sagecode98 / bioinformatics-

bioinformatic python, SQL and R studio code

Python basic python functions:

#!/usr/bin/env python3 r = 7.5 pi = 3.1415 circumference = 2pir print "circumference:" , circumference

x = pi*r print "r:" , r print "pi:" , pi print "x:" , x

p="10" t="7" q="70" string_test = "{0}X{1}={2}" print(string_test.format(p,t,q))

dna = 'ATGGAACCAACGTCAGTGACTTCGTCAG' print "The lenght of your sequence is:" , len(dna)

print "The first codon is:", dna[:3]

count_motif = dna.count("AA") print "There are",count_motif, "instances of the motif'AA':"

#!/usr/bin/env python3 program that prints all the numbers from 1 to 100, inclusive, each on its own line. x = 1 while x <=100: print(x) x = x + 1

Start a script with the following line: counts = '8,3,6,2,12,5' Transform this comma-separated string into a list using the split() function. The program should take each element of that list in turn and divide it into 48 (i.e. 48/element) and print the result of the division, like this: 48 / 8 = 6.0

counts = '8,3,6,2,12,5'

result = list(map(int, counts.split(',')))

for x in range(0, len(result)): print ('48/%s='%(result[x]),48/result[x])

function called start_codon which accepts a DNA sequence as its argument and returns the first codon as a string.

start_codon = raw_input(" Enter DNA sequence: ")

print(start_codon[:3])

Script to count the number of sequence entries within this file and report the count like:

F = open("e_coli_k12_dh10b.faa","r") test_string = F.read() print ("There were", test_string.count(">gi") ,"sequences within the file")

F.close()

fasta_sequence_count = raw_input(" Enter Sequence: ") print ("There were",fasta_sequence_count.count(">gi") ,"sequences within the file")

#!/usr/bin/env python3

import re

pattern = re.compile('bc*')

text12 = '''abccccccccccccccccccccccccccccccccccccccccccdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ *********** regular expressions 0123456789 b b b b ''' Whatever ='ABC240ABC-444ABC-947ABC0'

matches = pattern.finditer(text12)

for match in matches:

    print(match)

pattern1 = re.compile('\+**')

matches1 = pattern1.finditer(text12)

for match in matches1:

    print(match)

pattern2 = re.compile('\D\D\D\d+\D\D\D[-]\d+\D\D\D')

matches2 = pattern2.finditer(Whatever)

for match in matches2:

    print(match)

pattern3 = re.compile('\b\w{5}')

matches3 = pattern3.finditer(text12)

for match in matches3:

    print(match)

F = open('users.txt.',"r") contents = F.read()

who_pattern = re.compile('^\w*')

where_pattern = re.compile('pts/\d+')

when_and_IP_pattern = re.compile('\d\d\d\d[-]\d\d[-]\d\d\s\d\d[:]\d\d\s[(]\w*\W\w*\W\w*\W\w*[)]?\W(\d\d\d|\d\d)?(\W)?(hsd1|nyc|win)?(\W)(md|res|ad)?(\W)?(comcast|rr|jhu)?(\W)?(net|com|edu)?(\W)?')

who = who_pattern.finditer(contents) where = where_pattern.finditer(contents) when_and_IP = when_and_IP_pattern.finditer(contents)

length = len(who) for x in range(0,length): print(who[x],'on',where[x],'at',when_and_IP[x])

#print ('%son%sat%s'%who,where,when_and_IP)

word= ('boy, girl, sister, brother, the pain I feel, town, house townhouse') words= word.split(",") count = 0 lenght= len(words) for i in range(0,lenght): if re.search('[aeiouAEIOU]',words[i], flags=re.I): count=count+1; if count >=2 : print("has vowels") break else: print(" doesnt have vowels")

vowels in words: if words == (vowels[0],[1],[2],[3],[4])

            print (vowels[0][1])

teststring = "this is a test,string" pattern = re.compile(\w+(\s*),\w+(\s*) words= pattern.finditer(teststring)); word = sords.split(",")

print(word) (END)

biopython edited modules: #!/usr/bin/env python3

from Bio.Alphabet import IUPAC

from Bio.SeqUtils.ProtParam import ProteinAnalysis

from Bio import SeqIO

from operator import itemgetter

amino_acids = ('A','R','N','D','C','Q','E','G','H','O','I','L','K','M','F','P','U','S','T','W','Y','V')

handle = open("e_coli_k14_dh10b.faa","rU") length_file = SeqIO.parse(handle, "fasta") count = [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] percentage = [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]

for record in SeqIO.parse(handle, "fasta",IUPAC.protein): seq = record.seq.tostring() analysed_seq = ProteinAnalysis(seq) D = analysed_seq.count_amino_acids()

print (D)

print (D.keys())

print (D.values())

    listval = [D.get(key, 0) for key in amino_acids]

print(listval)

    for i in range (0,20) :
            count[i] = count[i] + listval[i]

