def load_sequences_from_uniprot(proteins, clean_seqid=None, cache_basename=None):
if clean_seqid:
change_seqids_in_proteins(proteins, clean_seqid)
seqids = []
for seqid in proteins:
seqids.append(seqid)
if 'other_seqids' in proteins[seqid]['attr']:
seqids.extend(proteins[seqid]['attr']['other_seqids'])
uniprot_data = uniprot.get_metadata_with_some_seqid_conversions(seqids, cache_basename)
load_fastas_into_proteins(proteins, uniprot_data)
if cache_basename:
uniprot.write_fasta(cache_basename+'.fasta', uniprot_data, uniprot_data.keys())
filename = '/data/cycd_targets/cycd_target_uniprot.txt'
targetIDs = pd.read_csv(filename)
already_seen = pd.concat((targetIDs['Entry'], entries))
# Load hit list from PSSM
filename = '/data/cycd_targets/hsap_proteome/hsap_hits>20.csv'
targetIDs = pd.read_csv(filename, sep='\t')
entries = targetIDs['Entry']
# Do a merge to see what's not already seen in the hand-curated list
merged = set(entries) - set(already_seen)
# Fetch and write as FASTA
out_name = '/data/cycd_targets/hsap_hits>20.fasta'
upData = uniprot.batch_uniprot_metadata(merged, 'cache')
uniprot.write_fasta(out_name, upData, merged)
split_fastas(out_name)
PSIPRED_DIR = '/data/cycd_targets/cycd_target_uniprot_individuals'
seqs = []
for filename in os.listdir(PSIPRED_DIR):
if filename.endswith('.ss2'):
print 'Working on ', filename
#Load PSIPRED VFORMAT in a sane way to extract only relevant info
df = pd.read_csv(os.path.join(PSIPRED_DIR, filename),
header=0,
delim_whitespace=True,
skiprows=0,
mapping = uniprot.sequentially_convert_to_uniprot_id(seqids, "cache.json")
uniprot_seqids = mapping.values()
# Example 4 - get UniProt metadata
uniprot_data = uniprot.batch_uniprot_metadata(uniprot_seqids, "cache2.txt")
pprint.pprint(uniprot_data, indent=2)
for l in open("cache2.txt"):
print l.strip()
uniprot.write_fasta("example.output.fasta", uniprot_data, uniprot_seqids)
# Example 5 - chaining commands to make your own
# special mapper
def map_to_refseq(seqids):
uniprot_mapping = uniprot.sequentially_convert_to_uniprot_id(seqids, "func.cache.json")
uniprot_ids = uniprot_mapping.values()
pairs = uniprot.batch_uniprot_id_mapping_pairs("ACC", "P_REFSEQ_AC", uniprot_ids)
mapping = {}
for seqid in seqids:
if seqid in uniprot_mapping:
uniprot_id = uniprot_mapping[seqid]
for pair in pairs:
seqids, 'cache.json')
uniprot_seqids = mapping.values()
# Example 4 - get UniProt metadata
uniprot_data = uniprot.batch_uniprot_metadata(
uniprot_seqids, 'cache2.txt')
pprint.pprint(uniprot_data, indent=2)
for l in open('cache2.txt'):
print l.strip()
uniprot.write_fasta('example.output.fasta', uniprot_data, uniprot_seqids)
# Example 5 - chaining commands to make your own
# special mapper
def map_to_refseq(seqids):
uniprot_mapping = uniprot.sequentially_convert_to_uniprot_id(
seqids, 'func.cache.json')
uniprot_ids = uniprot_mapping.values()
pairs = uniprot.batch_uniprot_id_mapping_pairs(
'ACC', 'P_REFSEQ_AC', uniprot_ids)
mapping = {}
for seqid in seqids:
if seqid in uniprot_mapping:
