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Ich versuche, ein Heatmap-Diagramm mit dem ComplexHeatmap-Paket zu erstellen. Meine Tabelle besteht aus folgendenSo fügen Sie eine Achse in eine Heatmap ein
> str(X)
'data.frame': 513 obs. of 4 variables:
$ Dist : num 0 0.0122 0.0244 0.0366 0.0488 ...
$ Prob_0 vs 0: num NaN 0.238 0.53 0.712 0.802 ...
$ Prob_4 vs 0: num NaN 0.478 0.589 0.611 0.566 ...
$ Prob_4 vs 4: num NaN 1.38 1.47 1.55 1.63 ...
Die erste Spalte ist die Entfernung bei jeder folgenden Variable geschätzt wurde. Ich habe das ComplexHeatmap-Paket verwendet und es funktioniert wunderbar, ich transponiere die Daten (heutzutage verwende ich die rownames, weil es einfacher ist). Allerdings würde ich gerne die realen Entfernungswerte als untere Anmerkung in der Heatmap verwenden, aber nicht so, wie sie dargestellt werden. Ich möchte eine durchgehende Linie (wie eine Achse) hinzufügen, die das Intervall von Abständen zeigt (wie ein 0-10 Wertebereich). Ist das möglich?
Hier ist der Code, den ich verwendet:
ft <- X[,-1] #removes the first line
Heatmap(t(ft), col = colorRamp2(c(-(max(abs(data.frame(t(ft))), na.rm = TRUE)), 0, max(abs(data.frame(t(ft))), na.rm = TRUE)),
c("red", "white", "blue")),cluster_columns = FALSE,
heatmap_legend_param = list(title = "Std. Coeff."))
Die Lösung ist nicht auf das ComplexHeatmap Paket beschränkt. Ich würde auch die Lösung für ein anderes Paket akzeptieren.
Edited:
Wie thisisrg erforderlich Ich werde die dput meiner Tabelle hinzufügen
X <- structure(list(Dist = c(0, 0.01220703125, 0.0244140625, 0.03662109375,
0.048828125, 0.06103515625, 0.0732421875, 0.08544921875, 0.09765625,
0.10986328125, 0.1220703125, 0.13427734375, 0.146484375, 0.15869140625,
0.1708984375, 0.18310546875, 0.1953125, 0.20751953125, 0.2197265625,
0.23193359375, 0.244140625, 0.25634765625, 0.2685546875, 0.28076171875,
0.29296875, 0.30517578125, 0.3173828125, 0.32958984375, 0.341796875,
0.35400390625, 0.3662109375, 0.37841796875, 0.390625, 0.40283203125,
0.4150390625, 0.42724609375, 0.439453125, 0.45166015625, 0.4638671875,
0.47607421875, 0.48828125, 0.50048828125, 0.5126953125, 0.52490234375,
0.537109375, 0.54931640625, 0.5615234375, 0.57373046875, 0.5859375,
0.59814453125, 0.6103515625, 0.62255859375, 0.634765625, 0.64697265625,
0.6591796875, 0.67138671875, 0.68359375, 0.69580078125, 0.7080078125,
0.72021484375, 0.732421875, 0.74462890625, 0.7568359375, 0.76904296875,
0.78125, 0.79345703125, 0.8056640625, 0.81787109375, 0.830078125,
0.84228515625, 0.8544921875, 0.86669921875, 0.87890625, 0.89111328125,
0.9033203125, 0.91552734375, 0.927734375, 0.93994140625, 0.9521484375,
0.96435546875, 0.9765625, 0.98876953125, 1.0009765625, 1.01318359375,
1.025390625, 1.03759765625, 1.0498046875, 1.06201171875, 1.07421875,
1.08642578125, 1.0986328125, 1.11083984375, 1.123046875, 1.13525390625,
1.1474609375, 1.15966796875, 1.171875, 1.18408203125, 1.1962890625,
1.20849609375, 1.220703125, 1.23291015625, 1.2451171875, 1.25732421875,
1.26953125, 1.28173828125, 1.2939453125, 1.30615234375, 1.318359375,
