def main():
# Read in the RNA sequences from a file specified by user input
filename = input("Please enter the input file name: ")
rnainfo = readfasta(filename)
# Prepare to re-write the RNA sequences to an output file specified by user input
outfilename = input("Please enter the output file name: ")
handle = open(outfilename, mode="w")
# Iterate through each RNA sequence in the input file
for i in range(len(rnainfo)):
# Specify gene that is being evaluated
handle.write("Gene " + str(i + 1) + ": " + rnainfo[i][2] + "\n\n")
# Translate the RNA Sequence to its corresponding single-letter amino acid sequence
# Write information to the output file
translatedseq = translate(rnainfo[i][2])
handle.write("Protein Sequence " + str(i + 1) + ": " + translatedseq +
"\n\n")
# Scan the single-letter amino acid sequence for transmembrane helices
# Write results to the output file
findTMD(translatedseq, handle)
# Close file
handle.close()
#!/usr/bin/python
import sys
from fasta import readfasta
f = open(sys.argv[1], "r")
fd = readfasta(f)
for key in fd:
sequence = fd[key][15720:15725]
print sequence
homozygote = 'ATCG'
SNPs = 'RYSWKMBDHV'
homozygote_count = len(
[base.upper() for base in sequence if base.upper() in homozygote])
SNPs_count = len(
[base.upper() for base in sequence if base.upper() in SNPs])
print homozygote_count
print SNPs_count
GCs = 'GC'
homozygote_count = len(
[base.upper() for base in sequence if base.upper() in homozygote])
GC_count = len([base.upper() for base in sequence if base.upper() in GCs])
return homozygote_count, GC_count
#************************************************
# Read bed and fasta input files
#************************************************
overlapping = open(sys.argv[1], "r")
fasta_seq = open(sys.argv[2], "r")
out = open(sys.argv[3], "w")
#************************************************
# Read fasta file in dictionary
fasta_dict = readfasta(fasta_seq)
#************************************************
#************************************************
# Read overlap file in dictionary
#************************************************
overlapping_list = [] # Create a list to keep order when printing
overlapping_dict = {}
multi_window_intervals = {}
for line in overlapping:
line = line.strip("\n").split("\t")
key = line[0] + ":" + line[1] + ":" + line[2]
value = [int(line[4]), int(line[5]), int(line[6])]
if key in overlapping_dict.keys():
overlapping_dict[key].append(value)
else:
overlapping_dict[key] = [value]
# use them for resampling.
# Usage: ./compile_sequences.py seq.fasta seq.coordinates seq.scaf.chro
fastaseq = open(sys.argv[1], "r") # File one is the fasta sequence
intergenic = open(sys.argv[2], "r") # File two is the intergenic file
chrfile = open(sys.argv[3], "r") # File three is the chromosome file that
# contains all the scaffolds for that chromosome.
def chunks(s, n):
for start in range(0, len(s), n):
yield s[start:start + n]
# Read the fasta file into a dictionary
fastaDict = readfasta(fastaseq)
#print fastaDict
# Read the intergenic coordinates into a dictionary
def intergenicCoord(intergenic):
intergenicDict = {}
for line in intergenic:
line = line.strip().split("\t")
key, value = line[0], line[1:]
if line[0] in intergenicDict.keys():
intergenicDict[key].append(value)
else:
intergenicDict[key] = [value]
return intergenicDict
#!/usr/bin/python
from __future__ import division
import sys
from fasta import readfasta
from het import heterozygosity
fasta = sys.argv[1]
# Read fasta into a dictionary
with open(fasta, 'r') as f:
fasta_dict = readfasta(f)
# Calculate heterozygosity for every scaffold
for key in fasta_dict.keys():
het = heterozygosity(fasta_dict[key])
print(key + "\t" + str(het[0]) + "\t" + str(het[1]) + "\t" + str(het[2]))
# It reads the intron coordinates generated by extract_from_gff.py into a dictionary,
# extract the corresponding sequences from a fasta file and then runs the heterozygosity
# function to count the number of SNPs and bases.
# Usage: ./intron_heterozygosity.py intron_coordinates.txt fasta.fa > output
##########################################################################################
#***************************************************
# Read the intron coordinates and the fasta sequence
#***************************************************
intron_coord = open(sys.argv[1], 'r')
fasta = open(sys.argv[2], 'r')
#******************************************
# Read the fasta sequence into a dictionary
#******************************************
fastaseq = readfasta(fasta)
#**********************************************
# Read the intron coordinates into a dictionary
#**********************************************
intron_dict = {}
for line in intron_coord:
line = line.strip('\n').split('\t')
key, value = line[0], line[1:]
if key in intron_dict.keys():
intron_dict[key].append(value)
else:
intron_dict[key] = [value]
#**************************************************************************
# Extract the intronic sequences from fasta and read them into a dictionary
if not isinstance(sequence, str):
raise Exception("Sequence is not a string")
R = len([base.upper() for base in sequence if base.upper() == "R"])
Y = len([base.upper() for base in sequence if base.upper() == "Y"])
S = len([base.upper() for base in sequence if base.upper() == "S"])
W = len([base.upper() for base in sequence if base.upper() == "W"])
K = len([base.upper() for base in sequence if base.upper() == "K"])
M = len([base.upper() for base in sequence if base.upper() == "M"])
return (R, Y, S, W, K, M)
################################################################################
fastafile = open(sys.argv[1], "r")
fastadict = readfasta(fastafile)
R_l = []
Y_l = []
S_l = []
W_l = []
K_l = []
M_l = []
for key in fastadict.keys():
R = trans_tranv_count(fastadict[key])[0]
Y = trans_tranv_count(fastadict[key])[1]
S = trans_tranv_count(fastadict[key])[2]
W = trans_tranv_count(fastadict[key])[3]
K = trans_tranv_count(fastadict[key])[4]
M = trans_tranv_count(fastadict[key])[5]
R_l.append(R)
