comparison peptide_pi_annotator.py @ 3:78afc81ab244 draft default tip

planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tools/pi_db_tools commit decb06dc90d7069d317968b979f649a04720b264

2:77ddaee887a8

                                         args.ignoremods):
            fp.write('\t'.join([str(x) for x in outline]))
            fp.write('\n')


def get_first_matching_pattern(patterns, string):
    for pattern in patterns:
        if re.search(pattern, string):
            return pattern
    return False


def get_col_by_pattern(peptable, colpattern):
    with open(peptable) as fp:

    with open(peptable) as fp:
        header = next(fp).strip('\n').split('\t')
        yield header + ['Experimental pI', 'Predicted pI', 'Delta pI']
        for line in fp:
            line = line.strip('\n').split('\t')
            strip = strips[get_first_matching_pattern(strips.keys(),
                                                      line[stripcol])]
            exp_pi = (strip['fr_width'] * int(line[frac_col]) +
                      strip['intercept'])

            sequence = line[seqcol]
            for weight in ignoremods:
                if weight == '*':
                    regex = '[+-]\d*\.\d*'
                else:

            except KeyError:
                print('CANNOT PREDICT', sequence)
                not_predicted_count += 1
                pred_pi, delta_pi = 'NA', 'NA'
            else:
                delta_pi = exp_pi - pred_pi
                predicted_count += 1
            yield line + [exp_pi, pred_pi, delta_pi]
    print('Number of peptides without pI prediction: {}\n'
          'Number of peptides with predicion: {}\n'.format(not_predicted_count,
                                                           predicted_count))


def parse_commandline():
    parser = argparse.ArgumentParser(
        formatter_class=argparse.RawTextHelpFormatter)

3:78afc81ab244

                                         args.ignoremods):
            fp.write('\t'.join([str(x) for x in outline]))
            fp.write('\n')


def get_strip(strips, string):
    for pattern in strips.keys():
        if re.search(pattern, string):
            return strips[pattern]
    return False


def get_col_by_pattern(peptable, colpattern):
    with open(peptable) as fp:

    with open(peptable) as fp:
        header = next(fp).strip('\n').split('\t')
        yield header + ['Experimental pI', 'Predicted pI', 'Delta pI']
        for line in fp:
            line = line.strip('\n').split('\t')
            sequence = line[seqcol]
            for weight in ignoremods:
                if weight == '*':
                    regex = '[+-]\d*\.\d*'
                else:

            except KeyError:
                print('CANNOT PREDICT', sequence)
                not_predicted_count += 1
                pred_pi, delta_pi = 'NA', 'NA'
            else:
                predicted_count += 1
            strip = get_strip(strips, line[stripcol])
            if not strip:
                exp_pi, delta_pi = 'NA', 'NA'
            else:
                try:
                    exp_pi = (strip['fr_width'] * int(line[frac_col]) +
                              strip['intercept'])
                except ValueError:
                    print('Cannot detect fraction for PSM {}'.format(sequence))
                    exp_pi, delta_pi = 'NA', 'NA'
                else:
                    if pred_pi != 'NA':
                        delta_pi = exp_pi - pred_pi
                    else:
                        delta_pi = 'NA'
            yield line + [exp_pi, pred_pi, delta_pi]
    print('Number of peptides without pI prediction: {}\n'
          'Number of peptides predicted: {}\n'.format(not_predicted_count,
                                                      predicted_count))


def parse_commandline():
    parser = argparse.ArgumentParser(
        formatter_class=argparse.RawTextHelpFormatter)