1.33056640625, 1.3427734375, 1.35498046875, 1.3671875, 1.37939453125,
1.3916015625, 1.40380859375, 1.416015625, 1.42822265625, 1.4404296875,
1.45263671875, 1.46484375, 1.47705078125, 1.4892578125, 1.50146484375,
1.513671875, 1.52587890625, 1.5380859375, 1.55029296875, 1.5625,
1.57470703125, 1.5869140625, 1.59912109375, 1.611328125, 1.62353515625,
1.6357421875, 1.64794921875, 1.66015625, 1.67236328125, 1.6845703125,
1.69677734375, 1.708984375, 1.72119140625, 1.7333984375, 1.74560546875,
1.7578125, 1.77001953125, 1.7822265625, 1.79443359375, 1.806640625,
1.81884765625, 1.8310546875, 1.84326171875, 1.85546875, 1.86767578125,
1.8798828125, 1.89208984375, 1.904296875, 1.91650390625, 1.9287109375,
1.94091796875, 1.953125, 1.96533203125, 1.9775390625, 1.98974609375,
2.001953125, 2.01416015625, 2.0263671875, 2.03857421875, 2.05078125,
2.06298828125, 2.0751953125, 2.08740234375, 2.099609375, 2.11181640625,
2.1240234375, 2.13623046875, 2.1484375, 2.16064453125, 2.1728515625,
2.18505859375, 2.197265625, 2.20947265625, 2.2216796875, 2.23388671875,
2.24609375, 2.25830078125, 2.2705078125, 2.28271484375, 2.294921875,
2.30712890625, 2.3193359375, 2.33154296875, 2.34375, 2.35595703125,
2.3681640625, 2.38037109375, 2.392578125, 2.40478515625, 2.4169921875,
2.42919921875, 2.44140625, 2.45361328125, 2.4658203125, 2.47802734375,
2.490234375, 2.50244140625, 2.5146484375, 2.52685546875, 2.5390625,
2.55126953125, 2.5634765625, 2.57568359375, 2.587890625, 2.60009765625,
2.6123046875, 2.62451171875, 2.63671875, 2.64892578125, 2.6611328125,
2.67333984375, 2.685546875, 2.69775390625, 2.7099609375, 2.72216796875,
2.734375, 2.74658203125, 2.7587890625, 2.77099609375, 2.783203125,
2.79541015625, 2.8076171875, 2.81982421875, 2.83203125, 2.84423828125,
2.8564453125, 2.86865234375, 2.880859375, 2.89306640625, 2.9052734375,
2.91748046875, 2.9296875, 2.94189453125, 2.9541015625, 2.96630859375,
2.978515625, 2.99072265625, 3.0029296875, 3.01513671875, 3.02734375,
3.03955078125, 3.0517578125, 3.06396484375, 3.076171875, 3.08837890625,
3.1005859375, 3.11279296875, 3.125, 3.13720703125, 3.1494140625,
3.16162109375, 3.173828125, 3.18603515625, 3.1982421875, 3.21044921875,
3.22265625, 3.23486328125, 3.2470703125, 3.25927734375, 3.271484375,
3.28369140625, 3.2958984375, 3.30810546875, 3.3203125, 3.33251953125,
3.3447265625, 3.35693359375, 3.369140625, 3.38134765625, 3.3935546875,
3.40576171875, 3.41796875, 3.43017578125, 3.4423828125, 3.45458984375,
3.466796875, 3.47900390625, 3.4912109375, 3.50341796875, 3.515625,
3.52783203125, 3.5400390625, 3.55224609375, 3.564453125, 3.57666015625,
3.5888671875, 3.60107421875, 3.61328125, 3.62548828125, 3.6376953125,
3.64990234375), `Prob_0 vs 0` = c(NaN, 0.237576420544701, 0.530243745611471,
0.712131719708788, 0.802271955686006, 0.813756100443225, 0.9227537054007,
1.13350585109593, 1.43349058067932, 1.78945709095286, 2.06095184683552,
2.2273963944522, 2.360212814586, 2.49808638550077, 2.54474369482735,
2.55292644989474, 2.62127842108026, 2.77283212106261, 2.96510939846837,
