def generate_report(config_file, proj_conf, single_end, stranded):
d = {
"project_id": proj_conf["id"],
"samplenames": " ".join(proj_conf["samples"]),
"latex_opt": "",
"uppnex": "",
"mapping": "",
"dup_rem": "",
"read_count": "",
"quantifyer": "",
"gene_body_cov": "",
"FPKM_heatmap": "",
"Mapping_statistics": "",
"Read_Distribution": "",
"rRNA_table": "",
"GBC": "",
"strandness_table": "",
"complexity_plot": "",
"species": "",
"genombuild": "",
"rseqc_version": "",
"Preseq": "",
"date": date.today(),
"anotation_version": "",
}
## Latex option (no of floats per page)
floats_per_page = ".. raw:: latex\n\n \setcounter{totalnumber}{8}"
d["latex_opt"] = floats_per_page
## Project information fetched from StatusDB
couch = load_couch_server(config_file)
proj_db = couch["projects"]
key = find_proj_from_view(proj_db, proj_conf["id"])
info = proj_db[key]
try:
uppnex_proj = info["uppnex_id"]
reference_genome = info["reference_genome"]
if reference_genome == "hg19":
d["species"] = "Human"
elif reference_genome == "mm9":
d["species"] = "Mouse"
elif reference_genome == "rn4":
d["species"] = "Rat"
elif reference_genome == ("Zv9" or "Zv8"):
d["species"] = "Zebrafish"
elif reference_genome == "sacCer2":
d["species"] = "Saccharomyces cerevisiae"
elif reference_genome == "dm3":
d["species"] = "Drosophila melanogaster"
else:
d["species"] = reference_genome
except:
uppnex_proj = ""
print "No uppnex ID fetched"
pass
d["uppnex"] = uppnex_proj
## RNA-seq tools fetched from config file post_process.yaml
try:
tools = proj_conf["config"]["custom_algorithms"]["RNA-seq analysis"]
d["mapping"] = os.path.join(tools["aligner"], tools["aligner_version"])
d["dup_rem"] = os.path.join(tools["dup_remover"], tools["dup_remover_version"])
d["read_count"] = os.path.join(tools["counts"], tools["counts_version"])
d["quantifyer"] = os.path.join(tools["quantifyer"], tools["quantifyer_version"])
d["genombuild"] = tools[reference_genome]["name"]
d["rseqc_version"] = tools["rseqc_version"]
d["Preseq"] = tools["preseq"]
d["anotation_version"] = tools[reference_genome]["annotation_release"]
except:
print "Could not fetched RNA-seq tools from config file post_process.yaml"
pass
## Mapping Statistics
tab = Texttable()
tab.set_cols_dtype(["t", "t", "t", "t"])
tab.header(["Sample", "Tot NO Reads", "UniqMapped", "UniqMapped DuplRem"])
statistics = {}
try:
for sample_name in proj_conf["samples"]:
try:
f = open("tophat_out_" + sample_name + "/logs/prep_reads.log", "r")
tot_NO_read_pairs = f.readlines()[2].split()[3]
f.close()
f = open("tophat_out_" + sample_name + "/stat" + sample_name, "r")
dict = make_stat(f, tot_NO_read_pairs, single_end)
tab.add_row(
[
sample_name,
tot_NO_read_pairs,
str(dict["bef_dup_rem"]["%uniq_mapped"]) + "%",
str(dict["aft_dup_rem"]["%uniq_mapped"]) + "%",
]
)
statistics[sample_name] = dict
except:
print "Could not make mapping statistics for sample " + sample_name
d["Mapping_statistics"] = indent_texttable_for_rst(tab)
stat_json = open("stat.json", "w")
print >> stat_json, statistics
stat_json.close()
except:
print "Could not make Mapping Statistics table"
pass
## Read Distribution
try:
tab = Texttable()
tab.set_cols_dtype(["t", "t", "t", "t", "t", "t", "t", "t"])
