] = output[i][0] - marker['Mb'] = output[i][1] - marker['chr2'] = int(output[i][2]) - pair_scan_results.append(marker) - - #print("pair_scan_results:", pair_scan_results) - - return pair_scan_results - - def process_rqtl_results(self, result): # TODO: how to make this a one liner and not copy the stuff in a loop - qtl_results = [] - - output = [tuple([result[j][i] for j in range(result.ncol)]) for i in range(result.nrow)] - #print("R/qtl scanone output:", output) - - for i, line in enumerate(result.iter_row()): - marker = {} - marker['name'] = result.rownames[i] - marker['chr'] = output[i][0] - marker['Mb'] = output[i][1] - marker['lod_score'] = output[i][2] - qtl_results.append(marker) - - return qtl_results - - def process_rqtl_perm_results(self, results): - perm_vals = [] - for line in str(results).split("\n")[1:(self.num_perm+1)]: - #print("R/qtl permutation line:", line.split()) - perm_vals.append(float(line.split()[1])) - - self.perm_output = perm_vals - self.suggestive = np.percentile(np.array(perm_vals), 67) - self.significant = np.percentile(np.array(perm_vals), 95) - - return self.suggestive, self.significant - - def run_plink(self): plink_output_filename = webqtlUtil.genRandStr("%s_%s_"%(self.dataset.group.name, self.this_trait.name)) diff --git a/wqflask/wqflask/marker_regression/rqtl_mapping.py b/wqflask/wqflask/marker_regression/rqtl_mapping.py new file mode 100644 index 00000000..93bf717c --- /dev/null +++ b/wqflask/wqflask/marker_regression/rqtl_mapping.py @@ -0,0 +1,193 @@ +import rpy2.robjects as ro +import numpy as np + +from base.webqtlConfig import TMPDIR +from utility import webqtlUtil +from utility.tools import locate, TEMPDIR + +def run_rqtl_geno(vals, dataset, method, model, permCheck, num_perm, do_control, control_marker, manhattan_plot, pair_scan): + geno_to_rqtl_function(dataset) + + ## 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 + plot = ro.r["plot"] # Map the plot function + postscript = ro.r["postscript"] # Map the postscript function + png = ro.r["png"] # Map the png function + dev_off = ro.r["dev.off"] # Map the device off function + + print(r_library("qtl")) # Load R/qtl + + ## Get pointers to some R/qtl functions + scanone = ro.r["scanone"] # Map the scanone function + scantwo = ro.r["scantwo"] # Map the scantwo function + 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 local GENOtoCSVR function + + crossname = dataset.group.name + genofilelocation = locate(crossname + ".geno", "genotype") + crossfilelocation = TMPDIR + crossname + ".cross" + + #print("Conversion of geno to cross at location:", genofilelocation, " to ", crossfilelocation) + + cross_object = GENOtoCSVR(genofilelocation, crossfilelocation) # TODO: Add the SEX if that is available + + if manhattan_plot: + cross_object = calc_genoprob(cross_object) + else: + cross_object = calc_genoprob(cross_object, step=1, stepwidth="max") + + cross_object = add_phenotype(cross_object, sanitize_rqtl_phenotype(vals)) # Add the phenotype + + # for debug: write_cross(cross_object, "csvr", "test.csvr") + + # Scan for QTLs + covar = create_covariates(control_marker, cross_object) # Create the additive covariate matrix + + if pair_scan: + if do_control == "true": # If sum(covar) > 0 we have a covariate matrix + print("Using covariate"); result_data_frame = scantwo(cross_object, pheno = "the_pheno", addcovar = covar, model=model, method=method, n_cluster = 16) + else: + print("No covariates"); result_data_frame = scantwo(cross_object, pheno = "the_pheno", model=model, method=method, n_cluster = 16) + + #print("Pair scan results:", result_data_frame) + + pair_scan_filename = webqtlUtil.genRandStr("scantwo_") + ".png" + png(file=TEMPDIR+pair_scan_filename) + plot(result_data_frame) + dev_off() + + return process_pair_scan_results(result_data_frame) + else: + if do_control == "true": + print("Using covariate"); result_data_frame = scanone(cross_object, pheno = "the_pheno", addcovar = covar, model=model, method=method) + else: + print("No covariates"); result_data_frame = scanone(cross_object, pheno = "the_pheno", model=model, method=method) + + if num_perm > 0 and permCheck == "ON": # Do permutation (if requested by user) + if do_control == "true": + perm_data_frame = scanone(cross_object, pheno_col = "the_pheno", addcovar = covar, n_perm = num_perm, model=model, method=method) + else: + perm_data_frame = scanone(cross_object, pheno_col = "the_pheno", n_perm = num_perm, model=model, method=method) + + perm_output, suggestive, significant = process_rqtl_perm_results(num_perm, perm_data_frame) # Functions that sets the thresholds for the webinterface + return perm_output, suggestive, significant, process_rqtl_results(result_data_frame) + else: + return process_rqtl_results(result_data_frame) + +def geno_to_rqtl_function(dataset): # TODO: Need to figure out why some genofiles have the wrong format and don't convert properly + + ro.r(""" + trim <- function( x ) { gsub("(^[[:space:]]+|[[:space:]]+$)", "", x) } + + getGenoCode <- function(header, name = 'unk'){ + mat = which(unlist(lapply(header,function(x){ length(grep(paste('@',name,sep=''), x)) })) == 1) + return(trim(strsplit(header[mat],':')[[1]][2])) + } + + GENOtoCSVR <- function(genotypes = '%s', out = 'cross.csvr', phenotype = NULL, sex = NULL, verbose = FALSE){ + header = readLines(genotypes, 40) # Assume a geno header is not longer than 40 lines + toskip = which(unlist(lapply(header, function(x){ length(grep("Chr\t", x)) })) == 1)-1 # Major hack to skip the geno headers + + genocodes <- c(getGenoCode(header, 'mat'), getGenoCode(header, 'het'), getGenoCode(header, 'pat')) # Get the genotype codes + type <- getGenoCode(header, 'type') + genodata <- read.csv(genotypes, sep='\t', skip=toskip, header=TRUE, na.strings=getGenoCode(header,'unk'), colClasses='character', comment.char = '#') + cat('Genodata:', toskip, " ", dim(genodata), genocodes, '\n') + if(is.null(phenotype)) phenotype <- runif((ncol(genodata)-4)) # If there isn't a phenotype, generate a random one + if(is.null(sex)) sex <- rep('m', (ncol(genodata)-4)) # If there isn't a sex phenotype, treat all as males + outCSVR <- rbind(c('Pheno', '', '', phenotype), # Phenotype + c('sex', '', '', sex), # Sex phenotype for the mice + cbind(genodata[,c('Locus','Chr', 'cM')], genodata[, 5:ncol(genodata)])) # Genotypes + write.table(outCSVR, file = out, row.names=FALSE, col.names=FALSE,quote=FALSE, sep=',') # Save it to a file + require(qtl) + cross = read.cross(file=out, 'csvr', genotypes=genocodes) # Load the created cross file using R/qtl read.cross + if(type == 'riset') cross <- convert2riself(cross) # If its a RIL, convert to a RIL in R/qtl + return(cross) + } + """ % (dataset.group.name + ".geno")) + +def add_phenotype(cross, pheno_as_string): + ro.globalenv["the_cross"] = cross + ro.r('the_cross$pheno <- cbind(pull.pheno(the_cross), the_pheno = '+ pheno_as_string +')') + return ro.r["the_cross"] + +def create_covariates(control_marker, cross): + ro.globalenv["the_cross"] = cross + ro.r('genotypes <- pull.geno(the_cross)') # Get the genotype matrix + userinputS = control_marker.