c("GO:0043484","regulation of RNA splicing", 0.006,-4.334, 4.564, 2.846,-1.9392,0.824,0.443),#
c("GO:0001700","", 0.003, 6.337,-3.379, 2.504,-1.0998,0.832,0.446),#
c("GO:0030721","", 0.000, 4.817, 6.552, 0.699,-1.6685,0.826,0.450),#
c("GO:0051129","", 0.045, 2.265, 7.425, 3.711,-1.8220,0.737,0.458),#
c("GO:0051340","", 0.003,-2.596, 6.152, 2.598,-2.3526,0.892,0.470),#
c("GO:0035152","", 0.001, 6.080, 0.005, 2.196,-2.7903,0.745,0.472),#
c("GO:0008340","", 0.009, 6.407,-3.413, 3.035,-1.6606,0.825,0.473),#
c("GO:0006085","", 0.004,-1.213,-1.643, 2.697,-2.2385,0.910,0.474),#
c("GO:0045478","", 0.000, 4.829, 6.460, 1.279,-1.6685,0.815,0.484),#
c("GO:0051591","", 0.005,-1.258, 0.746, 2.749,-1.7936,0.959,0.490),#
c("GO:0006213","", 0.201,-3.187,-4.297, 4.359,-1.4180,0.828,0.495),#
c("GO:0043433","", 0.009,-4.260, 4.614, 2.999,-1.0960,0.817,0.499),#
c("GO:0007276","", 0.062, 5.891,-4.046, 3.846,-1.4704,0.848,0.500),#
c("GO:0007444","", 0.009, 6.446,-3.405, 2.991,-1.7166,0.816,0.504),#
c("GO:0016044","", 0.166, 5.067, 6.954, 4.276,-1.6677,0.785,0.505),#
c("GO:0060047","", 0.013, 5.819,-3.867, 3.159,-1.1929,0.879,0.508),#
c("GO:0019953","", 0.086, 3.339,-2.209, 3.990,-1.0008,0.959,0.510),#
c("GO:0051084","", 0.014,-3.660,-0.386, 3.194,-1.0462,0.904,0.516),#
c("GO:0048754","", 0.021, 6.380,-3.373, 3.372,-1.3150,0.814,0.526),#
c("GO:0010927","", 0.019, 7.406, 2.247, 3.332,-1.1170,0.660,0.527),#
c("GO:0006413","", 0.337,-5.138, 0.300, 4.584,-1.7656,0.863,0.533),#
c("GO:0001763","", 0.026, 6.478,-3.423, 3.470,-1.3294,0.820,0.537),#
c("GO:0006412","translation", 4.967,-5.423, 0.276, 5.753,-5.2041,0.832,0.538),#
c("GO:0045429","", 0.004,-2.690, 5.902, 2.619,-1.0462,0.842,0.541),#
c("GO:0009992","", 0.000,-1.437, 6.111, 1.623,-1.6685,0.886,0.541),#
c("GO:0006112","", 0.129,-0.107,-1.299, 4.169,-1.8918,0.915,0.543),#
c("GO:0007016","", 0.002, 2.191, 7.245, 2.401,-3.1273,0.682,0.560),#
c("GO:0042692","", 0.034, 6.774,-3.330, 3.589,-2.5846,0.785,0.563),#
c("GO:0016052","", 1.399,-2.781,-2.512, 5.203,-5.3516,0.867,0.564),#
c("GO:0035317","", 0.001, 7.750, 1.636, 2.004,-1.9392,0.666,0.567),#
c("GO:0051235","", 0.032,-1.949, 6.873, 3.556,-1.9771,0.861,0.584),#
c("GO:0005977","", 0.128,-2.440,-1.665, 4.164,-1.8918,0.840,0.589),#
c("GO:0043933","", 1.085, 4.880, 6.508, 5.092,-2.5019,0.781,0.593),#
c("GO:0042775","", 0.315,-0.424,-1.022, 4.555,-2.1471,0.906,0.598),#
c("GO:0044042","", 0.249,-2.591,-1.536, 4.452,-1.3150,0.900,0.600),#
c("GO:0000302","response to reactive oxygen species", 0.096,-1.618, 1.005, 4.039,-2.2784,0.942,0.602),#
c("GO:0009791","", 0.098, 6.683,-3.550, 4.048,-1.0400,0.805,0.606),#
