CloneSet50


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Clone
Mass
Clones in
CloneSet
Parameter
Count
Clone
Similarity
Syntax Category
[Sequence Length]
41140.966or_test
Clone AbstractionParameter Bindings
Clone Instance
(Click to see clone)
Line CountSource Line
Source File
14202
Bio/Align/Applications/_Mafft.py
2470
Bio/Align/Applications/_Muscle.py
3478
Bio/Align/Applications/_Muscle.py
45102
Bio/Align/Applications/_Muscle.py
55113
Bio/Align/Applications/_Muscle.py
65222
Bio/Align/Applications/_Muscle.py
75228
Bio/Align/Applications/_Muscle.py
85237
Bio/Align/Applications/_Muscle.py
95245
Bio/Align/Applications/_Muscle.py
105291
Bio/Align/Applications/_Muscle.py
115314
Bio/Align/Applications/_Muscle.py
Clone Instance
1
Line Count
4
Source Line
202
Source File
Bio/Align/Applications/_Mafft.py

            #BLOSUM number matrix (Henikoff and Henikoff 1992) is used.
            #number=30, 45, 62 or 80. Default: 62
            _Option(["--bl","bl"],["input"],
                    lambda x:x in BLOSUM_MATRICES,0,"BLOSUM number matrix is used. Default: 62",0)


Clone Instance
2
Line Count
4
Source Line
70
Source File
Bio/Align/Applications/_Muscle.py

            #cluster1        upgma                upgmb              Clustering method.
            _Option(["-cluster1","cluster1"],["input"],
                    lambda x:x in CLUSTERING_ALGORITHMS,0,"Clustering method used in iteration 1",0)


Clone Instance
3
Line Count
4
Source Line
78
Source File
Bio/Align/Applications/_Muscle.py

            #cluster2        upgmb                                   cluster1 is used in
            #                neighborjoining                         iteration 1 and 2,
            #                                                        cluster2 in later
            #                                                        iterations.
            _Option(["-cluster2","cluster2"],["input"],
                    lambda x:x in CLUSTERING_ALGORITHMS,0,"Clustering method used in iteration 2",0)


Clone Instance
4
Line Count
5
Source Line
102
Source File
Bio/Align/Applications/_Muscle.py

            #distance1       kmer6_6              Kmer6_6 (amino) or Distance measure for
            #                kmer20_3             Kmer4_6 (nucleo)   iteration 1.
            #                kmer20_4
            #                kbit20_3
            #                kmer4_6
            _Option(["-distance1","distance1"],["input"],
                    lambda x:x in DISTANCE_MEASURES_ITER1,0,"Distance measure for iteration 1",0)


Clone Instance
5
Line Count
5
Source Line
113
Source File
Bio/Align/Applications/_Muscle.py

            #distance2       kmer6_6              pctid_kimura       Distance measure for
            #                kmer20_3                                iterations 2, 3 ...
            #                kmer20_4
            #                kbit20_3
            #                pctid_kimura
            #                pctid_log
            _Option(["-distance2","distance2"],["input"],
                    lambda x:x in DISTANCE_MEASURES_ITER2,0,"Distance measure for iteration 2",0)


Clone Instance
6
Line Count
5
Source Line
222
Source File
Bio/Align/Applications/_Muscle.py

            #objscore        sp                   spm                Objective score used by
            #                ps                                      tree dependent
            #                dp                                      refinement.
            #                xp                                      sp=sum-of-pairs score.
            #                spf                                     spf=sum-of-pairs score
            #                spm                                     (dimer approximation)
            #                                                        spm=sp for < 100 seqs,
            #                                                        otherwise spf
            #                                                        dp=dynamic programming
            #                                                        score.
            #                                                        ps=average profile-
            #                                                        sequence score.
            #                                                        xp=cross profile score.
            _Option(["-objscore","objscore"],["input"],
                    lambda x:x in OBJECTIVE_SCORES,0,"Objective score used by tree dependent refinement",0)


