diff options
| -rw-r--r-- | wqflask/wqflask/ctl/ctl_analysis.py | 19 |
1 files changed, 17 insertions, 2 deletions
diff --git a/wqflask/wqflask/ctl/ctl_analysis.py b/wqflask/wqflask/ctl/ctl_analysis.py index 3159ad7f..8a2f1954 100644 --- a/wqflask/wqflask/ctl/ctl_analysis.py +++ b/wqflask/wqflask/ctl/ctl_analysis.py @@ -8,11 +8,14 @@ import rpy2.rinterface as ri from base.webqtlConfig import GENERATED_IMAGE_DIR from utility import webqtlUtil # Random number for the image +from utility import genofile_parser # genofile_parser import base64 import array +import csv from utility import helper_functions +from utility.tools import locate from rpy2.robjects.packages import importr utils = importr("utils") @@ -43,13 +46,17 @@ r_dev_off = ro.r["dev.off"] # Map the dev.off function class CTL(object): def __init__(self): print("Initialization of CTL") - #log = r_file("/tmp/genenetwork_wcgna.log", open = "wt") + #log = r_file("/tmp/genenetwork_ctl.log", open = "wt") #r_sink(log) # Uncomment the r_sink() commands to log output from stdout/stderr to a file #r_sink(log, type = "message") r_library("ctl") # Load CTL - Should only be done once, since it is quite expensive r_options(stringsAsFactors = False) print("Initialization of CTL done, package loaded in R session") - self.r_CTLscan = ro.r["CTLscan"] # Map the CTLscan function + self.r_CTLscan = ro.r["CTLscan"] # Map the CTLscan function + self.r_CTLsignificant = ro.r["CTLsignificant"] # Map the CTLsignificant function + self.r_lineplot = ro.r["ctl.lineplot"] # Map the ctl.lineplot function + self.r_CTLnetwork = ro.r["CTLnetwork"] # Map the CTLnetwork function + self.r_CTLprofiles = ro.r["CTLprofiles"] # Map the CTLprofiles function print("Obtained pointers to CTL functions") def run_analysis(self, requestform): @@ -57,18 +64,26 @@ class CTL(object): 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") + parser = genofile_parser.ConvertGenoFile(genofilelocation) + parser.process_csv() + print(parser.markers) self.results = {} sys.stdout.flush() |