c("GO:0051881","", 0.003,-1.699, 6.373, 2.477,-1.1929,0.875,0.610),#
c("GO:0051187","", 0.531,-2.027,-1.695, 4.781,-5.0487,0.857,0.615),#
c("GO:0006397","", 0.620,-4.822,-0.359, 4.849,-8.9747,0.856,0.621),#
c("GO:0007265","", 0.221,-2.956, 5.997, 4.402,-2.4889,0.855,0.623),#
c("GO:0010324","", 0.005, 4.607, 6.144, 2.777,-1.5812,0.822,0.623),#
c("GO:0006122","", 0.011,-0.080,-1.282, 3.105,-1.6685,0.925,0.627),#
c("GO:0016339","", 0.001, 1.439,-0.992, 2.201,-1.0433,0.961,0.632),#
c("GO:0030030","", 0.278, 4.677, 6.193, 4.500,-2.1762,0.754,0.635),#
c("GO:0006559","", 0.019,-3.253,-4.084, 3.331,-2.2959,0.838,0.636),#
c("GO:0006911","", 0.005, 4.011, 6.037, 2.743,-1.0521,0.800,0.646),#
c("GO:0006979","response to oxidative stress", 0.231,-1.317, 0.827, 4.420,-2.0583,0.950,0.646),#
c("GO:0060537","muscle tissue development", 0.036, 7.028,-3.549, 3.618,-1.5332,0.829,0.653),#
c("GO:0050684","", 0.005,-4.394, 4.770, 2.748,-1.7936,0.831,0.653),#
c("GO:0008064","", 0.026, 2.387, 7.863, 3.464,-7.1506,0.637,0.655),#
c("GO:0016358","", 0.014, 7.794, 1.720, 3.188,-1.3150,0.635,0.658),#
c("GO:0006897","endocytosis", 0.075, 1.131, 3.355, 3.934,-1.4100,0.960,0.660),#
c("GO:0002165","", 0.010, 6.716,-3.572, 3.036,-1.3715,0.823,0.662),#
c("GO:0032268","", 0.389,-5.544, 4.690, 4.647,-2.1629,0.775,0.664),#
c("GO:0030163","", 0.408,-4.836,-1.080, 4.667,-1.3202,0.857,0.670),#
c("GO:0010033","", 0.355,-1.417, 1.182, 4.607,-1.1732,0.949,0.670),#
c("GO:0034220","", 1.198, 0.136, 2.096, 5.135,-2.0607,0.923,0.670),#
c("GO:0006570","", 0.045,-2.154,-4.133, 3.706,-1.3029,0.876,0.672),#
c("GO:0042554","", 0.002, 1.269,-1.060, 2.350,-1.0462,0.957,0.675),#
c("GO:0006119","", 0.910,-0.125,-1.330, 5.016,-4.2692,0.905,0.680),#
c("GO:0019362","", 0.466,-3.592,-4.539, 4.725,-3.9281,0.786,0.682),#
c("GO:0006631","", 0.734,-2.148,-4.054, 4.923,-1.1916,0.860,0.684),#
c("GO:0007052","", 0.006, 4.749, 6.355, 2.839,-4.1726,0.739,0.688),#
c("GO:0060711","", 0.005, 6.754,-3.633, 2.740,-1.0462,0.819,0.689),#
c("GO:0009109","", 0.518,-2.422,-2.497, 4.771,-5.2684,0.849,0.689),#
c("GO:0030865","", 0.007, 4.950, 6.686, 2.873,-1.7936,0.757,0.691),#
c("GO:0009208","", 0.044,-2.712,-4.135, 3.698,-1.0960,0.830,0.694),#
c("GO:0032989","", 0.840, 7.542, 2.233, 4.981,-1.0284,0.622,0.695),#
c("GO:0051100","", 0.024,-2.219, 5.334, 3.430,-1.0433,0.890,0.699))
one.data <- data.frame(revigo.data2);#
names(one.data) <- revigo.names;#
one.data <- one.data [(one.data$plot_X != "null" & one.data$plot_Y != "null"), ];#
one.data$plot_X <- as.numeric( as.character(one.data$plot_X) );#
