def latex_bowtie(input, output, param):
json_dict = json_load(input["json"])
basic_map_table = []
for sam in json_dict["stat"]:
basic_map_table.append(
[
underline_to_space(sam),
json_dict["stat"][sam]["total_reads"],
json_dict["stat"][sam]["mappable_reads"],
json_dict["stat"][sam]["mappable_rate"],
]
)
latex = JinjaTemplateCommand(
name="mapping quality",
template=input["template"],
param={
"section_name": "bowtie",
"basic_map_table": basic_map_table,
"mappable_ratio_graph": json_dict["output"]["pdf"],
"render_dump": output["latex"],
},
)
template_dump(latex)
def latex_venn(input, output, param):
json_dict = json_load(input["json"])
latex = JinjaTemplateCommand(
name = "venn diagram latex",
template = input["template"],
param = {"section_name": "venn",
"venn_graph": json_dict["input"]["venn"],
"render_dump": output["latex"]})
template_dump(latex)
def latex_cor(input, output, param):
json_dict = json_load(input["json"])
latex = JinjaTemplateCommand(
name = "correlation",
template = input["template"],
param = {"section_name": "correlation",
"correlation_graph": json_dict["input"]["cor_pdf"],
"render_dump": output["latex"]})
template_dump(latex)
def latex_macs2_on_sample(input, output, param):
json_dict = json_load(input["json"])
latex = JinjaTemplateCommand(
name="redunRateQC",
template=input["template"],
param = {"section_name": "redundant",
"redundant_ratio_graph": json_dict["output"]["pdf"],
"render_dump": output["latex"]})
template_dump(latex)
def latex_ceas(input, output, param):
json_dict = json_load(input["json"])
ceas_latex = JinjaTemplateCommand(
name = "ceas redraw",
template = input["template"],
param = {"gene_distribution_graph": json_dict["output"]["metagene_dist_pdf"],
"section_name": "ceas",
"meta_gene_graph": json_dict["output"]["peakheight_and_pie_pdf"],
"render_dump" : output["latex"]})
template_dump(ceas_latex)
def latex_seqpos(input, output, param):
json_dict = json_load(input["json"])
latex = JinjaTemplateCommand(
name = "motif finding",
template = input["template"],
param = {"motif_table": json_dict["stat"]["satisfied_motifs"],
"section_name": "motif",
"render_dump": output["latex"]})
template_dump(latex)
def latex_contamination(input, output, param):
json_dict = json_load(input["json"])
library_quality_latex = JinjaTemplateCommand(
name="library contamination",
template=input["template"],
param={"section_name": "library_contamination",
"library_contamination": json_dict["stat"],
'prefix_dataset_id': json_dict["param"]['id'],
"render_dump": output["latex"]
})
template_dump(library_quality_latex)
def latex_fastqc(input, output, param):
json_dict = json_load(input["json"])
fastqc_summary = []
stat = json_dict["stat"]
for sample in stat:
fastqc_summary.append([underline_to_space(sample), stat[sample]["sequence_length"], stat[sample]["median"]])
latex = JinjaTemplateCommand(
template=input["template"],
param={"section_name": "sequence_quality",
"path": json_dict["output"]["pdf"],
"fastqc_table": fastqc_summary,
"fastqc_graph": json_dict["output"]["pdf"],
'prefix_dataset_id': [ underline_to_space(i) for i in stat.keys() ],
"render_dump": output["latex"]})
template_dump(latex)
def latex_macs2(input, output, param):
# TODO: qian work out the peaks_summary_result part
json_dict = json_load(input["json"])
summary = [underline_to_space(json_dict["param"]["id"]),
json_dict["stat"]["qvalue"],
json_dict["stat"]["totalpeak"],
json_dict["stat"]["peaksge10"],
json_dict["stat"]["shiftsize"]]
high_confident_latex = JinjaTemplateCommand(
name = "high confident latex",
template = input["template"],
param = {"section_name": "high_confident_peaks",
"peak_summary_table": summary,
"high_confident_peak_graph": json_dict["output"]["pdf"],
"render_dump": output["latex"]})
template_dump(high_confident_latex)
def _s(json_path):
return json_load(json_path)["stat"]
def _items(json_path):
return json_load(json_path)["stat"].items()