# If run: ./Open_reading_frame.py CDS.fa SW > output
# The script counts only S and W sites.
# CDS.fa is produced by extract_CDS_from_fasta.py and contains a fasta sequence with IUPAC
# coded SNPs.
##########################################################################################
#*******************
# Specify the inputs
#*******************
inFile = open(sys.argv[1], 'r')
argument = sys.argv[2]
#************************************************************
# Read the fasta file into a dictionary
#************************************************************
fastaseq = readfasta(inFile)
# Specify four nucleotides
#************************************************************
nucs = ["A", "T", "C", "G"]
#************************************************************
# Specify IUPAC codes as a dictionary
#************************************************************
IUPAC_code = {
'R': ['A', 'G'],
'Y': ['C', 'T'],
'S': ['G', 'C'],
'W': ['A', 'T'],
'K': ['G', 'T'],
'M': ['A', 'C']
} #, 'B':['C', 'G', 'T'], 'D':['A', 'G', 'T'], 'H':['A', 'C', 'T'], 'V':['A', 'C', 'G']}
# Four fold degenerate sites
# The script counts only S and W sites.
# CDS.fa is produced by extract_CDS_from_fasta.py and contains a fasta sequence with IUPAC
# coded SNPs.
##########################################################################################
#*******************
# Specify the inputs
#*******************
inFile = open(sys.argv[1], 'r')
argument = sys.argv[2]
#strand = open(sys.argv[3], "r")
#************************************************************
# Read the fasta file into a dictionary
#************************************************************
dna_orf = readfasta(inFile)
# Specify four nucleotides
#************************************************************
nucs = ["A", "T", "C", "G"]
#************************************************************
# Specify IUPAC codes as a dictionary
#************************************************************
IUPAC_code = {
'R': ['A', 'G'],
'Y': ['C', 'T'],
'S': ['G', 'C'],
'W': ['A', 'T'],
'K': ['G', 'T'],
'M': ['A', 'C']
} #, 'B':['C', 'G', 'T'], 'D':['A', 'G', 'T'], 'H':['A', 'C', 'T'], 'V':['A', 'C', 'G']}
# Four fold degenerate sites
# dictionary, it then extracts the CDS coordinates from the fasta file and finally #
# concatenates each sequence to the other to create a CDS with SNPs marked #
# as IUPAC code. #
# Usage: ./extract_CDS_from_Fasta.py cds.txt fasta.fa > output #
######################################################################################
#*******************
# Specify the inputs
#*******************
cds_file = open(sys.argv[1], 'r')
fasta = open(sys.argv[2], 'r')
#************************************************************
# Read the fasta file into a dictionary
#************************************************************
fastaDict = readfasta(fasta)
# With the current readfasta() function, it's much faster to
# use the single line fasta sequence
#*******************************************
# Read the CDS coordinates into a dictionary
#*******************************************
CDS_dict = {}
for line in cds_file:
line = line.strip('\n').split('\t')
key, value = line[0], line[1:3]
if key in CDS_dict.keys():
CDS_dict[key].append(value)
else:
CDS_dict[key] = [value]
#print CDS_dict
# synonymous, missense and nonsense according to the following rule: #******************************************************************* # Inputs: sequence.fa annotation.gff #******************************************************************* # Run: annotate_vcf.py sequence.fa annotation.gff > output.txt #******************************************************************* #******************************************************************* # Open inputs #******************************************************************* fastafile = open(sys.argv[1], "r") gff_file = open(sys.argv[2], "r") #******************************************************************* # Read fasta file into dictionary #******************************************************************* g_fasta = readfasta(fastafile) #******************************************************************* # Read gff file into dictionary #******************************************************************* gff_dict = gff_to_dict(gff_file) #******************************************************************* # Create the degeneracy count table #******************************************************************* degeneracy_table_counts = count_sites()[0] #******************************************************************* # Create the degeneracy base table #******************************************************************* degeneracy_table_bases = count_sites()[1] #******************************************************************* #*******************************************************************
#*******************************************************************************
# Written by Homa Papoli - October 2017
#*******************************************************************************
# Script contains functions to:
# 1. Generate a fasta sequence without N
# 2. Perform resampling from the fasta sequence to generate new sequence
# 3. Calculate heterozygosity from the new sequence
#*******************************************************************************
f1 = open(sys.argv[1], "r")
seq = sys.argv[2] # indicate which chromosome to resample
replicates = int(sys.argv[3]) # number of resampling
num = int(sys.argv[4]) # indicate the length from which to sample
# Read the fasta file into a dictionary.
fastadict = readfasta(f1)
#def resampling_f(fastadict, seq, num):
# fastadict[seq] = fastadict[seq].replace("N","").replace("n","")
# l = []
# # If sampling the sequence as long as the original one
# # new_seq = ''.join([random.choice(fastadict[seq]) for nuc in fastadict[seq]])
# # If sampling the sequence for a specific set of number
# new_seq = ''.join([random.choice(fastadict[seq]) for i in range(num)]) # New sequences
# new_seq_het = list(heterozygosity(new_seq))[2] # Het of the new sequence
# l.append(new_seq_het)
# return l
def resampling_f(fastadict, seq, n, k):
fastadict[seq] = fastadict[seq].replace("N", "").replace("n", "")
seq_list = np.random.choice(tuple(fastadict[seq]),