one.data$plot_Y <- as.numeric( as.character(one.data$plot_Y) );#
one.data$plot_size <- as.numeric( as.character(one.data$plot_size) );#
one.data$log10_p_value <- as.numeric( as.character(one.data$log10_p_value) );#
one.data$frequency <- as.numeric( as.character(one.data$frequency) );#
one.data$uniqueness <- as.numeric( as.character(one.data$uniqueness) );#
one.data$dispensability <- as.numeric( as.character(one.data$dispensability) );#
#
p1 <- ggplot( data = one.data );#
p1 <- p1 + geom_point( aes( plot_X, plot_Y, colour = log10_p_value, size = plot_size), alpha = I(0.6) ) + scale_area();#
p1 <- p1 + scale_colour_gradientn( colours = c("blue", "green", "yellow", "red"), limits = c( min(one.data$log10_p_value), 0) );#
p1 <- p1 + geom_point( aes(plot_X, plot_Y, size = plot_size), shape = 21, fill = "transparent", colour = I (alpha ("black", 0.6) )) + scale_area();#
p1 <- p1 + scale_size( range=c(5, 30)) + theme_bw(); # + scale_fill_gradientn(colours = heat_hcl(7), limits = c(-300, 0) );#
ex <- one.data [ one.data$dispensability < 0.15, ]; #
p1 <- p1 + geom_text( data = ex, aes(plot_X, plot_Y, label = description), colour = I(alpha("black", 0.85)), size = 3 );#
p1 <- p1 + labs (y = "semantic space x", x = "semantic space y");#
p1 <- p1 + opts(legend.key = theme_blank()) ;#
one.x_range = max(one.data$plot_X) - min(one.data$plot_X);#
one.y_range = max(one.data$plot_Y) - min(one.data$plot_Y);#
p1 <- p1 + xlim(min(one.data$plot_X)-one.x_range/10,max(one.data$plot_X)+one.x_range/10);#
p1 <- p1 + ylim(min(one.data$plot_Y)-one.y_range/10,max(one.data$plot_Y)+one.y_range/10)
p1
revigo.data2<- rbind(c("GO:0006800","", 0.154, 1.858, 0.396, 4.210,-2.0916,0.993,0.000),#
c("GO:0007626"," ", 0.020,-1.112, 1.133, 3.364,-1.6635,0.971,0.000),#
c("GO:0008283","", 0.143, 0.694,-0.161, 4.213,-1.0233,0.993,0.000),#
c("GO:0008380","RNA splicing", 0.170,-4.408,-0.013, 4.287,-10.7570,0.873,0.000),#
c("GO:0016192","vesicle-mediated transport", 0.348, 0.764, 3.164, 4.598,-3.0506,0.963,0.000),#
c("GO:0022610","", 0.544, 1.207, 0.368, 4.792,-2.2067,0.993,0.000),#
c("GO:0055114","",16.676, 1.629, 0.426, 6.279,-6.6635,0.982,0.013),#
c("GO:0030716","oocyte fate determination", 0.001, 6.988,-3.504, 1.949,-2.6073,0.831,0.014),#
c("GO:0035088","", 0.002, 0.328, 0.023, 2.453,-1.3493,0.967,0.015),#
c("GO:0007163","", 0.016, 1.499, 0.542, 3.262,-1.3900,0.971,0.016),#
c("GO:0030029","", 0.106, 0.178,-0.029, 4.084,-6.2848,0.968,0.019),#
c("GO:0007010","cytoskeleton organization", 0.203, 4.735, 6.336, 4.363,-10.4486,0.734,0.020),#
c("GO:0007017","", 0.308, 0.566, 0.210, 4.546,-5.2226,0.965,0.021),#
