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updating mut_seq script

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This commit is contained in:
Tanushree Tunstall 2020-02-25 18:13:18 +00:00
parent e9a95e9d3a
commit f9837b474c
1 changed files with 85 additions and 137 deletions
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mcsm_analysis/pyrazinamide/scripts/generate_mut_sequences.py Normal file → Executable file
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@ -21,110 +21,121 @@ from Bio import SeqIO
# output: MSA for mutant sequences # output: MSA for mutant sequences
# path: "Data/<drug>/input/processed/<filename>" # path: "Data/<drug>/input/processed/<filename>"
#*********************************************************************** #***********************************************************************
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% #%%
############# specify variables for input and output paths and filenames # specify input and output variables
homedir = os.path.expanduser('~') # spyder/python doesn't recognise tilde homedir = os.path.expanduser('~')
basedir = "/git/Data/pyrazinamide/input" #=======
# input # input
inpath = "/original" #=======
in_filename_fasta = "/3pl1.fasta.txt"
infile_fasta = homedir + basedir + inpath + in_filename_fasta
print("Input file is:", infile_fasta)
inpath_p = "/processed"
in_filename_meta_data = "/meta_data_with_AFandOR.csv"
infile_meta_data = homedir + basedir + inpath_p + in_filename_meta_data
print("Input file is:", infile_meta_data)
# output: only path specified, filenames in respective sections
outpath = "/processed"
################## end of variable assignment for input and output files
#==========
#read files
#==========
############# #############
# fasta file # fasta file
############# #############
#my_file = infile_fasta indir = 'git/Data/pyrazinamide/input/original'
in_filename_fasta = "3pl1.fasta.txt"
my_fasta = str() infile_fasta = homedir + '/' + indir + '/' + in_filename_fasta
for seq_record in SeqIO.parse(infile_fasta, "fasta"): print(infile_fasta)
my_seq = seq_record.seq
my_fasta = str(my_seq) #convert to a string
print(my_fasta)
# print( len(my_fasta) )
# print( type(my_fasta) )
len(my_fasta)
############# #############
# SNP info # meta data
#############
# FIXME when you change the dir struc
inpath_p = "git/Data/pyrazinamide/input/processed"
in_filename_meta_data = "meta_data_with_AFandOR.csv"
infile_meta_data = homedir + '/' + inpath_p + '/' + in_filename_meta_data
print("Input file is:", infile_meta_data)
#=======
# output
#=======
outdir = 'git/Data/pyrazinamide/output'
# filenames in respective sections
################## end of variable assignment for input and output files
#%%
#==========
# read files
#==========
#############
# fasta file
#############
my_fasta_o = str()
for seq_record in SeqIO.parse(infile_fasta, "fasta"):
my_seq = seq_record.seq
my_fasta_o = str(my_seq) #convert to a string
print(my_fasta_o)
print(len(my_fasta_o))
# print( type(my_fasta) )
# remove non_struc positions from fasta
def remove_char(str, n):
first_part = str[:n]
last_part = str[n+1:]
return first_part + last_part
#print(remove_char('Python', 0))
ns_pos_o = 186
offset = 1 # 0 based indexing
ns_pos = ns_pos_o - offset
my_fasta = remove_char(my_fasta_o, ns_pos)
print("orig length:", len(my_fasta_o))
print("new length:", len(my_fasta))
#############
# SNP info and no of MSA to generate
############# #############
# read mutant_info file and extract cols with positions and mutant_info # read mutant_info file and extract cols with positions and mutant_info
# This should be all samples with pncA muts # This should be all samples with pncA muts
#my_data = pd.read_csv('mcsm_complex1_normalised.csv') #335, 15 #my_data = pd.read_csv('mcsm_complex1_normalised.csv') #335, 15
#my_data = pd.read_csv('meta_data_with_AFandOR.csv') #3093, 22 my_data = pd.read_csv(infile_meta_data)
my_data = pd.read_csv(infile_meta_data) #3093, 22
