class RNASeqFrame(PipelineFrame):
def __init__(self, pipepanel, pipeline_name, *args, **kwargs):
PipelineFrame.__init__(self, pipepanel, pipeline_name, *args, **kwargs)
self.info = None
eframe = self.eframe = LabelFrame(self, text="Options")
#,fg=textLightColor,bg=baseColor)
eframe.grid(row=5, column=1, sticky=W, columnspan=7, padx=10, pady=5)
label = Label(eframe,
text="Pipeline") #,fg=textLightColor,bg=baseColor)
label.grid(row=3, column=0, sticky=W, padx=10, pady=5)
Pipelines = ["initialqcrnaseq", "rnaseq"]
Pipeline = self.Pipeline = StringVar()
Pipeline.set(Pipelines[0])
om = OptionMenu(eframe,
Pipeline,
*Pipelines,
command=self.option_controller)
om.config() #bg = widgetBgColor,fg=widgetFgColor)
om["menu"].config() #bg = widgetBgColor,fg=widgetFgColor)
#om.pack(side=LEFT,padx=20,pady=5)
om.grid(row=3, column=1, sticky=W, padx=10, pady=5)
rReadlens = [
'Read Length is 50', 'Read Length is 75', 'Read Length is 100',
'Read Length is 125', 'Read Length is 150', 'Read Length is 250'
]
self.rReadlen = rReadlen = StringVar()
rReadlen.set(rReadlens[2])
self.om2 = OptionMenu(eframe,
rReadlen,
*rReadlens,
command=self.option_controller)
#self.om2.grid(row=4,column=1,sticky=W,padx=10,pady=5)
rStrands = [
'0, Reads are Unstranded', '1, Reads are from Sense Strand',
'2, Reads are from Anti-Sense Strand'
]
self.rStrand = rStrand = StringVar()
rStrand.set(rStrands[0])
self.om3 = OptionMenu(eframe,
rStrand,
*rStrands,
command=self.option_controller)
#self.om3.grid(row=5,column=1,sticky=W,padx=10,pady=5)
rDegs = [
"no, Do not Report Differentially Expressed Genes",
"yes, Report Differentially Expressed Genes"
]
self.rDeg = rDeg = StringVar()
rDeg.set(rDegs[0])
self.om4 = OptionMenu(eframe,
rDeg,
*rDegs,
command=self.option_controller)
self.om4.grid(row=6, column=1, sticky=W, padx=10, pady=5)
#####################
#Sample Threshold
#####################
self.sampleLF = sampleLF = LabelFrame(
eframe, text="Low Abundance Gene Thresholds")
self.rMincount = rMincount = StringVar()
rMincount.set("5")
self.rMinsamples = rMinsamples = StringVar()
rMinsamples.set("2")
#rMincount.trace('w', lambda a,b,c,x="rmincount": makejson(x))
#Filter out genes < [5] read counts in < [2] samples
rminsamplesL = Label(sampleLF, text="Include genes with >=") # in")
rmincountE = Entry(sampleLF, bd=2, width=3, textvariable=rMincount)
rmincountL = Label(sampleLF, text="read counts in >=")
rminsamplesE = Entry(sampleLF, bd=2, width=3, textvariable=rMinsamples)
rminsamplesR = Label(sampleLF, text="samples")
rminsamplesL.grid(row=9, column=1, sticky=W, padx=10, pady=5)
rmincountE.grid(row=9, column=2, sticky=W, padx=0, pady=5)
rmincountL.grid(row=9, column=3, sticky=W, padx=5, pady=5)
rminsamplesE.grid(row=9, column=4, sticky=W, padx=0, pady=5)
rminsamplesR.grid(row=9, column=5, sticky=W, padx=10, pady=5)
#rMinsamples.trace('w', lambda a,b,c,x="rmincount": makejson(x))
sampleLF.grid(row=8,
column=0,
columnspan=4,
sticky=W,
padx=20,
pady=10)
#####################
self.add_info(eframe)
self.option_controller()
def option_controller(self, *args, **kwargs):
PipelineFrame.option_controller(self)
if self.Pipeline.get() == 'initialqcrnaseq':
self.om4.grid_forget()
self.sampleLF.grid_forget()
else:
self.om4.grid(row=6, column=1, sticky=W, padx=10, pady=5)
self.sampleLF.grid(row=8,
column=0,
columnspan=4,
sticky=W,
padx=20,
pady=10)
def makejson_wrapper(self, *args, **kwargs):