c("GO:0000910","", 0.236, 1.601, 0.587, 4.429,-1.2966,0.966,0.021),#
c("GO:0045454","", 0.541,-2.252, 6.619, 4.790,-4.6421,0.830,0.022),#
c("GO:0007155","", 0.540, 0.897,-0.558, 4.789,-2.3218,0.949,0.024),#
c("GO:0042743","", 0.046, 0.049,-0.207, 3.718,-1.8137,0.950,0.035),#
c("GO:0017144","", 0.079, 1.661, 0.611, 3.954,-1.4425,0.953,0.036),#
c("GO:0015980","", 4.971, 0.029,-1.557, 5.753,-9.0182,0.887,0.052),#
c("GO:0006518","peptide metabolic process", 0.211, 0.787,-0.160, 4.381,-1.4665,0.950,0.054),#
c("GO:0006084","", 0.531,-0.875,-1.660, 4.782,-6.2684,0.897,0.060),#
c("GO:0006006","glucose metabolic process", 1.107,-2.536,-4.315, 5.101,-8.4908,0.805,0.065),#
c("GO:0009820","", 0.004, 0.980,-0.151, 2.614,-2.7758,0.962,0.077),#
c("GO:0051186","", 3.543, 0.040, 0.069, 5.606,-3.3125,0.937,0.077),#
c("GO:0006091","", 6.142, 0.623,-0.201, 5.845,-18.0615,0.934,0.085),#
c("GO:0043603","", 0.201,-0.518,-1.157, 4.361,-1.3966,0.926,0.108),#
c("GO:0006890","", 0.005, 1.319, 3.630, 2.757,-1.6644,0.933,0.176),#
c("GO:0048678","", 0.005,-1.154, 0.732, 2.717,-1.0101,0.968,0.214),#
c("GO:0006090","", 0.041,-2.007,-3.845, 3.667,-4.3215,0.891,0.227),#
c("GO:0006414","", 0.665,-5.221, 0.298, 4.880,-6.7905,0.856,0.251),#
c("GO:0051443","", 0.002,-4.697, 4.427, 2.332,-3.1308,0.797,0.259),#
c("GO:0008104","", 1.847, 0.620, 3.155, 5.323,-2.8214,0.936,0.277),#
c("GO:0001539","", 0.387, 0.225, 2.329, 4.645,-2.3615,0.932,0.280),#
c("GO:0010608","", 0.218,-4.398, 5.559, 4.395,-2.4001,0.860,0.289),#
c("GO:0006458","", 0.014,-3.541,-0.418, 3.201,-1.7523,0.904,0.296),#
c("GO:0015985","", 0.663, 0.574, 2.899, 4.879,-2.4501,0.923,0.297),#
c("GO:0016071","", 0.719,-6.026,-1.368, 4.913,-7.6253,0.876,0.300),#
c("GO:0018149","", 0.009,-4.101,-0.343, 3.019,-2.2912,0.901,0.306),#
c("GO:0006818","", 1.025, 0.901, 3.433, 5.067,-2.3529,0.961,0.312),#
c("GO:0021682","", 0.000, 6.949,-3.836, 1.398,-1.6685,0.841,0.315),#
c("GO:0007264","", 0.496,-2.983, 6.084, 4.753,-2.5153,0.847,0.320),#
c("GO:0010498","", 0.042,-5.261,-1.329, 3.680,-2.8750,0.847,0.321),#
c("GO:0006558","", 0.058,-2.232,-4.159, 3.818,-2.1048,0.874,0.323),#
c("GO:0006471","", 0.013,-3.683,-0.341, 3.180,-1.0960,0.899,0.339),#
c("GO:0009894","", 0.238,-3.396, 4.831, 4.433,-1.5155,0.836,0.345),#
c("GO:0006108","", 0.111,-2.053,-3.984, 4.103,-1.3029,0.885,0.346),#
c("GO:0010035","", 0.247,-1.386, 1.132, 4.449,-2.4658,0.950,0.350),#
c("GO:0007164","", 0.004, 6.764,-3.366, 2.685,-1.3497,0.853,0.359),#
c("GO:0009205","", 4.768,-3.673,-3.935, 5.735,-4.6946,0.775,0.369),#
c("GO:0006749","", 0.072,-2.360,-4.572, 3.915,-1.5837,0.878,0.372),#
