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Add support for lower/mixed case FASTA #3

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Add support for lower/mixed case FASTA #3

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3 changes: 2 additions & 1 deletion deepsp_predictor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -165,6 +165,7 @@ def load_input_data(filename):

# One Hot Encoding of Aligned Sequence
def one_hot_encoder(s):
s = s.upper()
d = {'A': 0, 'C': 1, 'D': 2, 'E': 3, 'F': 4, 'G': 5, 'H': 6, 'I': 7, 'K': 8, 'L': 9, 'M': 10, 'N': 11, 'P': 12, 'Q': 13, 'R': 14, 'S': 15, 'T': 16, 'V': 17, 'W': 18, 'Y': 19, '-': 20}

x = np.zeros((len(d), len(s)))
Expand Down Expand Up @@ -212,4 +213,4 @@ def one_hot_encoder(s):
'SCM_neg_CDRH1','SCM_neg_CDRH2','SCM_neg_CDRH3','SCM_neg_CDRL1','SCM_neg_CDRL2','SCM_neg_CDRL3','SCM_neg_CDR','SCM_neg_Hv','SCM_neg_Lv','SCM_neg_Fv',
'SCM_pos_CDRH1','SCM_pos_CDRH2','SCM_pos_CDRH3','SCM_pos_CDRL1','SCM_pos_CDRL2','SCM_pos_CDRL3','SCM_pos_CDR','SCM_pos_Hv','SCM_pos_Lv','SCM_pos_Fv']
df = pd.concat([pd.DataFrame(name_list), pd.DataFrame(sap_pos), pd.DataFrame(scm_neg), pd.DataFrame(scm_pos)], ignore_index=True, axis=1,); df.columns = features
df.to_csv('DeepSP_descriptors.csv', index=False)
df.to_csv('DeepSP_descriptors.csv', index=False)