Sequence Cleaner
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if sequence not in sequences: | if sequence not in sequences: | ||
sequences[sequence]=seq_record.id | sequences[sequence]=seq_record.id | ||
| − | # | + | #If It is in the hash table , We just gonna take its ID and concatenate with the Id of other sequence that was exaclty the same. |
else: | else: | ||
sequences[sequence]+="_"+seq_record.id | sequences[sequence]+="_"+seq_record.id | ||
Revision as of 18:34, 9 July 2011
Description
I want to share my script using biopython to clean sequences up , you should know analyzing poor data takes CPU time and interpreting the results from poor data takes people time, so it's always important to make a preprocessing.
Let me call my script as “Sequence_cleaner” and the big idea is to remove duplicate sequences, remove too short sequences ( the user defines the minimum length) and remove sequences which have too many unknown nucleotides (N) ( the user defines the % of N is allows ) and in the end the user can choose if he/she wants to have a file as output or print the result.
Script
from Bio import SeqIO def sequence_cleaner(fasta_file,min_length=0,por_n=100): #create our hash table to add the sequences sequences={} #Using the biopython fasta parse we can read our fasta input for seq_record in SeqIO.parse(fasta_file, "fasta"): #Take the current sequence sequence=str(seq_record.seq).upper() #Check if the current sequence is according to the user parameters if (len(sequence)>=min_length and (float(sequence.count("N"))/float(len(sequence)))*100<=por_n): # If the sequence passed in the test "is It clean?" and It isnt in the hash table , the sequence and Its id are going to be in the hash if sequence not in sequences: sequences[sequence]=seq_record.id #If It is in the hash table , We just gonna take its ID and concatenate with the Id of other sequence that was exaclty the same. else: sequences[sequence]+="_"+seq_record.id #Write the clean sequences #Create a file in the same directory where you ran this script output_file=open("clear_"+fasta_file,"w+") #Just Read the Hash Table and write on the file as a fasta format for sequence in sequences: output_file.write(">"+sequences[sequence]+"\n"+sequence+"\n") output_file.close() #sequence_cleaner("Aip_coral.fasta",10,10) "You should call the function 'sequence_cleaner', there are 3 basics parameters: " #1st: your fasta file " #2nd: the user define the minimum length (default value 0 ( means you dont care to minimum length) " #3rd: the user define the % of N is allows (default value 100 ( means you dont care to 'N' in your sequences)) "FYI If You dont care to the 2nd and the 3rd parameters you just gonna remove the duplicate sequences "