tab.header(["Sample", "CDS", "5'UTR", "3'UTR", "Intron", "TSS", "TES", "mRNA"])
read_dist = {}
for i in range(len(proj_conf["samples"])):
sample_name = proj_conf["samples"][i]
dict = {}
try:
f = open("RSeQC_rd_" + sample_name + ".out", "r")
dict = read_RSeQC_rd233(f)
row = [
sample_name,
dict["CDS_Exons"]["Tags/Kb"],
dict["5'UTR_Exons"]["Tags/Kb"],
dict["3'UTR_Exons"]["Tags/Kb"],
dict["Introns"]["Tags/Kb"],
dict["TSS_up_1kb"]["Tags/Kb"],
dict["TES_down_1kb"]["Tags/Kb"],
dict["mRNA_frac"],
]
tab.add_row(row)
read_dist[sample_name] = dict
except:
print "Could not make read distribution for sample " + sample_name
pass
RSeQC_rd_json = open("RSeQC_rd.json", "w")
print >> RSeQC_rd_json, read_dist
RSeQC_rd_json.close()
d["Read_Distribution"] = indent_texttable_for_rst(tab)
except:
print "Could not make Read Distribution table"
pass
## Gene Body Coverage
try:
figure()
x = range(0, 101)
for i in range(len(proj_conf["samples"])):
y = zeros(101)
sample_name = proj_conf["samples"][i]
f = open(sample_name + ".geneBodyCoverage.txt", "r")
for line in f.readlines():
try:
key = int(line.split()[0])
val = int(line.split()[1])
y[key] = val
except:
pass
plot(x, y) # ,label=proj_conf['samples'][i])
# legend(loc='upper left',fontsize='xx-small')
ylabel("read number")
xlabel("percentile of gene body (5'->3')")
savefig("gbc.pdf")
d["GBC"] = image("gbc.pdf", width="100%")
except:
print "could not make GBC plot"
## FPKM_heatmap
if os.path.exists("FPKM_heatmap.pdf"):
d["FPKM_heatmap"] = image("FPKM_heatmap.pdf", width="100%")
else:
print "could not make FPKM heatmap"
## complexity plot
if os.path.exists("complexity_curves.pdf"):
d["complexity_plot"] = image("complexity_curves.pdf", width="100%")
else:
complexity = False
print "could not make complexity plot"
## rRNA_table
try:
tab = Texttable()
tab.set_cols_dtype(["t", "t"])
tab.header(["Sample", "rRNA"])
f = open("rRNA.quantification", "r")
D = {}
for line in f:
D[str(line.split("\t")[0].strip())] = str(line.split("\t")[1].strip())
for sample_name in proj_conf["samples"]:
if D.has_key(sample_name):
tab.add_row([sample_name, D[sample_name]])
d["rRNA_table"] = indent_texttable_for_rst(tab)
f.close()
except:
print "could not generate rRNA table"
pass
## strandness_table
try:
tab = Texttable()
tab.set_cols_dtype(["t", "t"])
tab.header(["Sample", "strand-specific reads"])
try:
f = open("infer_experiment.json", "rb")
data = json.load(f)
except:
print "can't open infer_experiment.json\n"
D = data
for sample_name in proj_conf["samples"]:
if D.has_key(sample_name):
tab.add_row([sample_name, str(float(D[sample_name]) * 100) + "%"])
d["strandness_table"] = indent_texttable_for_rst(tab)
f.close()
except:
print "could not generate strandness_table"
pass
return d
def generate_report(config_file,proj_conf,single_end,stranded,genome):
d = {
'project_id': proj_conf['id'],
'samplenames': ' '.join(proj_conf['samples']),
'latex_opt' : "",
'uppnex': "",
'mapping':"",
'dup_rem':"",
'read_count':"",
'quantifyer':"",
'gene_body_cov':"",
'FPKM_heatmap':"",
'Mapping_statistics': "",
'Read_Distribution':"",
'rRNA_table':"",
'GBC':"",
'strandness_table':"",
'complexity_plot': "",
'species':"",
