tests/testQuality.R
In neobernad/evaluomeR: Evaluation of Bioinformatics Metrics
library(evaluomeR)
library(RSKC)
library(sparcl)
dataFrame <- quality(data=ontMetrics, cbi="kmeans", k=3)
assay(dataFrame)
# Metric Cluster_1_SilScore Cluster_2_SilScore Cluster_3_SilScore Avg_Silhouette_Width Cluster_1_Size Cluster_2_Size Cluster_3_Size
# [1,] "ANOnto" "0.754894925204277" "0.570241066303214" "0.775876285585267" "0.736742918153759" "12" "14" "54"
# [2,] "AROnto" "0.837074497995987" "0.509946991883709" "0.959264389073384" "0.786971025529677" "65" "13" "2"
# [3,] "CBOOnto" "0.766630500367533" "0.574451527320666" "0.470708665744913" "0.72319889705568" "63" "15" "2"
# [4,] "CBOOnto2" "0.766630500367533" "0.574451527320666" "0.470708665744913" "0.72319889705568" "63" "15" "2"
# [5,] "CROnto" "0.885055456924709" "0.636126752920544" "0" "0.855322610912838" "73" "6" "1"
# [6,] "DITOnto" "0.615581638093901" "0.441137593941046" "0.746848044839846" "0.553468450386794" "41" "33" "6"
# [7,] "INROnto" "0.760945813444805" "0.506239463726949" "0" "0.690941232718754" "60" "19" "1"
# [8,] "LCOMOnto" "0.657281417643165" "0.61764525421598" "0.722333227599342" "0.652913140794165" "21" "40" "19"
# [9,] "NACOnto" "0.759522276872854" "0.445845264823784" "0.254826579985626" "0.661322430756974" "58" "17" "5"
# [10,] "NOCOnto" "0.898396530127955" "0.742673517080307" "0.363472944618239" "0.879183827500925" "75" "3" "2"
# [11,] "NOMOnto" "0.708789049998754" "0.605603643727872" "0" "0.668973564992505" "55" "24" "1"
# [12,] "POnto" "0.755700546488043" "0.737169134813343" "0.651090644844594" "0.67661537075347" "8" "14" "58"
# [13,] "PROnto" "0.770018889790615" "0.56606585120985" "0.636058646833202" "0.668644905329162" "32" "24" "24"
# [14,] "RFCOnto" "0.672903800663584" "0.571360647044581" "0" "0.635298846489826" "56" "23" "1"
# [15,] "RROnto" "0.636058646833202" "0.56606585120985" "0.770018889790615" "0.668644905329162" "24" "24" "32"
# [16,] "TMOnto" "0.782948726523096" "0.50860642260504" "0.634534477835837" "0.710090639489989" "56" "18" "6"
# [17,] "TMOnto2" "1" "0.73737171744016" "0.462679160671249" "0.724657891719511" "16" "45" "19"
# [18,] "WMCOnto" "0.868556472442156" "0.369670756071292" "0.763547528087877" "0.828514820105485" "72" "6" "2"
# [19,] "WMCOnto2" "0.891854974826074" "0.598522433823083" "0.613618761016468" "0.870232442430684" "74" "4" "2"
dataFrame <- quality(data=ontMetrics, cbi="kmeans", k=4)
assay(dataFrame)
# Metric Cluster_1_SilScore Cluster_2_SilScore Cluster_3_SilScore Cluster_4_SilScore Avg_Silhouette_Width Cluster_1_Size Cluster_2_Size Cluster_3_Size Cluster_4_Size
# [1,] "ANOnto" "0.717030499002753" "0.569222510427433" "0.552363239306396" "0.584449669565973" "0.600638738086962" "12" "11" "4" "53"
# [2,] "AROnto" "0.891757427020894" "0.614385150712436" "0.498602630835942" "0.953766280221553" "0.813833608784603" "58" "13" "7" "2"
# [3,] "CBOOnto" "0.682847685112873" "0.475694878561971" "0.418096612044278" "0.462053414220223" "0.5843870090796" "46" "18" "14" "2"
# [4,] "CBOOnto2" "0.682847685112873" "0.475694878561971" "0.418096612044278" "0.462053414220223" "0.5843870090796" "46" "18" "14" "2"
# [5,] "CROnto" "0.931552645421743" "0.615016966742524" "0.460688748724164" "0" "0.84502648526675" "63" "10" "6" "1"
# [6,] "DITOnto" "0.621392145232729" "0.589638237470761" "0.512852920317478" "0.717462336796908" "0.582143307479606" "15" "35" "24" "6"
# [7,] "INROnto" "0.679354776901229" "0.514845315378322" "0.552323396139528" "0" "0.609561353444975" "46" "19" "14" "1"