list(my_data.columns) list(my_data.columns)
#my_data['OR'].value_counts()
#my_data['OR'].isna().sum()
#FIXME: You need a better way to identify this #FIXME: You need a better way to identify this
# ideally this file should not contain any non_struc pos
# remove positions not in the structure # remove positions not in the structure
#pos_remove = 186 my_data = my_data[my_data.position != ns_pos_o] #3092, 22
my_data = my_data[my_data.position != 186] #3092, 22
# if multiple positions, then try the example below; # if multiple positions, then try the example below;
# https://stackoverflow.com/questions/29017525/deleting-rows-based-on-multiple-conditions-python-pandas # https://stackoverflow.com/questions/29017525/deleting-rows-based-on-multiple-conditions-python-pandas
#df = df[(df.one > 0) | (df.two > 0) | (df.three > 0) & (df.four < 1)] #df = df[(df.one > 0) | (df.two > 0) | (df.three > 0) & (df.four < 1)]
#mut_info1 = my_data[['Position', 'Mutant_type']] #335, 2 mut_info1 = my_data[['position', 'mutant_type']]
mut_info1 = my_data[['position', 'mutant_type']] #3092, 2 #%%
################
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
###############
# data cleaning # data cleaning
################ ################
# extract only those positions that have a frequency count of pos>1 # extract only those positions that have a frequency count of pos>1
###mut_info['freq_pos'] = mut_info.groupby('Position').count()#### dodgy ###mut_info['freq_pos'] = mut_info.groupby('Position').count()#### dodgy
# add a column of frequency for each position # add a column of frequency for each position
#mut_info1['freq_pos'] = mut_info1.groupby('Position')['Position'].transform('count') #335,3 #mut_info1['freq_pos'] = mut_info1.groupby('position')['position'].transform('count')
mut_info1['freq_pos'] = mut_info1.groupby('position')['position'].transform('count') #3092,3 mut_info1['freq_pos'] = mut_info1.position.map(mut_info1.position.value_counts())
# sort by position # sort by position
mut_info2 = mut_info1.sort_values(by=['position']) mut_info2 = mut_info1.sort_values(by=['position'])
#FIXME
#__main__:1: SettingWithCopyWarning:
#A value is trying to be set on a copy of a slice from a DataFrame.
#Try using .loc[row_indexer,col_indexer] = value instead
#See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
#sort dataframe by freq values so the row indices are in order!
#mut_info2 = mut_info1.sort_values(by = 'freq_pos'
# , axis = 0
# , ascending = False
# , inplace = False
# , na_position = 'last')
#mut_info2 = mut_info2.reset_index( drop = True)
# count how many pos have freq 1 as you will need to exclude those # count how many pos have freq 1 as you will need to exclude those
mut_info2[mut_info2.freq_pos == 1].sum() #20 mutfreq1_count = mut_info2[mut_info2.freq_pos == 1].sum().freq_pos
# extract entries with freq_pos>1 # extract entries with freq_pos>1
# should be 3093-211 = 3072 # should be 3093-211 = 3072
mut_info3 = mut_info2.loc[mut_info2['freq_pos'] >1] #3072 mut_info3 = mut_info2.loc[mut_info2['freq_pos'] >1] #3072
print("orig length:", len(mut_info1))
print("No. of excluded values:", mutfreq1_count)
print("new length:", len(mut_info3))
# sanity check
if ( (len(mut_info1) - mutfreq1_count) == len(mut_info3) ):
print("Sanity check passed: Filtered data correctly")
else:
print("Error: Debug you code")
# reset index to allow iteration <<<<<<<< IMPORTANT # reset index to allow iteration !!!!!!!!!! IMPORTANT
mut_info = mut_info3.reset_index(drop = True) mut_info = mut_info3.reset_index(drop = True)
del(mut_info1, mut_info2, mut_info3, my_data) ##del(mut_info1, mut_info2, mut_info3, my_data)
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
################### ###################
# generate mut seqs # generate mut seqs
################### ###################
@ -132,20 +143,19 @@ mut_seqsL = [] * len(mut_info)
# iterate # iterate
for i, pos in enumerate(mut_info['position']): for i, pos in enumerate(mut_info['position']):