'genombuild':"",
'rseqc_version':'',
'Preseq':'',
'date':date.today(),
'anotation_version':''
}
## Latex option (no of floats per page)
floats_per_page = '.. raw:: latex\n\n \setcounter{totalnumber}{8}'
d['latex_opt'] = floats_per_page
## Project information fetched from StatusDB
couch=load_couch_server(config_file)
proj_db = couch['projects']
key = find_proj_from_view(proj_db, proj_conf['id'])
info = proj_db[key]
species= {
'hg19': 'Human',
'mm9': 'Mouse',
'rn4': 'Rat',
'rn5': 'Rat',
'Zv8': 'Zebrafish',
'Zv9': 'Zebrafish',
'Zv10': 'Zebrafish',
'sacCer2': 'Saccharomyces cerevisiae',
'dm3': 'Drosophila melanogaster'
}
try:
uppnex_proj = info['uppnex_id']
reference_genome = genome if genome else info['reference_genome']
if reference_genome in species.keys():
d['species'] = species.get(reference_genome, reference_genome)
else:
d['species'] = reference_genome
except:
uppnex_proj = ""
print "No uppnex ID fetched"
pass
d['uppnex'] = uppnex_proj
## RNA-seq tools fetched from config file post_process.yaml
try:
tools = proj_conf['config']['custom_algorithms']['RNA-seq analysis']
d['mapping'] = os.path.join(tools['aligner'],tools['aligner_version'])
d['dup_rem'] = os.path.join(tools['dup_remover'],tools['dup_remover_version'])
d['read_count'] = os.path.join(tools['counts'],tools['counts_version'])
d['quantifyer'] = os.path.join(tools['quantifyer'],tools['quantifyer_version'])
d['genombuild'] = tools[reference_genome]['name']
d['rseqc_version'] = tools['rseqc_version']
d['Preseq'] = os.path.join(tools['Preseq'],tools['Preseq_version'])
d['anotation_version'] = tools[reference_genome]['annotation_release']
except:
print "Could not fetched RNA-seq tools from config file post_process.yaml"
pass
## Mapping Statistics
tab = Texttable()
tab.set_cols_dtype(['t','t','t','t'])
tab.header(['Sample','Tot NO Reads','UniqMapped','UniqMapped DuplRem'])
statistics={}
try:
for sample_name in proj_conf['samples']:
try:
f = open('tophat_out_'+sample_name+'/logs/prep_reads.log', 'r')
tot_NO_read_pairs = f.readlines()[2].split()[3]
f.close()
f = open('tophat_out_'+sample_name+'/stat'+sample_name, 'r')
dict = make_stat(f,tot_NO_read_pairs,single_end)
tab.add_row([sample_name,tot_NO_read_pairs,str(dict['bef_dup_rem']['%uniq_mapped'])+'%',str(dict['aft_dup_rem']['%uniq_mapped'])+'%'])
statistics[sample_name] = dict
except:
print 'Could not make mapping statistics for sample '+sample_name
d['Mapping_statistics'] = indent_texttable_for_rst(tab)
stat_json = open('stat.json','w')
print>> stat_json, statistics
stat_json.close()
except:
print "Could not make Mapping Statistics table"
pass
## Read Distribution
try:
tab = Texttable()
tab.set_cols_dtype(['t','t','t','t','t','t','t','t'])
tab.header(["Sample","CDS","5'UTR","3'UTR","Intron","TSS","TES","mRNA"])
read_dist = {}
for i in range(len(proj_conf['samples'])):
sample_name = proj_conf['samples'][i]
dict = {}
try:
f = open('RSeQC_rd_'+sample_name+'.out','r')
dict = read_RSeQC_rd233(f)
row = [sample_name,dict['CDS_Exons']['Tags/Kb'], dict["5'UTR_Exons"]['Tags/Kb'],
dict["3'UTR_Exons"]['Tags/Kb'],dict['Introns']['Tags/Kb'],
dict['TSS_up_1kb']['Tags/Kb'],dict['TES_down_1kb']['Tags/Kb'], dict['mRNA_frac']]
