comparison read2mut.py @ 22:24c50e7539ef draft

planemo upload for repository https://github.com/Single-Molecule-Genetics/VariantAnalyzerGalaxy/tree/master/tools/variant_analyzer commit ee4a8e6cf290e6c8a4d55f9cd2839d60ab3b11c8

21:b67d4c7da780

            alt = mut_array[i, 3]
            dcs_median = cvrg_dict[key1][2]
            whole_array = list(pure_tags_dict_short[key1].keys())

            tier_dict[key1] = {}
            values_tier_dict = [("tier 1.1", 0), ("tier 1.2", 0), ("tier 2.1", 0), ("tier 2.2", 0), ("tier 2.3", 0), ("tier 2.4", 0), ("tier 3.1", 0), ("tier 3.2", 0), ("tier 4.1", 0), ("tier 4.2", 0), ("tier 5", 0), ("tier 6", 0)]
            for k, v in values_tier_dict:
                tier_dict[key1][k] = v

            used_keys = []
            if 'ab' in mut_pos_dict[key1].keys():

                                beg1 = total1new
                                total1new = 0
                                alt1ff = 0
                                alt1f = 0
                                trimmed_five = True
                            if ((read_pos1 >= 0) and (abs(read_len_median1 - read_pos1) <= trim3)):
                                beg1 = total1new
                                total1new = 0
                                alt1ff = 0
                                alt1f = 0

            lst = tuple(lst)
            ws2.write_row(row + 1, 0, lst)
            if chimera_correction:
                ws2.conditional_format('P{}:Q{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$P$1="tier 1.1"', 'format': format1, 'multi_range': 'P{}:Q{} P1:Q1'.format(row + 2, row + 2)})
                ws2.conditional_format('R{}:U{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$R$1="tier 2.1"', 'format': format3, 'multi_range': 'R{}:U{} R1:U1'.format(row + 2, row + 2)})
                ws2.conditional_format('V{}:AA{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$V$1="tier 3.1"', 'format': format2, 'multi_range': 'V{}:AA{} V1:AA1'.format(row + 2, row + 2)})
            else:
                ws2.conditional_format('J{}:K{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$J$1="tier 1.1"', 'format': format1, 'multi_range': 'J{}:K{} J1:K1'.format(row + 2, row + 2)})
                ws2.conditional_format('L{}:O{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$L$1="tier 2.1"', 'format': format3, 'multi_range': 'L{}:O{} L1:O1'.format(row + 2, row + 2)})
                ws2.conditional_format('P{}:U{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$P$1="tier 3.1"', 'format': format2, 'multi_range': 'P{}:U{} P1:U1'.format(row + 2, row + 2)})
            row += 1

22:24c50e7539ef

            alt = mut_array[i, 3]
            dcs_median = cvrg_dict[key1][2]
            whole_array = list(pure_tags_dict_short[key1].keys())

            tier_dict[key1] = {}
            values_tier_dict = [("tier 1.1", 0), ("tier 1.2", 0), ("tier 2.1", 0), ("tier 2.2", 0), ("tier 2.3", 0), ("tier 2.4", 0), 
                                ("tier 3.1", 0), ("tier 3.2", 0), ("tier 4.1", 0), ("tier 4.2", 0), ("tier 5", 0), ("tier 6", 0)]
            for k, v in values_tier_dict:
                tier_dict[key1][k] = v

            used_keys = []
            if 'ab' in mut_pos_dict[key1].keys():

                                beg1 = total1new
                                total1new = 0
                                alt1ff = 0
                                alt1f = 0
                                trimmed_five = True

                            if ((read_pos1 >= 0) and (abs(read_len_median1 - read_pos1) <= trim3)):
                                beg1 = total1new
                                total1new = 0
                                alt1ff = 0
                                alt1f = 0

            lst = tuple(lst)
            ws2.write_row(row + 1, 0, lst)
            if chimera_correction:
                ws2.conditional_format('P{}:Q{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$P$1="tier 1.1"', 'format': format1, 'multi_range': 'P{}:Q{} P1:Q1'.format(row + 2, row + 2)})
                ws2.conditional_format('R{}:U{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$R$1="tier 2.1"', 'format': format3, 'multi_range': 'R{}:U{} R1:U1'.format(row + 2, row + 2)})
                ws2.conditional_format('V{}:Z{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$V$1="tier 3.1"', 'format': format2, 'multi_range': 'V{}:Z{} V1:Z1'.format(row + 2, row + 2)})
            else:
                ws2.conditional_format('J{}:K{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$J$1="tier 1.1"', 'format': format1, 'multi_range': 'J{}:K{} J1:K1'.format(row + 2, row + 2)})
                ws2.conditional_format('L{}:O{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$L$1="tier 2.1"', 'format': format3, 'multi_range': 'L{}:O{} L1:O1'.format(row + 2, row + 2)})
                ws2.conditional_format('P{}:U{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$P$1="tier 3.1"', 'format': format2, 'multi_range': 'P{}:U{} P1:U1'.format(row + 2, row + 2)})
            row += 1