# [8,] "LCOMOnto" "0.563584714383498" "0.565734453969461" "0.526937877760086" "0.662861247621334" "0.57713748864992" "19" "19" "23" "19"
# [9,] "NACOnto" "0.763008703189753" "0.507554700154524" "0.610806402578204" "0.0693863149967116" "0.627188990478616" "42" "23" "10" "5"
# [10,] "NOCOnto" "0.712806750183687" "0.368068489789737" "0.711626648649838" "0.363472944618239" "0.600607673118847" "51" "24" "3" "2"
# [11,] "NOMOnto" "0.796568957921031" "0.487448631370323" "0.505810544669573" "0" "0.620956620752701" "35" "25" "19" "1"
# [12,] "POnto" "0.755700546488043" "0.717551583859045" "0.702605079149018" "0.531828315626997" "0.676374911502771" "8" "14" "42" "16"
# [13,] "PROnto" "0.808419016380534" "0.406920889282586" "0.546429726628472" "0.636912857924547" "0.623564355956028" "22" "12" "23" "23"
# [14,] "RFCOnto" "0.708660103503223" "0.527891770926241" "0.575667190561062" "0" "0.613856368788046" "37" "27" "15" "1"
# [15,] "RROnto" "0.636912857924547" "0.546429726628472" "0.406920889282586" "0.808419016380534" "0.623564355956028" "23" "23" "12" "22"
# [16,] "TMOnto" "0.772548576303018" "0.527581279093128" "0.56435245544769" "0.756878515673905" "0.694408411158545" "48" "15" "12" "5"
# [17,] "TMOnto2" "1" "0.709314170957853" "0.593309463294573" "0.516092763511662" "0.725408613137789" "16" "39" "19" "6"
# [18,] "WMCOnto" "0.811550829534933" "0.517887706724764" "0.232935788267106" "0.751527957476758" "0.737070037248562" "62" "12" "4" "2"
# [19,] "WMCOnto2" "0.806794961402285" "0.458575230569131" "0.48724511207104" "0.613618761016468" "0.72940235766569" "61" "13" "4" "2"
dataFrame <- qualityRange(data=ontMetrics, cbi="kmeans", k.range = c(3,4))
assay(dataFrame$k_4)
# Metric Cluster_1_SilScore Cluster_2_SilScore Cluster_3_SilScore Cluster_4_SilScore Avg_Silhouette_Width Cluster_1_Size Cluster_2_Size Cluster_3_Size Cluster_4_Size
# 1 "ANOnto" "0.569222510427433" "0.552363239306396" "0.584449669565973" "0.717030499002753" "0.600638738086962" "11" "4" "53" "12"
# 2 "AROnto" "0.891757427020894" "0.498602630835942" "0.953766280221553" "0.614385150712436" "0.813833608784603" "58" "7" "2" "13"
# 3 "CBOOnto" "0.682847685112873" "0.475694878561971" "0.418096612044278" "0.462053414220223" "0.5843870090796" "46" "18" "14" "2"
# 4 "CBOOnto2" "0.682847685112873" "0.475694878561971" "0.418096612044278" "0.462053414220223" "0.5843870090796" "46" "18" "14" "2"
# 5 "CROnto" "0.615016966742524" "0.931552645421743" "0.460688748724164" "0" "0.84502648526675" "10" "63" "6" "1"
# 6 "DITOnto" "0.621392145232729" "0.589638237470761" "0.512852920317478" "0.717462336796908" "0.582143307479606" "15" "35" "24" "6"
# 7 "INROnto" "0.679354776901229" "0.514845315378322" "0.552323396139528" "0" "0.609561353444975" "46" "19" "14" "1"
# 8 "LCOMOnto" "0.563584714383498" "0.565734453969461" "0.526937877760086" "0.662861247621334" "0.57713748864992" "19" "19" "23" "19"
# 9 "NACOnto" "0.507554700154524" "0.763008703189753" "0.0693863149967116" "0.610806402578204" "0.627188990478616" "23" "42" "5" "10"
# 10 "NOCOnto" "0.363472944618239" "0.712806750183687" "0.368068489789737" "0.711626648649838" "0.600607673118847" "2" "51" "24" "3"
# 11 "NOMOnto" "0.796568957921031" "0" "0.487448631370323" "0.505810544669573" "0.620956620752701" "35" "1" "25" "19"
# 12 "POnto" "0.717551583859045" "0.702605079149018" "0.531828315626997" "0.755700546488043" "0.676374911502771" "14" "42" "16" "8"
# 13 "PROnto" "0.808419016380534" "0.636912857924547" "0.406920889282586" "0.546429726628472" "0.623564355956028" "22" "23" "12" "23"
# 14 "RFCOnto" "0.708660103503223" "0" "0.527891770926241" "0.575667190561062" "0.613856368788046" "37" "1" "27" "15"
# 15 "RROnto" "0.808419016380534" "0.636912857924547" "0.406920889282586" "0.546429726628472" "0.623564355956028" "22" "23" "12" "23"
# 16 "TMOnto" "0.527581279093128" "0.772548576303018" "0.756878515673905" "0.56435245544769" "0.694408411158545" "15" "48" "5" "12"
# 17 "TMOnto2" "0.593309463294573" "1" "0.709314170957853" "0.516092763511662" "0.725408613137789" "19" "16" "39" "6"
# 18 "WMCOnto" "0.811550829534933" "0.517887706724764" "0.751527957476758" "0.232935788267106" "0.737070037248562" "62" "12" "2" "4"
# 19 "WMCOnto2" "0.48724511207104" "0.806794961402285" "0.613618761016468" "0.458575230569131" "0.72940235766569" "4" "61" "2" "13"
dataFrame <- qualityRange(data=ontMetrics, cbi="kmeans", k.range = c(3,4), all_metrics=TRUE, getImages = TRUE)
assay(dataFrame$k_3)
# Metric Cluster_1_SilScore Cluster_2_SilScore Cluster_3_SilScore Cluster_4_SilScore Avg_Silhouette_Width Cluster_1_Size Cluster_2_Size Cluster_3_Size Cluster_4_Size
# 1 "all_metrics" "0.560364615463509" "0.768006541644696" "0.761635263968552" "0.343459043619883" "0.730815149196402" "2" "70" "2" "6"
dataFrame <- quality(data=ontMetrics, cbi="kmeans", k=4, all_metrics=TRUE)
assay(dataFrame)
# Metric Cluster_1_SilScore Cluster_2_SilScore Cluster_3_SilScore Cluster_4_SilScore Avg_Silhouette_Width
# [1,] "all_metrics" "0.560364615463509" "0.768006541644696" "0.761635263968552" "0.343459043619883" "0.730815149196402"
# Cluster_1_Size Cluster_2_Size Cluster_3_Size Cluster_4_Size
# [1,] "2" "70" "2" "6"
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library(evaluomeR)
library(RSKC)
library(sparcl)
dataFrame <- quality(data=ontMetrics, cbi="kmeans", k=3)
assay(dataFrame)
# Metric Cluster_1_SilScore Cluster_2_SilScore Cluster_3_SilScore Avg_Silhouette_Width Cluster_1_Size Cluster_2_Size Cluster_3_Size
# [1,] "ANOnto" "0.754894925204277" "0.570241066303214" "0.775876285585267" "0.736742918153759" "12" "14" "54"
# [2,] "AROnto" "0.837074497995987" "0.509946991883709" "0.959264389073384" "0.786971025529677" "65" "13" "2"
# [3,] "CBOOnto" "0.766630500367533" "0.574451527320666" "0.470708665744913" "0.72319889705568" "63" "15" "2"
# [4,] "CBOOnto2" "0.766630500367533" "0.574451527320666" "0.470708665744913" "0.72319889705568" "63" "15" "2"
# [5,] "CROnto" "0.885055456924709" "0.636126752920544" "0" "0.855322610912838" "73" "6" "1"
# [6,] "DITOnto" "0.615581638093901" "0.441137593941046" "0.746848044839846" "0.553468450386794" "41" "33" "6"
# [7,] "INROnto" "0.760945813444805" "0.506239463726949" "0" "0.690941232718754" "60" "19" "1"
# [8,] "LCOMOnto" "0.657281417643165" "0.61764525421598" "0.722333227599342" "0.652913140794165" "21" "40" "19"
# [9,] "NACOnto" "0.759522276872854" "0.445845264823784" "0.254826579985626" "0.661322430756974" "58" "17" "5"
# [10,] "NOCOnto" "0.898396530127955" "0.742673517080307" "0.363472944618239" "0.879183827500925" "75" "3" "2"
# [11,] "NOMOnto" "0.708789049998754" "0.605603643727872" "0" "0.668973564992505" "55" "24" "1"
# [12,] "POnto" "0.755700546488043" "0.737169134813343" "0.651090644844594" "0.67661537075347" "8" "14" "58"
# [13,] "PROnto" "0.770018889790615" "0.56606585120985" "0.636058646833202" "0.668644905329162" "32" "24" "24"