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 + #print("R/qtl matrix of covariates:", ro.r["covariates"]) + return ro.r["covariates"] + +def sanitize_rqtl_phenotype(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 process_pair_scan_results(result): + pair_scan_results = [] + + result = result[1] + output = [tuple([result[j][i] for j in range(result.ncol)]) for i in range(result.nrow)] + #print("R/qtl scantwo output:", output) + + for i, line in enumerate(result.iter_row()): + marker = {} + marker['name'] = result.rownames[i] + marker['chr1'] = output[i][0] + marker['Mb'] = output[i][1] + marker['chr2'] = int(output[i][2]) + pair_scan_results.append(marker) + + #print("pair_scan_results:", pair_scan_results) + + return pair_scan_results + +def process_rqtl_perm_results(num_perm, results): + perm_vals = [] + for line in str(results).split("\n")[1:(num_perm+1)]: + #print("R/qtl permutation line:", line.split()) + perm_vals.append(float(line.split()[1])) + + perm_output = perm_vals + suggestive = np.percentile(np.array(perm_vals), 67) + significant = np.percentile(np.array(perm_vals), 95) + print("SIGNIFICANT:", significant) + + return perm_output, suggestive, significant + +def process_rqtl_results(result): # TODO: how to make this a one liner and not copy the stuff in a loop + qtl_results = [] + + output = [tuple([result[j][i] for j in range(result.ncol)]) for i in range(result.nrow)] + #print("R/qtl scanone output:", output) + + for i, line in enumerate(result.iter_row()): + marker = {} + marker['name'] = result.rownames[i] + marker['chr'] = output[i][0] + marker['Mb'] = output[i][1] + marker['lod_score'] = output[i][2] + qtl_results.append(marker) + + return qtl_results \ No newline at end of file diff --git a/wqflask/wqflask/templates/collections/add.html b/wqflask/wqflask/templates/collections/add.html index 47b87d73..d45aa015 100644 --- a/wqflask/wqflask/templates/collections/add.html +++ b/wqflask/wqflask/templates/collections/add.html @@ -25,7 +25,7 @@ <select name="existing_collection" class="form-control"> {% for col in collections %} - <option value="{{ col.id }}">{{ col.name }}</option> + <option value="{{ col.id }}:{{ col.name }}">{{ col.name }}</option> {% endfor %} </select> <br /> diff --git a/wqflask/wqflask/templates/show_trait_mapping_tools.html b/wqflask/wqflask/templates/show_trait_mapping_tools.html index 3d9c2521..9c1101ca 100644 --- a/wqflask/wqflask/templates/show_trait_mapping_tools.html +++ b/wqflask/wqflask/templates/show_trait_mapping_tools.html @@ -32,6 +32,18 @@ {% if use_pylmm_rqtl and not use_plink_gemma and dataset.group.species != "human" %} <div class="tab-pane active" id="interval_mapping"> <div style="margin-top: 20px" class="form-horizontal"> + {% if genofiles and genofiles|length>0 %} + <div class="mapping_method_fields form-group"> + <label for="genofiles" class="col-xs-3 control-label">Geno File</label> + <div style="margin-left: 20px;" class="col-xs-4 controls"> + <select name="genofile" class="form-control"> + {% for item in genofiles %} + <option value="{{item[0]}}">{{item[1]}}</option> + {% endfor %} + </select> + </div> + </div> + {% endif %} <div class="mapping_method_fields form-group"> <label for="mapping_permutations" class="col-xs-3 control-label">Permutations</label> <div style="margin-left: 20px;" class="col-xs-4 controls"> @@ -90,8 +102,8 @@ <div class="mapping_method_fields form-group"> - <label style="text-align:left;" class="col-xs-12 control-label">Marker Regr.</label> - <div class="col-xs-12 controls"> + <label style="text-align:left;" class="col-xs-3 control-label">Marker<br>Regression</label> + <div style="margin-left: 20px;" class="col-xs-4 controls"> <label class="radio-inline"> <input type="radio" name="manhattan_plot_reaper" value="True"> Yes |