self.makejson(*args, **kwargs)
def add_info(self, parent):
if not self.info:
self.info = LabelFrame(parent, text="Sample Information")
self.groups_button = Button(self.info,
text="Set Groups",
command=self.popup_groups)
self.contrasts_button = Button(self.info,
text="Set Contrasts",
command=self.popup_contrasts)
#self.pairs_load_button.pack( side=BOTTOM, padx=5, pady=5 )
#self.pairs_save_button.pack( side=BOTTOM, padx=5, pady=5 )
self.groups_button.grid(row=5, column=5, padx=10, pady=5)
self.contrasts_button.grid(row=5, column=6, padx=10, pady=5)
self.info.grid(row=10,
column=0,
columnspan=6,
sticky=W,
padx=20,
pady=10)
def popup_groups(self):
self.popup_window("Groups Information", "groups.tab")
def popup_contrasts(self):
self.popup_window("Contrasts Information", "contrasts.tab")
def popup_window(self, text, filename):
top = Toplevel()
info = LabelFrame(top, text=text) #"Group Information")
info_text = Text(
info,
width=50,
height=8,
#bg=projectBgColor,
#fg=projectFgColor,
font=("nimbus mono bold", "11"))
def savefunc():
self.writepaste(filename, info_text)
def loadfunc():
self.readpaste(filename, info_text)
info_save_button = Button(info, text="Save", command=savefunc)
info_load_button = Button(info, text="Load", command=loadfunc)
#self.pairs_load_button.pack( side=BOTTOM, padx=5, pady=5 )
#self.pairs_save_button.pack( side=BOTTOM, padx=5, pady=5 )
info_load_button.grid(row=5, column=5, padx=10, pady=5)
info_save_button.grid(row=5, column=6, padx=10, pady=5)
info_text.grid(row=1,
rowspan=3,
column=1,
columnspan=7,
padx=5,
pady=5)
info.grid(row=7, column=0, columnspan=6, sticky=W, padx=20, pady=10)
top.focus_force()
def makejson(self, *args):
#print(args[0])
caller = args[0]
#global PD
#global UnitsBak
#global RGbak
D = dict()
try:
F = open(self.workpath.get() + "/samples", "r")
f = F.read().split("\n")
F.close()
for line in f:
L = line.split()
a = L.pop(0)
D[a] = L
samples = D
except:
samples = {"na": "na"}
D = dict()
try:
F = open(self.workpath.get() + "/pairs", "r")
f = F.read().split()
F.close()
for i in range(0, len(f), 2):
# a=f[i].split(".")[0]
# b=f[i+1].split(".")[0]
a = f[i]
b = f[i + 1]
D[a + "+" + b] = [a, b]
pairs = D
except:
pairs = {"na": "na"}
D = dict()
try:
F = open(self.workpath.get() + "/contrasts.tab", "r")
# f=F.read().split('\n')
# F.close()
# D["rsamps"]=f[0].split()
# D["rgroups"]=f[1].split()
# D["rcontrasts"]=f[2].split()
# D["rlabels"]=f[3].split()
f = F.readlines()
F.close()
## sampl=[]
## grp=[]
cont = []
## lbl=[]
for x in f:
if len(x.split()) == 2:
cont.append(x.split()[0])
cont.append(x.split()[1])
D["rcontrasts"] = cont
# contrasts["rcontrasts"]=cont
contrasts = D
except:
contrasts = {"rcontrasts": "na"}
## contrasts={"rsamps":"na","rgroups":"na","rcontrasts":"na","rlabels":"na"}
##------
D = dict()
try:
F = open(self.workpath.get() + "/groups.tab", "r")
f = F.readlines()
F.close()
sampl = []
grp = []
# cont=[]
lbl = []
for x in f:
# if len(x.split()) == 4 or len(x.split()) == 3:
if len(x.split()) == 3:
sampl.append(x.split()[0])
grp.append(x.split()[1])
lbl.append(x.split()[2])
D["rsamps"] = sampl
D["rgroups"] = grp
D["rlabels"] = lbl
# D["rcontrasts"]="na"
# contrasts=D
groups = D
except:
# contrasts={"rsamps":"na","rgroups":"na","rcontrasts":"na","rlabels":"na"}
groups = {"rsamps": "na", "rgroups": "na", "rlabels": "na"}
##------
D = dict()
FT = filetype #.get()
