mirDIP : microRNA Data Integration Portal

You can use this API for calling mirDIP from your Python code.

	




# Note: Works with Python 3 and up

import urllib.request, urllib.parse


# ########################################################################################################
#                                                   class library mirDIP_Http                            #
# ########################################################################################################
class mirDIP_Http:

    mapScore = {
    'Very High' : '0',
    'High' : '1',
    'Medium' : '2',
    'Low' : '3'
    }


    url = "http://ophid.utoronto.ca/mirDIP"
        
    map = {}    # results will be here

    def __init__(self):
        return

    
    # unidirectional on genes
    def unidirectionalSearchOnGenes(self, geneSymbols, minimumScore):
    
        self.sendPost(self.url + "/Http_U", geneSymbols, '', self.mapScore[minimumScore])
        return


    # unidirectional on microrna(s)
    def unidirectionalSearchOnMicroRNAs(self, microRNAs, minimumScore):
            
        self.sendPost(self.url + "/Http_U", '', microRNAs, self.mapScore[minimumScore])
        return


    # bidirectional        
    def bidirectionalSearch(self, geneSymbols, microRNAs, minimumScore, sources, occurrances):

        '''
            String url_b = url + "/Http_B";
            
            String parameters = 
                    "genesymbol=" + geneSymbols + 
                    "&" + "microrna=" + microRNAs +
                    "&" + "scoreClass=" + mapScore.get(minimumScore) + 
                    "&" + "dbOccurrences=" + occurrances +
                    "&" + "sources=" + sources;
            
            int responseCode = sendPost(url_b, parameters);
            return responseCode;
        '''

        self.sendPost(self.url + "/Http_B", geneSymbols, microRNAs, self.mapScore[minimumScore], sources, occurrances)
        return        


       
    # .. serve POST request
    def sendPost(self, url_, geneSymbols, microrna, minimumScore, sources = '', occurrances = '1'):

        params = {
        'genesymbol' : geneSymbols,
        'microrna' : microrna,
        'scoreClass' : minimumScore,
        'dbOccurrences' : occurrances,
        'sources' : sources}

        params = bytes( urllib.parse.urlencode( params ).encode() )
        response = ''

        try:
            handler = urllib.request.urlopen(url_, params)
        except Exception:
            traceback.print_exc()
        else:
            self.response = handler.read().decode('utf-8')
            ## print(self.response)
            self.makeMap()

        return


    def makeMap(self):
            
        ENTRY_DEL = 0x01
        KEY_DEL = 0x02
            
        arr = self.response.split(chr(ENTRY_DEL))
            
        for str in arr:
                
            arrKeyValue = str.split(chr(KEY_DEL));
            if len(arrKeyValue) > 1: 
                self.map[arrKeyValue[0]] = arrKeyValue[1]

        return

    def getGeneratedAt(self): 

        if "generated_at" in self.map: 
            return self.map["generated_at"]
        else:
            return ''


    def getGeneSymbols(self):
       
        if "gene_symbols" in self.map:
            return self.map["gene_symbols"]
        else:
            return ''


    def getMicroRNAs(self): 
        if "micro_rnas" in self.map: 
            return self.map["micro_rnas"]
        else:
            return ''

    def getMinimumScore(self): 
        if "minimum_score" in self.map: 
            return self.map["minimum_score"]
        else:
            return ''

    def getDatabaseOccurrences(self):
        if "dbOccurrences" in self.map: 
            return self.map["dbOccurrences"]
        else: 
            return ''

    def getSources(self):
        if "sources" in self.map: 
            return self.map["sources"]
        else:
            return '' 
        
    def getResulsSize(self):
        if "results_size" in self.map: 
            return self.map["results_size"]
        else: 
            return ''

    def getResuls(self): 
        if "results" in self.map: 
            return self.map["results"]
        else: 
            return ''





#########################################################################################################
#                                          Pick-up right sample for your search                         #
#########################################################################################################
# Note: Adjust 'ophid.utoronto.ca' if you are using our development server.

