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-rw-r--r--wqflask/wqflask/collect.py17
-rw-r--r--wqflask/wqflask/marker_regression/marker_regression.py194
-rw-r--r--wqflask/wqflask/marker_regression/rqtl_mapping.py193
-rw-r--r--wqflask/wqflask/templates/collections/add.html2
-rw-r--r--wqflask/wqflask/templates/show_trait_mapping_tools.html16
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&nbsp;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
generated by cgit v1.2.3 (git 2.44.0) at 2024-11-22 22:32:24 +0000