I would like to get a script written in biopython that creates a list of genome accession numbers for the genus Pseudomonas. But I don't know enough about biopython to achieve this. The goal is to use this list in genome to genome distance calculator 3.
Somebody gave me this script but it is not accession numbers, it's the list of ids of the records returned, for example the PMID in the case of PubMed :
from Bio import Entrez from Bio import SeqIO # Set the email address to use for the NCBI Entrez search
Entrez.email = "[email protected]" # Set the search term and search parameters
search_term = "pseudomonas[Organism]"
search_params = {
"db": "genome",
"term": search_term,
"retmax": 1000 # retrieve up to 1000 genomes
} # Search the NCBI Genome database using the Entrez API
handle = Entrez.esearch(**search_params)
record = Entrez.read(handle) # Extract the list of accession numbers from the search results
accession_numbers = record["IdList"] # Print the list of accession numbers
print(accession_numbers)
To get the genome accession numbers from the script you provided, you can modify the search parameters to retrieve the accession numbers rather than the record ids. You can do this by changing the "rettype" parameter to "acc" like this:
search_params = { "db": "genome", "term": search_term, "rettype": "acc", # retrieve the accession numbers "retmax": 1000 # retrieve up to 1000 genomes }
This will retrieve the genome accession numbers rather than the record ids. You can then use this list of accession numbers in genome to genome distance calculator 3 as needed.
I'm sorry, but the return is not accession numbers, even with "rettype": "acc"
['121403', '121354', '120434', '120433', '120362', '120361', '120326', '120325', '119252', '118524', '118280', '116938', '116043', '115451', '114351', '114276', '114020', '113998', '113188', '113187', '113186', '113185', '113184', '113183', '113182', '113181', '113180', '112459', '112429', '111779', '111141', '110120', '110118', '109874', '109631', '109029', '109028', '109027', '109026', '109025', '109024', '109023', '109022', '109020', '108987', '108983', '108645', '108644', '108465', '108464', '108226', '108128', '107484', '107446', '107215', '107151', '106448', '106414', '105682', '105681', '105680', '105670', '105669', '105668', '105667', '105666', '105665', '105664', '105663', '105662', '105661', '105660', '105659', '105658', '105657', '105656', '105655', '105654', '105653', '105652', '105651', '105650', '105649', '105648', '105647', '105646', '105645', '105644', '105643', '105642', '105641', '105640', '105639', '105638', '105637', '105636', '105635', '105634', '105633', '105632', '104758', '104707', '104243', '103347', '101611', '101610', '101563', '101514', '101489', '101342', '100510', '100507', '100489', '100055', '100047', '100020', '100019', '99496', '99150', '99113', '99109', '99108', '99097', '99096', '99095', '99052', '98986', '98928', '98611', '98260', '98012', '97753', '97612', '97509', '97138', '97125', '97021', '96897', '96796', '96574', '95487', '95335', '94995', '94971', '94319', '93550', '93513', '92947', '92938', '92588', '91835', '91764', '89519', '89474', '87926', '87860', '87847', '87758', '87704', '87647', '87389', '87231', '86953', '86864', '86424', '86397', '85390', '85358', '85343', '85247', '84650', '84528', '83430', '83429', '83336', '82601', '81802', '79564', '79495', '78220', '78219', '77868', '76465', '75391', '73439', '72455', '71336', '71325', '70100', '69261', '68873', '68841', '67996', '66928', '66184', '65408', '64273', '62407', '55925', '55527', '55064', '54890', '54641', '54639', '54168', '52690', '51842', '50900', '50801', '50719', '50525', '50119', '50091', '50089', '49931', '49926', '49912', '49867', '49795', '49686', '49685', '49666', '49658', '49657', '49656', '49651', '49650', '49635', '49625', '49624', '49619', '49618', '49615', '49612', '49605', '49601', '49596', '49594', '49544', '49526', '49524', '49523', '49501', '49500', '49484', '49446', '49425', '49416', '49413', '49404', '49364', '49351', '49350', '46130', '45794', '45364', '44987', '44845', '44404', '44402', '43682', '42108', '42107', '41274', '40838', '40798', '40797', '40796', '40795', '40794', '40214', '39923', '38922', '38683', '38682', '38681', '37003', '36890', '36383', '36141', '35811', '35787', '35408', '35399', '34517', '34088', '34049', '33265', '32054', '31838', '31753', '31370', '30999', '30960', '30584', '22829', '17302', '16644', '16643', '16535', '16517', '16376', '16340', '15920', '15312', '15308', '15290', '14593', '14592', '14591', '14590', '14589', '14588', '14587', '14586', '14585', '14584', '14583', '14582', '14581', '14580', '14577', '14524', '14405', '14136', '14023', '13508', '13402', '13257', '12999', '12979', '12943', '12568', '12409', '12176', '12097', '12066', '11916', '11559', '11288', '11209', '11206', '11127', '3640', '2943', '2506', '2258', '2255', '2253', '1458', '1431', '187', '185', '174', '150']
Mohamad Dzul Syakimin Mohd Noor, I think that your text is generated by ChatGPT, and the answer is not correct. For everyone, I would like to thank you for not using an AI to generate your answers. If you do it anyway, check at least that your response is relevant.
from Bio import Entrez
Entrez.email = "[email protected]" # provide your email address
term = "Pseudomonas[Organism] AND genome[Title]" # define your search term
handle = Entrez.esearch(db="nucleotide", term=term, retmax=1000) # perform the search with retmax=1000
record = Entrez.read(handle) # parse the results
ids = record["IdList"] # get the list of ids
for id in ids: # loop over the ids
summary_handle = Entrez.esummary(db="nucleotide", id=id) # get the summary for each id
summary = Entrez.read(summary_handle) # parse the summary
accession = summary[0]["AccessionVersion"] # get the accession number from the summary
print(accession) # print the accession number
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