        

# **************************************************
# Example of Unidirectional search on Gene Symbols *
# **************************************************
# GeneSymbols 
#      - Comma delimited. 
#      - Follow to HUGO approved spelling.)
geneSymbols = "AKAP17A,AKR1C2,APP,ZZZ3,MARK4,C17orf51"
# Minimum Score 
#      - Use one of those: 'Very High', 'High', 'Medium', 'Low'. 
#      - Mind exact spelling.
minimumScore = "Very High"


o = mirDIP_Http()   # note: re-instance with every search !!!
o.unidirectionalSearchOnGenes(geneSymbols, minimumScore)

# print results
print("\r\n  Unidirectional Search on Genes:  \r\n")
print("Generated at: " + o.getGeneratedAt())
print("Gene Symbols: " + o.getGeneSymbols())
print("Minimum Score: " + o.getMinimumScore())
print("Results Size: " + o.getResulsSize())
print("Results: \r\n" + o.getResuls());     # formatted as tab-delimited spreadsheet



# ***********************************************
# Example of Unidirectional search on MicroRNAs *
# ***********************************************
# MicroRMAs 
#      - Comma delimited. 
#      - Follow the notation as shown.
microRNAs = "hsa-miR-603, hsa-let-7a-3p, hsa-miR-625-5p, hsa-miR-7852-3p, hsa-miR-17-5p"

# Minimum Score 
#      - Use one of those: 'Very High', 'High', 'Medium', 'Low'. 
#      - Mind exact spelling.
minimumScore = "Very High"


o = mirDIP_Http()   # note: re-instance with every search !!!

o.unidirectionalSearchOnMicroRNAs(microRNAs, minimumScore)

# print results
print("\n  Unidirectional Search on microRNAs  \n");
print("Generated at: " + o.getGeneratedAt());
print("Micro RNAs: " + o.getMicroRNAs());
print("Minimum Score: " + o.getMinimumScore());
print("Results Size: " + o.getResulsSize());
print("Results: \r\n" + o.getResuls());      # formatted as tab-delimited spreadsheet




        
# *********************************
# Example of Bidirectional search *
# *********************************
# GeneSymbols 
#      - Comma delimited. 
#      - Follow to HUGO approved spelling.
geneSymbols = "AKAP17A,AKR1C2,APP,ZZZ3,MARK4, C17orf51"
            
# MicroRMAs 
#       - Comma delimited; 
#      - Follow the notation as shown.
microRNAs = "hsa-miR-603,hsa-let-7a-3p,hsa-miR-625-5p,hsa-miR-7852-3p," + \
                "hsa-miR-17-5p,hsa-miR-4321,hsa-miR-758-3p"
            
# Minimum Score
#      - Use one of those: 'Very High', 'High', 'Medium', 'Low'. 
#      - Mind exact spelling.
minimumScore = "Very High"
            
# Sources 
#      - Use ony combination of those: 
#              bitargeting_May_2021, BCmicrO, CoMeTa, Cupid, DIANA, miranda_May_2021, 
#              mirbase, mirCoX, mirmap_May_2021, mirzag, miRcode, miRDB_v6, miRTar2GO, 
#              MBStar, MirAncesTar, MirSNPInTarget, MirTar2, MiRNATIP, MultiMiTar, PACCMIT, 
#              PITA_May_2021, rnahybrid_May_2021, RNA22, TargetScan_v7_2
#      - Mind exact spelling
sources = "bitargeting_May_2021, BCmicrO, CoMeTa, Cupid, DIANA, miranda_May_2021, " + \
            "mirbase, mirCoX, mirmap_May_2021, mirzag, miRcode, miRDB_v6, miRTar2GO, " + \
            "MBStar, MirAncesTar, MirSNPInTarget, MirTar2, MiRNATIP, MultiMiTar, PACCMIT, " + \
            "PITA_May_2021, rnahybrid_May_2021, RNA22, TargetScan_v7_2"

# Data
# Database Occurrences (named as 'Number of Sources' on 'Bidirectional search' web page): 
#          - Use this option to select microRNA target predictions that are 
#              present in at least a given number of sources - irrespective 
#              of what those sources are.
#          - The valid values are: from 1 to 24
occurrances = '2'


o = mirDIP_Http()   # note: re-instance with every search !!!

o.bidirectionalSearch(geneSymbols, microRNAs, minimumScore, sources, occurrances)

# print results
print("\n  Bidirectioanl Search:  \n")
print("Generated at: " + o.getGeneratedAt())
print("Gene Symbols: " + o.getGeneSymbols())
print("Minimum Score: " + o.getMinimumScore())
print("Database Occurrences: " + o.getDatabaseOccurrences())
print("Source Filter: " + o.getSources())
print("Results Size: " + o.getResulsSize())
print("Results: \r\n" + o.getResuls());      # formatted as tab-delimited spreadsheet