# p = Popen("ls "+workpath.get()+"/*."+FT, shell=True, stdin=PIPE, stdout=PIPE, stderr=DEVNULL, close_fds=True)
p = Popen("find " + self.workpath.get() +
" -maxdepth 1 -type l -printf '%f\n' ",
shell=True,
stdin=PIPE,
stdout=PIPE,
stderr=DEVNULL,
close_fds=True)
a = p.stdout.read().decode(encoding='UTF-8').split("\n")
RG = dict()
b = a.pop()
# tkinter.messagebox.showerror("",a)
# if freezeunits.get()=="no":
for i in a:
key = re.sub(".realign", "", i.split("/")[-1])
key = re.sub(".bai", "", key)
key = re.sub(".bam", "", key)
key = re.sub(".sam", "", key)
key = re.sub(".recal", "", key)
key = re.sub(".dedup", "", key)
key = re.sub(".sorted", "", key)
key = re.sub(".fin", "", key)
key = re.sub(".R[12]", "", key)
key = re.sub("_R[12]", "", key)
key = re.sub(".fastq", "", key)
key = re.sub(".gz", "", key)
# key=re.sub("[\._](R[12]\.)*"+FT+"$","",i.split("/")[-1])
# key=re.sub(".R[12]."+FT+"$","",i.split("/")[-1])
# key=re.sub("([._]R[12][._])*([fin|sorted|dedup|recal|realign])*\.{0}$".format(FT),"",i.split("/")[-1])
D[key] = key
RG[key] = {
'rgsm': key,
'rglb': 'na',
'rgpu': 'na',
'rgpl': 'ILLUMINA',
'rgcn': 'na'
}
units = D
UnitsBak = D
try:
F = open(self.workpath.get() + "/rg.tab", "r")
f = F.read().splitlines()
F.close()
for theLine in f:
if not re.match("^ID", theLine):
(rgid, rgsm, rglb, rgpl, rgpu, rgcn) = theLine.split("\t")
RG[rgid] = {
'rgsm': rgsm,
'rglb': rglb,
'rgpu': rgpu,
'rgpl': rgpl,
'rgcn': rgcn
}
except:
pass
RGbak = RG
# else:
# units=UnitsBak
# RG=RGbak
#
PD = dict()
smparams = []
for i in range(len(self.parameters)):
if cp[i].var.get() == "1":
smparams.append(parameters[i])
AD = eval(
open(join(PIPELINER_HOME,
self.annotation.get() + ".json"), "r").read())
SD = AD['references']['rnaseq']['STARDIR']
# tkinter.messagebox.showinfo("initLock","SD={0}".format(SD))
gi = self.global_info
PD = {
'project': {
'pfamily':
gi.pfamily.get(),
'units':
units,
'samples':
samples,
'pairs':
pairs,
'id':
gi.eprojectid.get(),
'pi':
gi.epi.get(),
'organism':
gi.eorganism.get(),
'analyst':
gi.eanalyst.get(),
'poc':
gi.epoc.get(),
'pipeline':
self.Pipeline.get(),
'version':
"1.0",
'annotation':
gi.annotation.get(),
'datapath':
self.datapath.get(),
'targetspath':
self.targetspath.get(),
'filetype':
filetype,
'binset':
"standard-bin",
'username':
gi.euser.get(),
'flowcellid':
gi.eflowcell.get(),
'platform':
gi.eplatform.get(),
'custom':
customRules,
'efiletype':
efiletype,
'workpath':
self.workpath.get(),
'batchsize':
batchsize,
"smparams":
smparams,
"rgid":
RG,
"cluster":
"cluster_medium.json",
"description":
gi.description.get('1.0', END),
"technique":
gi.technique.get(),
"TRIM":
"yes",
"groups":
groups,
"contrasts":
contrasts,
"SJDBOVERHANG":
self.rReadlen.get().split(" ")[3],
"STRANDED":
self.rStrand.get().split(",")[0],
"DEG":
self.rDeg.get().split(",")[0].lower(),
"STARSTRANDCOL":
"{0}".format(int(self.rStrand.get().split(",")[0]) + 2),
"MINSAMPLES":
self.rMinsamples.get(),
"MINCOUNTGENES":
self.rMincount.get(),
"MINCOUNTJUNCTIONS":
self.rMincount.get(),
"MINCOUNTGENEJUNCTIONS":
self.rMincount.get(),
"STARDIR":
SD + self.rReadlen.get().split(" ")[3],
"PICARDSTRAND": [
"NONE", "FIRST_READ_TRANSCRIPTION_STRAND",
"SECOND_READ_TRANSCRIPTION_STRAND"
][int(self.rStrand.get().split(",")[0])]
}
}
J = json.dumps(PD, sort_keys=True, indent=4, ensure_ascii=True)
gi.jsonconf.delete("1.0", END)
gi.jsonconf.insert(INSERT, J)
self.saveproject(gi.jsonconf.get("1.0", END))