# [14,] "RFCOnto" "0.672903800663584" "0.571360647044581" "0" "0.635298846489826" "56" "23" "1"
# [15,] "RROnto" "0.636058646833202" "0.56606585120985" "0.770018889790615" "0.668644905329162" "24" "24" "32"
# [16,] "TMOnto" "0.782948726523096" "0.50860642260504" "0.634534477835837" "0.710090639489989" "56" "18" "6"
# [17,] "TMOnto2" "1" "0.73737171744016" "0.462679160671249" "0.724657891719511" "16" "45" "19"
# [18,] "WMCOnto" "0.868556472442156" "0.369670756071292" "0.763547528087877" "0.828514820105485" "72" "6" "2"
# [19,] "WMCOnto2" "0.891854974826074" "0.598522433823083" "0.613618761016468" "0.870232442430684" "74" "4" "2"
dataFrame <- quality(data=ontMetrics, cbi="kmeans", k=4)
assay(dataFrame)
# Metric Cluster_1_SilScore Cluster_2_SilScore Cluster_3_SilScore Cluster_4_SilScore Avg_Silhouette_Width Cluster_1_Size Cluster_2_Size Cluster_3_Size Cluster_4_Size
# [1,] "ANOnto" "0.717030499002753" "0.569222510427433" "0.552363239306396" "0.584449669565973" "0.600638738086962" "12" "11" "4" "53"
# [2,] "AROnto" "0.891757427020894" "0.614385150712436" "0.498602630835942" "0.953766280221553" "0.813833608784603" "58" "13" "7" "2"
# [3,] "CBOOnto" "0.682847685112873" "0.475694878561971" "0.418096612044278" "0.462053414220223" "0.5843870090796" "46" "18" "14" "2"
# [4,] "CBOOnto2" "0.682847685112873" "0.475694878561971" "0.418096612044278" "0.462053414220223" "0.5843870090796" "46" "18" "14" "2"
# [5,] "CROnto" "0.931552645421743" "0.615016966742524" "0.460688748724164" "0" "0.84502648526675" "63" "10" "6" "1"
# [6,] "DITOnto" "0.621392145232729" "0.589638237470761" "0.512852920317478" "0.717462336796908" "0.582143307479606" "15" "35" "24" "6"
# [7,] "INROnto" "0.679354776901229" "0.514845315378322" "0.552323396139528" "0" "0.609561353444975" "46" "19" "14" "1"
# [8,] "LCOMOnto" "0.563584714383498" "0.565734453969461" "0.526937877760086" "0.662861247621334" "0.57713748864992" "19" "19" "23" "19"
# [9,] "NACOnto" "0.763008703189753" "0.507554700154524" "0.610806402578204" "0.0693863149967116" "0.627188990478616" "42" "23" "10" "5"
# [10,] "NOCOnto" "0.712806750183687" "0.368068489789737" "0.711626648649838" "0.363472944618239" "0.600607673118847" "51" "24" "3" "2"
# [11,] "NOMOnto" "0.796568957921031" "0.487448631370323" "0.505810544669573" "0" "0.620956620752701" "35" "25" "19" "1"
# [12,] "POnto" "0.755700546488043" "0.717551583859045" "0.702605079149018" "0.531828315626997" "0.676374911502771" "8" "14" "42" "16"
# [13,] "PROnto" "0.808419016380534" "0.406920889282586" "0.546429726628472" "0.636912857924547" "0.623564355956028" "22" "12" "23" "23"
# [14,] "RFCOnto" "0.708660103503223" "0.527891770926241" "0.575667190561062" "0" "0.613856368788046" "37" "27" "15" "1"
# [15,] "RROnto" "0.636912857924547" "0.546429726628472" "0.406920889282586" "0.808419016380534" "0.623564355956028" "23" "23" "12" "22"
# [16,] "TMOnto" "0.772548576303018" "0.527581279093128" "0.56435245544769" "0.756878515673905" "0.694408411158545" "48" "15" "12" "5"
# [17,] "TMOnto2" "1" "0.709314170957853" "0.593309463294573" "0.516092763511662" "0.725408613137789" "16" "39" "19" "6"
# [18,] "WMCOnto" "0.811550829534933" "0.517887706724764" "0.232935788267106" "0.751527957476758" "0.737070037248562" "62" "12" "4" "2"
# [19,] "WMCOnto2" "0.806794961402285" "0.458575230569131" "0.48724511207104" "0.613618761016468" "0.72940235766569" "61" "13" "4" "2"
dataFrame <- qualityRange(data=ontMetrics, cbi="kmeans", k.range = c(3,4))
assay(dataFrame$k_4)