print('index:', i, 'position:', pos)
mut = mut_info['mutant_type'][i]
# print(mut)
# print( type(mut) )
print('index:', i, 'position:', pos, 'mutant', mut)
my_fastaL = list(my_fasta) my_fastaL = list(my_fasta)
offset_pos = pos-1 #due to counting starting from 0 mut = mut_info['mutant_type'][i]
offset_pos = pos-1
print('1-index:', pos, '0-index cur:', offset_pos, my_fastaL[offset_pos], 'mut:', mut)
my_fastaL[offset_pos] = mut my_fastaL[offset_pos] = mut
# print(my_fastaL) print('1-index:', pos, '0-index new:', offset_pos, my_fastaL[offset_pos], 'mut:', mut)
mut_seq = "".join(my_fastaL) mut_seq = "".join(my_fastaL)
# print(mut_seq + '\n') # print(mut_seq + '\n')
print('original:', my_fasta, ',', 'replaced:', my_fasta[offset_pos], 'at', pos, 'with', mut, mut_seq)
mut_seqsL.append(mut_seq) mut_seqsL.append(mut_seq)
# print('original:', my_fasta, ',', 'replaced at', pos, 'with', mut, mut_seq)
############### ###############
# sanity check # sanity check
@ -167,78 +177,16 @@ del(i, len_orig, mut, mut_seq, my_fastaL, offset_pos, pos, seqs)
############ ############
#filepath = homedir +'/git/LSHTM_Y1_PNCA/combined_v3/logo_plot/snp_seqsfile' #filepath = homedir +'/git/LSHTM_Y1_PNCA/combined_v3/logo_plot/snp_seqsfile'
#filepath = homedir + '/git/LSHTM_Y1_PNCA/mcsm_analysis/pyrazinamide/Data/gene_msa.txt' #filepath = homedir + '/git/LSHTM_Y1_PNCA/mcsm_analysis/pyrazinamide/Data/gene_msa.txt'
print(outdir)
print(outpath) out_filename = "gene_msa.txt"
out_filename_gene = "/gene_msa.txt" outfile_gene = homedir + '/' + outdir + '/' + out_filename
outfile_gene = homedir + basedir + outpath + out_filename_gene print(outfile_gene)
print("Output file is:", outfile_gene)
with open(outfile_gene, 'w') as file_handler: with open(outfile_gene, 'w') as file_handler:
for item in mut_seqsL: for item in mut_seqsL:
file_handler.write("{}\n".format(item)) file_handler.write("{}\n".format(item))
R="\n".join(mut_seqsL) #R = "\n".join(mut_seqsL)
f = open('Columns.csv','w') #f = open('Columns.csv','w')
f.write(R) #f.write(R)
f.close() #f.close()
#################################################################################
# extracting only positions with SNPs so that when you plot only those positions
################################################################################
#mut_seqsL = mut_seqsL[:3] #just trying with 3 seqs
# create a list of unique positions
pos = mut_info['position'] #3072
posL = list(set(list(pos))) #110
del(pos)
snp_seqsL = [] * len(mut_seqsL)
for j, mut_seq in enumerate(mut_seqsL):
print (j, mut_seq)
# print(mut_seq[101]) #testing, this should be P, T V (in order of the mut_info file)
mut_seqsE = list(mut_seq)
# extract specific posistions (corres to SNPs) from list of mutant sequences
snp_seqL1 = [mut_seqsE[i-1] for i in posL] #should be 110
# print(snp_seqL1)
# print(len(snp_seqL1))
snp_seq_clean = "".join(snp_seqL1)
snp_seqsL.append(snp_seq_clean)
###############
# sanity check
################
no_unique_snps = len(posL)
# checking if all the mutant sequences have the same length as the original fasta file sequence
for seqs in snp_seqsL:
# print(seqs)
# print(len(seqs))
if len(seqs) != no_unique_snps:
print('sequence lengths mismatch' +'\n', 'mutant seq length:', len(seqs), 'vs original seq length:', no_unique_snps)
else:
print('**Hooray** Length of mutant and original sequences match')
del(mut_seq, mut_seqsE, mut_seqsL, seqs, snp_seqL1, snp_seq_clean)
############
# write file
############
#filepath = homedir +'/git/LSHTM_Y1_PNCA/combined_v3/logo_plot/snp_seqsfile'
#filepath = homedir + '/git/LSHTM_Y1_PNCA/mcsm_analysis/pyrazinamide/Data/snps_msa.txt'
print(outpath)
out_filename_snps = "/snps_msa.txt"
outfile_snps = homedir + basedir + outpath + out_filename_snps
print("Output file is:", outfile_snps)
with open(outfile_snps, 'w') as file_handler:
for item in snp_seqsL:
file_handler.write("{}\n".format(item))
R="\n".join(snp_seqsL)
f = open('Columns.csv','w')
f.write(R)
f.close()