Clone Instance
7
Line Count
5
Source Line
228
Source File
Bio/Align/Applications/_Muscle.py

            #root1           pseudo               psuedo             Method used to root
            _Option(["-root1","root1"],["input"],
                    lambda x:x in TREE_ROOT_METHODS,0,"Method used to root tree in iteration 1",0)


Clone Instance
8
Line Count
5
Source Line
237
Source File
Bio/Align/Applications/_Muscle.py

            #root2           midlongestspan                          tree; root1 is used in
            #                minavgleafdist                          iteration 1 and 2,
            #                                                        root2 in later
            #                                                        iterations.
            _Option(["-root2","root2"],["input"],
                    lambda x:x in TREE_ROOT_METHODS,0,"Method used to root tree in iteration 2",0)


Clone Instance
9
Line Count
5
Source Line
245
Source File
Bio/Align/Applications/_Muscle.py

            #seqtype         protein              auto               Sequence type.
            #                nucleo
            #                auto
            _Option(["-seqtype","seqtype"],["input"],
                    lambda x:x in SEQUENCE_TYPES,0,"Sequence type",0)


Clone Instance
10
Line Count
5
Source Line
291
Source File
Bio/Align/Applications/_Muscle.py

            #weight1         none                 clustalw           Sequence weighting
            _Option(["-weight1","weight1"],["input"],
                    lambda x:x in WEIGHTING_SCHEMES,0,"Weighting scheme used in iteration 1",0)


Clone Instance
11
Line Count
5
Source Line
314
Source File
Bio/Align/Applications/_Muscle.py

            #weight2         henikoff                                scheme.
            #                henikoffpb                              weight1 is used in
            #                gsc                                     iterations 1 and 2.
            #                clustalw                                weight2 is used for
            #                threeway                                tree-dependent
            #                                                        refinement.
            #                                                        none=all sequences have
            #                                                        equal weight.
            #                                                        henikoff=Henikoff &
            #                                                        Henikoff weighting
            #                                                        scheme.
            #                                                        henikoffpb=Modified
            #                                                        Henikoff scheme as used
            #                                                        in PSI-BLAST.
            #                                                        clustalw=CLUSTALW
            #                                                        method.
            #                                                        threeway=Gotoh three-
            #                                                        way method.
            _Option(["-weight2","weight2"],["input"],
                    lambda x:x in WEIGHTING_SCHEMES,0,"Weighting scheme used in iteration 2",0)


Clone AbstractionParameter Count: 4Parameter Bindings

#BLOSUM number matrix (Henikoff and Henikoff 1992) is used.
#number=30, 45, 62 or 80. Default: 62
#weight2         henikoff                                scheme.
#                henikoffpb                              weight1 is used in
#                gsc                                     iterations 1 and 2.
#                clustalw                                weight2 is used for
#                threeway                                tree-dependent
#                                                        refinement.
#                                                        none=all sequences have
#                                                        equal weight.
#                                                        henikoff=Henikoff &
#                                                        Henikoff weighting
#                                                        scheme.
#                                                        henikoffpb=Modified
#                                                        Henikoff scheme as used
#                                                        in PSI-BLAST.
#                                                        clustalw=CLUSTALW
#                                                        method.
#                                                        threeway=Gotoh three-
#                                                        way method.
#weight1         none                 clustalw           Sequence weighting
#seqtype         protein              auto               Sequence type.
#                nucleo
#                auto
#root2           midlongestspan                          tree; root1 is used in
#                minavgleafdist                          iteration 1 and 2,
#                                                        root2 in later
#cluster2        upgmb                                   cluster1 is used in
#                neighborjoining                         iteration 1 and 2,
#                                                        cluster2 in later
#                                                        iterations.
#root1           pseudo               psuedo             Method used to root
#objscore        sp                   spm                Objective score used by
#                ps                                      tree dependent
#                dp                                      refinement.
#                xp                                      sp=sum-of-pairs score.
#                spf                                     spf=sum-of-pairs score
#                spm                                     (dimer approximation)
#                                                        spm=sp for < 100 seqs,
#                                                        otherwise spf
#                                                        dp=dynamic programming
#                                                        score.
#                                                        ps=average profile-
#                                                        sequence score.
#                                                        xp=cross profile score.
#distance2       kmer6_6              pctid_kimura       Distance measure for
#                kmer20_3                                iterations 2, 3 ...
#distance1       kmer6_6              Kmer6_6 (amino) or Distance measure for
#                kmer20_3             Kmer4_6 (nucleo)   iteration 1.
#                kmer20_4
#                kbit20_3
#                pctid_kimura
#                pctid_log
#                kmer4_6
#cluster1        upgma                upgmb              Clustering method.
_Option([ [[#variable5f9ec800]], [[#variable5f9ec7a0]]],["input"], lambda x:x in [[#variable5f9ec740]],0, [[#variable5f9ec6a0]],0)
 

