--- a/cpo_galaxy_prediction.py	Fri Aug 24 19:10:42 2018 -0400
+++ b/cpo_galaxy_prediction.py	Sat Aug 25 20:56:37 2018 -0400
@@ -457,7 +457,10 @@
         pf.start = int(plasmidFinder.iloc[i,2])
         pf.end = int(plasmidFinder.iloc[i,3])
         pf.gene = str(plasmidFinder.iloc[i,4])
-        pf.shortGene = pf.gene[:pf.gene.index("_")]
+        if (pf.gene.find("_") > -1):
+            pf.shortGene = pf.gene[:pf.gene.index("_")]
+        else:
+            pf.shortGene = pf.gene
         pf.coverage = str(plasmidFinder.iloc[i,5])
         pf.coverage_map = str(plasmidFinder.iloc[i,6])
         pf.gaps = str(plasmidFinder.iloc[i,7])
@@ -528,12 +531,14 @@
     rgiAMR = ParseRGIResult(rgi, plasmidContigs, likelyPlasmidContigs) # outputDir + "/predictions/" + ID + ".rgi.txt", plasmidContigs, likelyPlasmidContigs)#***********************
     ToJson(rgiAMR, "rgi.json") #*************
 
-    carbapenamases = []
+    carbapenamases = [] 
+    resfinderCarbas = [] #list of rfinder objects for lindaout list
     amrGenes = []
     for keys in rFinder:
         carbapenamases.append(rFinder[keys].shortGene + "(" + rFinder[keys].source + ")")
+        resfinderCarbas.append(rFinder[keys])
     for keys in rgiAMR:
-        if (rgiAMR[keys].Drug_Class.find("carbapenem") > -1):
+        if (rgiAMR[keys].Drug_Class.find("carbapenem") > -1 and rgiAMR[keys].AMR_Gene_Family.find("beta-lactamase") > -1):
             if (rgiAMR[keys].Best_Hit_ARO not in carbapenamases):
                 carbapenamases.append(rgiAMR[keys].Best_Hit_ARO+ "(" + rgiAMR[keys].source + ")")
         else:
@@ -598,7 +603,28 @@
     #TSV output
     lindaOut = []
     tsvOut = []
-    lindaOut.append("new\tID\tQUALITY\tExpected Species\tMLST Scheme\tSequence Type\tMLST_ALLELE_1\tMLST_ALLELE_2\tMLST_ALLELE_3\tMLST_ALLELE_4\tMLST_ALLELE_5\tMLST_ALLELE_6\tMLST_ALLELE_7\tSEROTYPE\tK_CAPSULE\tPLASMID_1_FAMILY\tPLASMID_1_BEST_MATCH\tPLASMID_1_COVERAGE\tPLASMID_1_SNVS_TO_BEST_MATCH\tPLASMID_1_CARBAPENEMASE\tPLASMID_1_INC_GROUP\tPLASMID_2_RFLP\tPLASMID_2_FAMILY\tPLASMID_2_BEST_MATCH\tPLASMID_2_COVERAGE\tPLASMID_2_SNVS_TO_BEST_MATCH\tPLASMID_2_CARBAPENEMASE\tPLASMID_2_INC_GROUP")
+    lindaOut.append("ID\tQUALITY\tExpected Species\tMLST Scheme\tSequence Type\tMLST_ALLELE_1\tMLST_ALLELE_2\tMLST_ALLELE_3\tMLST_ALLELE_4\tMLST_ALLELE_5\tMLST_ALLELE_6\tMLST_ALLELE_7\tSEROTYPE\tK_CAPSULE\tPLASMID_2_RFLP\tPLASMID_1_FAMILY\tPLASMID_1_BEST_MATCH\tPLASMID_1_COVERAGE\tPLASMID_1_SNVS_TO_BEST_MATCH\tPLASMID_1_CARBAPENEMASE\tPLASMID_1_INC_GROUP\tPLASMID_2_RFLP\tPLASMID_2_FAMILY\tPLASMID_2_BEST_MATCH\tPLASMID_2_COVERAGE\tPLASMID_2_SNVS_TO_BEST_MATCH\tPLASMID_2_CARBAPENEMASE\tPLASMID_2_INC_GROUP")
+    lindaTemp = ID + "\t" #id
+    lindaTemp += "\t" #quality
+    lindaTemp += expectedSpecies + "\t" #expected
+    lindaTemp += mlstHit.species + "\t" #mlstscheme
+    lindaTemp += str(mlstHit.seqType)  + "\t" #seq type
+    lindaTemp += "\t".join(mlstHit.scheme.split(";")) + "\t"#mlst alleles x 7
+    lindaTemp += "\t\t" #sero and kcap
+    
+    #resfinderCarbas
+    for carbs in resfinderCarbas:
+        if (carbs.source == "plasmid"): #
+            lindaTemp += "\t\t\t\t\t" #plasmid 1 rflp plasmid 1 family information. PLASMID_1_FAMILY\tPLASMID_1_BEST_MATCH\tPLASMID_1_COVERAGE\tPLASMID_1_SNVS_TO_BEST_MATCH
+            lindaTemp += carbs.shortGene + "\t" #found an carbapenase
+            contig = carbs.sequence[6:] #this is the contig number
+            for i in mSuite.keys():
+                if (str(mSuite[i].contig_num) == str(contig)): #found the right plasmid
+                    lindaTemp += mSuite[i].rep_type
+    lindaOut.append(lindaTemp)
+    out = open("summary.linda.tsv", 'w')
+    for item in lindaOut:
+        out.write("%s\n" % item)
 
     tsvOut.append("new\tID\tExpected Species\tMLST Species\tSequence Type\tMLST Scheme\tCarbapenem Resistance Genes\tOther AMR Genes\tTotal Plasmids\tPlasmids ID\tNum_Contigs\tPlasmid Length\tPlasmid RepType\tPlasmid Mobility\tNearest Reference\tDefinitely Plasmid Contigs\tLikely Plasmid Contigs")
     #start with ID