# Metric Cluster_1_SilScore Cluster_2_SilScore Cluster_3_SilScore Cluster_4_SilScore Avg_Silhouette_Width Cluster_1_Size Cluster_2_Size Cluster_3_Size Cluster_4_Size
# 1 "ANOnto" "0.569222510427433" "0.552363239306396" "0.584449669565973" "0.717030499002753" "0.600638738086962" "11" "4" "53" "12"
# 2 "AROnto" "0.891757427020894" "0.498602630835942" "0.953766280221553" "0.614385150712436" "0.813833608784603" "58" "7" "2" "13"
# 3 "CBOOnto" "0.682847685112873" "0.475694878561971" "0.418096612044278" "0.462053414220223" "0.5843870090796" "46" "18" "14" "2"
# 4 "CBOOnto2" "0.682847685112873" "0.475694878561971" "0.418096612044278" "0.462053414220223" "0.5843870090796" "46" "18" "14" "2"
# 5 "CROnto" "0.615016966742524" "0.931552645421743" "0.460688748724164" "0" "0.84502648526675" "10" "63" "6" "1"
# 6 "DITOnto" "0.621392145232729" "0.589638237470761" "0.512852920317478" "0.717462336796908" "0.582143307479606" "15" "35" "24" "6"
# 7 "INROnto" "0.679354776901229" "0.514845315378322" "0.552323396139528" "0" "0.609561353444975" "46" "19" "14" "1"
# 8 "LCOMOnto" "0.563584714383498" "0.565734453969461" "0.526937877760086" "0.662861247621334" "0.57713748864992" "19" "19" "23" "19"
# 9 "NACOnto" "0.507554700154524" "0.763008703189753" "0.0693863149967116" "0.610806402578204" "0.627188990478616" "23" "42" "5" "10"
# 10 "NOCOnto" "0.363472944618239" "0.712806750183687" "0.368068489789737" "0.711626648649838" "0.600607673118847" "2" "51" "24" "3"
# 11 "NOMOnto" "0.796568957921031" "0" "0.487448631370323" "0.505810544669573" "0.620956620752701" "35" "1" "25" "19"
# 12 "POnto" "0.717551583859045" "0.702605079149018" "0.531828315626997" "0.755700546488043" "0.676374911502771" "14" "42" "16" "8"
# 13 "PROnto" "0.808419016380534" "0.636912857924547" "0.406920889282586" "0.546429726628472" "0.623564355956028" "22" "23" "12" "23"
# 14 "RFCOnto" "0.708660103503223" "0" "0.527891770926241" "0.575667190561062" "0.613856368788046" "37" "1" "27" "15"
# 15 "RROnto" "0.808419016380534" "0.636912857924547" "0.406920889282586" "0.546429726628472" "0.623564355956028" "22" "23" "12" "23"
# 16 "TMOnto" "0.527581279093128" "0.772548576303018" "0.756878515673905" "0.56435245544769" "0.694408411158545" "15" "48" "5" "12"
# 17 "TMOnto2" "0.593309463294573" "1" "0.709314170957853" "0.516092763511662" "0.725408613137789" "19" "16" "39" "6"
# 18 "WMCOnto" "0.811550829534933" "0.517887706724764" "0.751527957476758" "0.232935788267106" "0.737070037248562" "62" "12" "2" "4"
# 19 "WMCOnto2" "0.48724511207104" "0.806794961402285" "0.613618761016468" "0.458575230569131" "0.72940235766569" "4" "61" "2" "13"
dataFrame <- qualityRange(data=ontMetrics, cbi="kmeans", k.range = c(3,4), all_metrics=TRUE, getImages = TRUE)
assay(dataFrame$k_3)
# Metric Cluster_1_SilScore Cluster_2_SilScore Cluster_3_SilScore Cluster_4_SilScore Avg_Silhouette_Width Cluster_1_Size Cluster_2_Size Cluster_3_Size Cluster_4_Size
# 1 "all_metrics" "0.560364615463509" "0.768006541644696" "0.761635263968552" "0.343459043619883" "0.730815149196402" "2" "70" "2" "6"
dataFrame <- quality(data=ontMetrics, cbi="kmeans", k=4, all_metrics=TRUE)
assay(dataFrame)
# Metric Cluster_1_SilScore Cluster_2_SilScore Cluster_3_SilScore Cluster_4_SilScore Avg_Silhouette_Width
# [1,] "all_metrics" "0.560364615463509" "0.768006541644696" "0.761635263968552" "0.343459043619883" "0.730815149196402"
# Cluster_1_Size Cluster_2_Size Cluster_3_Size Cluster_4_Size
# [1,] "2" "70" "2" "6"
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