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()