3.13535124706203, 3.30213097411516, 3.37630464370054, 3.35222203455243,
3.2714299353741, 3.33627708538652, 3.49176465027504, 3.5540603339226,
3.75250787652294, 3.91827782842129, 4.0044070913819, 4.08976492047229,
4.20375657992172, 4.31700924667487, 4.42566202147765, 4.44440076962983,
4.56082436897128, 4.72557926865402, 4.8740331806815, 5.00441636073648,
5.02062090967459, 4.96632870502554, 4.96772839556676, 5.07092080591646,
5.2313643833741, 5.32685592803999, 5.41766215746194, 5.44441764167056,
5.43606362140635, 5.411902474122, 5.51001879144363, 5.53935683201949,
5.51328527571126, 5.43982875047105, 5.44962004122367, 5.4543599702636,
5.33953065199409, 5.19967721754027, 5.08767333677512, 4.92863575797286,
4.75434216240437, 4.69579038226983, 4.70307840733031, 4.57422895104066,
4.4620642311161, 4.35307162836119, 4.32321117114019, 4.36581921785176,
4.43898474437526, 4.51676237748074, 4.58619818971311, 4.58969256320526,
4.73173779187246, 4.89265812606088, 4.99750494755418, 5.14412455064222,
5.31250854543885, 5.49535711142462, 5.72337528501464, 5.9495580972485,
6.15744565152309, 6.15928281609593, 6.13768803214605, 6.24658524021035,
6.4473325589996, 6.62622074786493, 6.86699964962475, 7.01602432570131,
7.04301998100178, 6.98735893391799, 6.94446513941456, 6.9753044467289,
6.87969341833369, 6.7039510131255, 6.58267869135413, 6.44898283558379,
6.24428619306375, 5.96897002113917, 5.68230081578111, 5.36787409068825,
5.03580956233143, 4.73749750278834, 4.57596584593804, 4.47271878316157,
4.30510167803549, 4.12027437262511, 4.01284715436542, 3.95817117397236,
4.00326257852433, 4.07690344768176, 4.09407841463112, 4.12515581185398,
4.24215809829794, 4.32809205688012, 4.34240005184899, 4.34123505839222,
4.39807932705815, 4.38844664234205, 4.45061150792117, 4.65164012222767,
4.87067077563656, 5.01419492945936, 5.02718999628037, 5.0129396678448,
5.05513659196026, 5.13086135099235, 5.18029901993765, 5.28836584159578,
5.31699535509692, 5.32601617300431, 5.34475147530333, 5.37158528502475,
5.48173294865045, 5.48833224088715, 5.47175200270752, 5.56063321340602,
5.58024801256755, 5.57279692717146, 5.57533414154514, 5.53351681792857,
5.43705109320126, 5.42202080052863, 5.5023613647921, 5.58355856606389,
5.5719210796375, 5.57229377578397, 5.53991450429585, 5.47968310754111,
5.52274738577026, 5.57685355250361, 5.63214664455547, 5.65677893337438,
5.73224889796731, 5.99936233861073, 6.24679969408281, 6.43985878262727,
6.51972384327445, 6.49350318842942, 6.43018559707729, 6.42478898892372,
6.506193188021, 6.62865926349153, 6.57360912592453, 6.42389326567735,
6.28202145157725, 6.20632766414902, 6.09396911193412, 6.0226863932659,
6.00625647490843, 5.91973889558252, 5.81238152369007, 5.77619193660644,
5.64645119183251, 5.50151310999086, 5.35307557495697, 5.29900724815286,
5.29600565877108, 5.35479867091857, 5.38204237079873, 5.35612345465627,
5.19181892815486, 5.13619465603709, 5.20931643323833, 5.24579326821275,
5.31493278463207, 5.35077079297442, 5.33075318977146, 5.259377420969,
5.17409634087382, 5.351622602699, 5.51295858534917, 5.5882698087635,