    #C =  analysed_seq.get_amino_acids_percent()
    #print (C)

summation = sum(count) for k in range(0,20): #print(count[k]) multiply = count[k]*100 percentage[k] = multiply/float(summation)

test_list=list(zip(amino_acids,count)) #print(test_list) #print (summation)

#print(percentage)

#sorted_values=sorted(test_list) sorted_values=sorted(test_list,key=itemgetter(1)) #print (sorted_values) sorted_percentage = sorted(percentage)

for j in range (15,20) : print (sorted_values[j],sorted_percentage[j])

#print (sorted_values)

(END)

Object oriented programing: module #!/usr/bin/python3 import random class healthRecord(object): patient_first_name = 'John' patient_last_name = 'Miller' patient_BP = '' sys=0 dia=0 patient_health = 'Good'

    def change_last_namex(self,last_name):
            self.patient_last_name=last_name
    def set_health_record(self):
            sys = random.randint(70, 180)
            dia = random.randint(40, 100)
            record=str(sys) +'/' + str(dia)
            self.patient_sys=sys
            self.patient_dia=dia
            self.patient_BP=record

    def get_BP(self):
        return self.patient_BP
    def get_health(self):
        if (self.sys >= 100 and self.sys <120):
           if (self.dia >=70 and self.dia <=80):
              self.health='good'
           else:
              self.health='bad'
        else:
           self.health='bad'
        return self.health

module1.py (END)

#!/usr/local/bin/python3 from module1 import healthRecord p = healthRecord() print ('Health reacord for '+ p.patient_first_name + p.patient_last_name) p.change_last_namex("papa") print ('Health reacord for '+ p.patient_first_name + p.patient_last_name) p.set_health_record() print ("patient record after updating:") r=p.get_BP() print('patient BP is' + r) q=p.get_health() print(q) #print ('patient has' + p.gethealth() + 'blood pressure') pythoncode_script1 (END)

R studio code data query data library("biomaRt")

ensembl = useMart("fungal_mart", dataset='scerevisiae_eg_gene',host="fungi.ensembl.org")

getBM(attributes=c('entrezgene','external_gene_name','name_1006','go_linkage_type'), filters='go', values= 'GO:0006623', mart=ensembl) End.

data query for Clinvar SNPs: getBM(attributes = c('refsnp_id','refsnp_source','chrom_start','chr_name','chrom_end','translation_start','translation_end','consequence_type_tv','sift_prediction','polyphen_prediction'), filters = c('chr_name'), values = list(1), mart = snpmart)

bioinformatics-

bioinformatic python, SQL and R studio code SQL code to creat and edit Genbank table -> CREATE TABLE genes ( -> ProteinID varchar(15), -> Product varchar(200), -> Gene varchar(100), -> Start char(8), -> Stop char(8), -> locus_tag varchar(20), -> translation varchar(2000) -> );

SELECT statement to return just the thrB gene. select Gene from genes where Gene= 'thrB'; SELECT statement to return all three genes which starts with 'thr' mysql> select Gene from genes where gene like ('thr%'); SELECT statement to return all genes whose start site falls between base 2500 and 5000. select * from genes where start >2500 and start<5000; INSERT statement that could have been used to add thrB (all fields). insert into genes values ('ACB01208.1','Homoserine kinase','thrB',2801,3733);

biotest database

Number of entries in the organism table: SELECT COUNT(*) FROM organism;

SELECT statement which queries the locus ID and product for all genes which contain the word 'lyase'. SELECT locus_ID , product from genes where product like '%lyase%';

Query for the locus ID, start and stop coordinates for all genes which have a start coordinate between 10,000 and 50,000. SELECT locus_ID , start , stop from genes where start>10000 and start<50000;

single query which returns all gene rows with the following two columns: Locus ID, G SELECT locus_ID , genus FROM genes join organism on genes.org_id=organism.id ;