CloneAbstraction
Parameter Bindings
Parameter
Index
Clone
Instance
Parameter
Name
Value
11[[#5f9ec800]]
"--bl" 
12[[#5f9ec800]]
"-weight2" 
13[[#5f9ec800]]
"-weight1" 
14[[#5f9ec800]]
"-seqtype" 
15[[#5f9ec800]]
"-root2" 
16[[#5f9ec800]]
"-root1" 
17[[#5f9ec800]]
"-objscore" 
18[[#5f9ec800]]
"-distance2" 
19[[#5f9ec800]]
"-distance1" 
110[[#5f9ec800]]
"-cluster2" 
111[[#5f9ec800]]
"-cluster1" 
21[[#5f9ec7a0]]
"bl" 
22[[#5f9ec7a0]]
"weight2" 
23[[#5f9ec7a0]]
"weight1" 
24[[#5f9ec7a0]]
"seqtype" 
25[[#5f9ec7a0]]
"root2" 
26[[#5f9ec7a0]]
"root1" 
27[[#5f9ec7a0]]
"objscore" 
28[[#5f9ec7a0]]
"distance2" 
29[[#5f9ec7a0]]
"distance1" 
210[[#5f9ec7a0]]
"cluster2" 
211[[#5f9ec7a0]]
"cluster1" 
31[[#5f9ec740]]
BLOSUM_MATRICES 
32[[#5f9ec740]]
WEIGHTING_SCHEMES 
33[[#5f9ec740]]
WEIGHTING_SCHEMES 
34[[#5f9ec740]]
SEQUENCE_TYPES 
35[[#5f9ec740]]
TREE_ROOT_METHODS 
36[[#5f9ec740]]
TREE_ROOT_METHODS 
37[[#5f9ec740]]
OBJECTIVE_SCORES 
38[[#5f9ec740]]
DISTANCE_MEASURES_ITER2 
39[[#5f9ec740]]
DISTANCE_MEASURES_ITER1 
310[[#5f9ec740]]
CLUSTERING_ALGORITHMS 
311[[#5f9ec740]]
CLUSTERING_ALGORITHMS 
41[[#5f9ec6a0]]
"BLOSUM number matrix is used. Default: 62" 
42[[#5f9ec6a0]]
"Weighting scheme used in iteration 2" 
43[[#5f9ec6a0]]
"Weighting scheme used in iteration 1" 
44[[#5f9ec6a0]]
"Sequence type" 
45[[#5f9ec6a0]]
"Method used to root tree in iteration 2" 
46[[#5f9ec6a0]]
"Method used to root tree in iteration 1" 
47[[#5f9ec6a0]]
"Objective score used by tree dependent refinement" 
48[[#5f9ec6a0]]
"Distance measure for iteration 2" 
49[[#5f9ec6a0]]
"Distance measure for iteration 1" 
410[[#5f9ec6a0]]
"Clustering method used in iteration 2" 
411[[#5f9ec6a0]]
"Clustering method used in iteration 1"