5.54832922756616, 5.56344896636778, 5.60192056575074, 5.5671784523359,
5.48254022592186, 5.4894950757978, 5.37064029303164, 5.19069581395775,
5.05079303599233, 4.92947445795189, 4.76883820732186, 4.57677894419868,
4.34579136896423, 4.16545601241833, 3.99936103873175, 3.87868937704688,
3.67712924824816, 3.46986190010122, 3.28027868099765, 3.1645778909222,
3.08210624078864, 2.96943610874946, 2.83415082957585, 2.71295790918139,
2.574872527898, 2.56130620876291, 2.63934245429256, 2.70847015054856,
2.73065389222475, 2.66699979442995, 2.65668873380784, 2.74476180854439,
2.76356764280366, 2.93087053849981, 3.06524245728706, 3.13595430936636,
3.14862518021699, 3.17086661973146, 3.30729040097112, 3.40846072897391,
3.4436398443871, 3.60484104144658, 3.8185230179118, 4.02072029592777,
4.15814878283129, 4.25896516446361, 4.32471484146874, 4.32109756504036,
4.27227278546762, 4.26607087553645, 4.18018265913158, 4.07315277006633,
3.89162806524799, 3.71912098354144, 3.55955180643683, 3.37271915496058,
3.19019410752165, 2.99466582188851, 2.77867675219537, 2.63794279062893,
2.54812047113694, 2.4559485493108, 2.33786970668933, 2.23482818875559,
2.15058001979509, 2.05386335667065, 2.00313636035246, 2.06068374289317,
2.01137842596851, 1.8880880493917, 1.74441283310472, 1.68116868553537,
1.60683006861109, 1.4935675136126, 1.54858112096455, 1.61989202309324,
1.61860166577077, 1.64081500171071, 1.68829329024331, 1.7489812778711,
1.79525477958204, 1.82242439448046, 1.99882914054592, 2.21050673908558,
2.34190406817834, 2.42554046859403, 2.40003353632323, 2.3878314749601,
2.41180766976115, 2.45348721202242, 2.55077591978968, 2.57223921674726,
2.55142651225624, 2.50780720036314, 2.43688529960885, 2.44695847274735,
2.53893568496856, 2.6022640809884, 2.67985683500395, 2.77833367204192,
2.90600967282694, 2.99544085801814, 3.00031686100334, 3.01318649496748,
3.04978626765603, 3.06199037701806, 3.1368326522569, 3.20699888665,
3.24241891399719), `Prob_4 vs 0` = c(NaN, 0.477792133571875,
0.588927152046119, 0.610721048165817, 0.565972160023058, 0.478172957982378,
0.414480476524951, 0.404447721771221, 0.425196754380851, 0.435268339639429,
0.398727128735965, 0.31207604280227, 0.228815034061013, 0.190514449735361,
0.106673211890841, -0.00404426795890488, -0.083193938438331,
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2.28586088375826, 2.20381278940513, 2.07403870517872, 1.95289948209375,
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0.86722269878929, 0.935667138481236, 0.977733491461596, 1.06057174686387,
1.17501083568156, 1.24432404758934, 1.24443615182021, 1.16682967589736,
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0.519116017612548, 0.520229873255494, 0.625792300345416, 0.732620897116329,
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"Prob_4 vs 0", "Prob_4 vs 4"), row.names = c(NA, 300L), class = "data.frame")
Ich denke, das ist die ComplexHeatmap (BioConductor) Paket. – thisisrg
Sie haben Recht, ich werde die Informationen bearbeiten –
Mit dem tatsächlichen Abstand meinst du Werte in Dist-Spalte? – thisisrg