tab.add_row(row)
read_dist[sample_name] = dict
except:
print "Could not make read distribution for sample "+sample_name
pass
RSeQC_rd_json = open('RSeQC_rd.json','w')
print >> RSeQC_rd_json, read_dist
RSeQC_rd_json.close()
d['Read_Distribution'] = indent_texttable_for_rst(tab)
except:
print "Could not make Read Distribution table"
pass
## Gene Body Coverage
try:
pdf_fn="geneBodyCoverage.pdf"
values = [1] *101
fig = plt.figure()
axes = fig.add_subplot(111)
plt.subplots_adjust(right=0.7)
sample_num=len(proj_conf['samples'])
n=math.ceil(float(sample_num)/12)
col=math.ceil(float(sample_num)/40)
colours = ['#a6cee3','#1f78b4','#b2df8a','#33a02c','#fb9a99','#e31a1c',
'#fdbf6f','#ff7f00','#cab2d6','#6a3d9a','#ffff99','#b15928']*int(n)
i = 0
for s in range(0,sample_num):
sample_name = proj_conf['samples'][s]
coverage_file = sample_name + '.geneBodyCoverage.txt'
fn = os.path.realpath(coverage_file)
try:
lines=open(fn).readlines()
for l in range(1,101):
(percentile, count) = (lines[0].split()[l],lines[1].split()[l])
if percentile.isdigit() is False:
continue
values[int(percentile)] = float(count) / 1000000
#print values
except IOError as e:
print "Could not load input file: {}".format(fn)
axes.plot(values, label=sample_name, color=colours[i])
i += 1
# Tidy the axes
axes.tick_params(which='both', labelsize=8, direction='out', top=False, right=False)
# Make the x axis labels percentages
axes.set_xticklabels(["%d%%" % p for p in axes.get_xticks()])
# Labels
matplotlib.rcParams['mathtext.default'] = 'regular'
plt.xlabel(r"Gene body position ($5' \rightarrow 3'$)")
plt.ylabel(r'Cumulative Read Count ($\times 10^6$)')
plt.title('Gene Body Coverage')
#Legend
axes.legend(loc='upper left', bbox_to_anchor = (1.02, 1.02), fontsize=6, ncol=int(col))
plt.savefig(pdf_fn)
d['GBC'] = image(pdf_fn, width="100%")
plt.close(fig)
except:
print sys.exc_info()
print "could not make GBC plot"
## FPKM_heatmap
if os.path.exists("FPKM_heatmap.pdf"):
d['FPKM_heatmap'] = image("FPKM_heatmap.pdf", width="100%")
else:
print "could not make FPKM heatmap"
## complexity plot
if os.path.exists("complexity_curves.pdf"):
d['complexity_plot'] = image("complexity_curves.pdf", width="100%")
else:
complexity=False
print "could not make complexity plot"
## rRNA_table
try:
tab = Texttable()
tab.set_cols_dtype(['t','t'])
tab.header(["Sample","rRNA"])
f=open('rRNA.quantification','r')
D={}
for line in f:
D[str(line.split('\t')[0].strip())]=str(line.split('\t')[1].strip())
for sample_name in proj_conf['samples']:
if D.has_key(sample_name):
tab.add_row([sample_name,D[sample_name]])
d['rRNA_table']=indent_texttable_for_rst(tab)
f.close()
except:
print "could not generate rRNA table"
pass
## strandness_table
try:
tab = Texttable()
tab.set_cols_dtype(['t','t'])
tab.header(["Sample","strand-specific reads"])
try:
f=open('infer_experiment.json', 'rb')
data=json.load(f)
except:
print "can't open infer_experiment.json\n"
D=data
for sample_name in proj_conf['samples']:
if D.has_key(sample_name):
tab.add_row([sample_name,str(float(D[sample_name])*100)+'%'])
d['strandness_table']=indent_texttable_for_rst(tab)
f.close()
except:
print "could not generate strandness_table"
pass
return d
