MS2PIP Server API
MS2PIP Server can be accessed through the webpage or through a RESTful API. While this page provides an example Python script for contacting the API, the Swagger-generated documentation can be found here: https://iomics.ugent.be/ms2pip/api/v2.
The following Python function contacts the MS2PIP Server RESTful API:
def run_ms2pip_server(peptides, frag_method, ptm_list, url='https://iomics.ugent.be/ms2pip/api/v2'):
# Check if all columns are present in dataframe
for col in ['spec_id', 'peptide', 'charge', 'modifications']:
if col not in peptides.columns:
print("{} is missing from peptides DataFrame".format(col))
return None
# Split-up into batches of 100 000 peptides (maximum MS2PIP Server accepts per request)
batch_size = 100000
result = pd.DataFrame()
for i in list(range(0, len(peptides), batch_size)):
print("Working on batch {}/{}".format(int(i / batch_size + 1), len(peptides) // batch_size + 1))
peptides_batch = peptides.iloc[i:i+batch_size, :]
# Combine data into dictionary for json post request
input_data = {
"params": {
"frag_method": frag_method,
"ptm": ptm_list
},
"peptides": peptides_batch.to_dict(orient='list')
}
# Post data to server and get task id
response = requests.post('{}/task'.format(url), json=input_data)
if 'task_id' not in response.json():
if 'error' in response.json():
print("Server error: {}".format(response.json()['error']))
else:
print("Something went wrong")
return None
task_id = response.json()['task_id']
print("Received task id: {}".format(task_id))
# Check server task status and get result when ready
sleep(1)
response = requests.get('{}/task/{}/status'.format(url, task_id))
state = response.json()['state']
if state != 'SUCCESS':
print("Check MS2PIP Server status every 5 seconds", end='')
state = 'PENDING'
pending_count = 0
while state == 'PENDING' or state == 'PROGRESS':
sleep(5)
print('.', end='')
response = requests.get('{}/task/{}/status'.format(url, task_id))
state = response.json()['state']
# Do not keep looping if task state is stuck on PENDING, it might have failed silently
if state == 'PENDING':
pending_count += 1
if pending_count > 24:
print("\nSomething went wrong")
return None
print('')
if state == 'SUCCESS':
response = requests.get('{}/task/{}/result'.format(url, task_id))
result_batch = pd.DataFrame.from_dict(response.json())['ms2pip_out']
result_batch = result_batch[['spec_id', 'charge', 'ion', 'ionnumber', 'mz', 'prediction']]
result = result.append(result_batch)
print("Result received", end='\n\n')
else:
error_message = response.json()['status']
print("Something went wrong: {}".format(error_message))
return None
print("Finished with all batches!")
return result
The function takes three arguments: peptides, frag_method and ptm_list. peptides is an MS2PIP PEPREC-formatted Pandas DataFrame. ptm_list is a list of MS2PIP formatted PTM definitions. A detailed explanation of both data structures can be found on the MS2PIP Server webpage. frag_method is the specific model with which you want to predict peak intensities (e.g. HCD, CID, iTRAQ…) Checkout README.md for a list of all available models.
The function also takes an argument url, in which you can provide a custom URL to the server. By default this is https://iomics.ugent.be/ms2pip/api.
An example for running the function:
# Define arguments
frag_method = 'HCD'
ptm_list = [
'Oxidation,15.994915,M',
'Carbamidomethyl,57.021464,C',
'PhosphoS,79.966331,S',
'PhosphoT,79.966331,T',
'PhosphoY,79.966331,Y',
'Glu->pyro-Glu,-18.010565,E',
'Gln->pyro-Glu,-17.026549,Q',
'Pyro-carbamidomethyl,39.994915,C',
'Deamidated,0.984016,N',
'iTRAQ,144.102063,N-term'
]
peptides = pd.DataFrame(data={
'spec_id': ['peptide1', 'peptide2'],
'peptide': ['STCINTFWLIVK', 'GRLNTFILK'],
'modifications': ['3|Carbamidomethyl', '-'],
'charge': [2, 3]
})
# Run function
result = run_ms2pip_server(peptides, frag_method, ptm_list)