diff options
| -rw-r--r-- | wqflask/wqflask/ctl/ctl_analysis.py | 99 |
1 files changed, 77 insertions, 22 deletions
diff --git a/wqflask/wqflask/ctl/ctl_analysis.py b/wqflask/wqflask/ctl/ctl_analysis.py index 8a2f1954..f998dc59 100644 --- a/wqflask/wqflask/ctl/ctl_analysis.py +++ b/wqflask/wqflask/ctl/ctl_analysis.py @@ -13,6 +13,10 @@ from utility import genofile_parser # genofile_parser import base64 import array import csv +import itertools + +from base import data_set +from base import trait as TRAIT from utility import helper_functions from utility.tools import locate @@ -26,9 +30,11 @@ r_options = ro.r["options"] # Map the options function r_read_csv = ro.r["read.csv"] # Map the read.csv function r_dim = ro.r["dim"] # Map the dim function r_c = ro.r["c"] # Map the c function +r_t = ro.r["t"] # Map the t function r_cat = ro.r["cat"] # Map the cat function r_paste = ro.r["paste"] # Map the paste function r_unlist = ro.r["unlist"] # Map the unlist function +r_head = ro.r["head"] # Map the unlist function r_unique = ro.r["unique"] # Map the unique function r_length = ro.r["length"] # Map the length function r_unlist = ro.r["unlist"] # Map the unlist function @@ -42,6 +48,12 @@ r_is_NA = ro.r["is.na"] # Map the is.na function r_file = ro.r["file"] # Map the file function r_png = ro.r["png"] # Map the png function for plotting r_dev_off = ro.r["dev.off"] # Map the dev.off function +r_save_image = ro.r["save.image"] # Map the save.image function +r_class = ro.r["class"] # Map the class function +r_save = ro.r["save"] # Map the save function +r_write_table = ro.r["write.table"] # Map the write.table function +r_as_data_frame = ro.r["as.data.frame"] # Map the write.table function +r_data_frame = ro.r["data.frame"] # Map the write.table function class CTL(object): def __init__(self): @@ -61,31 +73,73 @@ class CTL(object): def run_analysis(self, requestform): print("Starting CTL analysis on dataset") - self.trait_db_list = [trait.strip() for trait in requestform['trait_list'].split(',')] - print("Retrieved phenotype data from database", requestform['trait_list']) - - helper_functions.get_trait_db_obs(self, self.trait_db_list) - - self.input = {} # self.input contains the phenotype values we need to send to R - strains = [] # All the strains we have data for (contains duplicates) - traits = [] # All the traits we have data for (should not contain duplicates) - genotypebasename = "" - for trait in self.trait_list: - traits.append(trait[0].name) - if genotypebasename == "": - genotypebasename = trait[1].group.name - self.input[trait[0].name] = {} - for strain in trait[0].data: - strains.append(strain) - self.input[trait[0].name][strain] = trait[0].data[strain].value - - genofilelocation = locate(genotypebasename + ".geno", "genotype") + self.trait_db_list = [x for x in self.trait_db_list if x] + + datasetname = self.trait_db_list[0].split(":")[1] + dataset = data_set.create_dataset(datasetname) + + genofilelocation = locate(dataset.group.name + ".geno", "genotype") parser = genofile_parser.ConvertGenoFile(genofilelocation) parser.process_csv() - print(parser.markers) + + individuals = parser.individuals + markers = [] + markernames = [] + x = 1 + for marker in parser.markers: + markernames.append(marker["name"]) + markers.append(marker["genotypes"]) + if x == 1: + print marker["genotypes"] + + x = x +1 + + genotypes = list(itertools.chain(*markers)) + print(len(genotypes) / len(individuals), "==", len(parser.markers)) + + rGeno = r_t(ro.r.matrix(r_unlist(genotypes), nrow=len(markernames), ncol=len(individuals), dimnames = r_list(markernames, individuals), byrow=True)) + + print(r_dim(rGeno)) + #self.trait_names = [trait.split(':')[0].strip() for trait in self.trait_db_list] + #print(self.trait_names) + + + traits = [] + for trait in self.trait_db_list: + print("retrieving data for", trait) + if trait != "": + ts = trait.split(':') + gt = TRAIT.GeneralTrait(name = ts[0], dataset_name = ts[1]) + gt.retrieve_sample_data(individuals) + for ind in individuals: + if ind in gt.data.keys(): + traits.append(gt.data[ind].value) + else: + traits.append("-999") + + print len(traits) / len(individuals), "==", len(self.trait_db_list) + rPheno = r_t(ro.r.matrix(r_unlist(traits), nrow=len(self.trait_db_list), ncol=len(individuals), dimnames = r_list(self.trait_db_list, individuals), byrow=True)) + + rPheno = r_data_frame(rPheno) + rGeno = r_data_frame(rGeno) + + print(r_class(rPheno)) + print(r_class(rGeno)) + + + + r_write_table(rPheno, "~/pheno.csv") + r_write_table(rGeno, "~/geno.csv") + res = self.r_CTLscan(rGeno, rPheno) + self.results = {} - sys.stdout.flush() + self.results['imgurl'] = webqtlUtil.genRandStr("WGCNAoutput_") + ".png" + self.results['imgloc'] = GENERATED_IMAGE_DIR + self.results['imgurl'] + r_png(self.results['imgloc'], width=1000, height=600) + self.r_lineplot(res, significance = 1) + r_dev_off() + # sys.stdout.flush() def render_image(self, results): print("pre-loading imgage results:", self.results['imgloc']) @@ -98,7 +152,8 @@ class CTL(object): def process_results(self, results): print("Processing CTL output") template_vars = {} - template_vars["input"] = self.input + template_vars["results"] = self.results + self.render_image(self.results) sys.stdout.flush() return(dict(template_vars)) |