c("GO:0006769","", 0.000,-1.715,-3.752, 0.954,-2.4131,0.874,0.373),#
c("GO:0006396","", 2.591,-5.116,-0.789, 5.470,-1.4256,0.857,0.395),#
c("GO:0007566","", 0.003, 6.449,-3.641, 2.507,-1.6644,0.834,0.397),#
c("GO:0051289","", 0.007, 4.930, 6.755, 2.888,-1.7869,0.804,0.403),#
c("GO:0019991","", 0.000, 4.749, 6.216, 1.690,-1.1969,0.816,0.413),#
c("GO:0006457","", 0.973,-4.392,-0.306, 5.045,-5.6180,0.875,0.426),#
c("GO:0044087","regulation of cellular component biogenesis", 0.077, 2.289, 7.845, 3.943,-3.2426,0.769,0.428),#
c("GO:0043484","regulation of RNA splicing", 0.006,-4.334, 4.564, 2.846,-1.9392,0.824,0.443),#
c("GO:0001700","", 0.003, 6.337,-3.379, 2.504,-1.0998,0.832,0.446),#
c("GO:0030721","", 0.000, 4.817, 6.552, 0.699,-1.6685,0.826,0.450),#
c("GO:0051129","", 0.045, 2.265, 7.425, 3.711,-1.8220,0.737,0.458),#
c("GO:0051340","", 0.003,-2.596, 6.152, 2.598,-2.3526,0.892,0.470),#
c("GO:0035152","", 0.001, 6.080, 0.005, 2.196,-2.7903,0.745,0.472),#
c("GO:0008340","", 0.009, 6.407,-3.413, 3.035,-1.6606,0.825,0.473),#
c("GO:0006085","", 0.004,-1.213,-1.643, 2.697,-2.2385,0.910,0.474),#
c("GO:0045478","", 0.000, 4.829, 6.460, 1.279,-1.6685,0.815,0.484),#
c("GO:0051591","", 0.005,-1.258, 0.746, 2.749,-1.7936,0.959,0.490),#
c("GO:0006213","", 0.201,-3.187,-4.297, 4.359,-1.4180,0.828,0.495),#
c("GO:0043433","", 0.009,-4.260, 4.614, 2.999,-1.0960,0.817,0.499),#
c("GO:0007276","", 0.062, 5.891,-4.046, 3.846,-1.4704,0.848,0.500),#
c("GO:0007444","", 0.009, 6.446,-3.405, 2.991,-1.7166,0.816,0.504),#
c("GO:0016044","", 0.166, 5.067, 6.954, 4.276,-1.6677,0.785,0.505),#
c("GO:0060047","", 0.013, 5.819,-3.867, 3.159,-1.1929,0.879,0.508),#
c("GO:0019953","", 0.086, 3.339,-2.209, 3.990,-1.0008,0.959,0.510),#
c("GO:0051084","", 0.014,-3.660,-0.386, 3.194,-1.0462,0.904,0.516),#
c("GO:0048754","", 0.021, 6.380,-3.373, 3.372,-1.3150,0.814,0.526),#
c("GO:0010927","", 0.019, 7.406, 2.247, 3.332,-1.1170,0.660,0.527),#
c("GO:0006413","", 0.337,-5.138, 0.300, 4.584,-1.7656,0.863,0.533),#
c("GO:0001763","", 0.026, 6.478,-3.423, 3.470,-1.3294,0.820,0.537),#
c("GO:0006412","", 4.967,-5.423, 0.276, 5.753,-5.2041,0.832,0.538),#
c("GO:0045429","", 0.004,-2.690, 5.902, 2.619,-1.0462,0.842,0.541),#
c("GO:0009992","", 0.000,-1.437, 6.111, 1.623,-1.6685,0.886,0.541),#
c("GO:0006112","energy reserve metabolic process", 0.129,-0.107,-1.299, 4.169,-1.8918,0.915,0.543),#
c("GO:0007016","", 0.002, 2.191, 7.245, 2.401,-3.1273,0.682,0.560),#
c("GO:0042692","", 0.034, 6.774,-3.330, 3.589,-2.5846,0.785,0.563),#
c("GO:0016052","", 1.399,-2.781,-2.512, 5.203,-5.3516,0.867,0.564),#
c("GO:0035317","", 0.001, 7.750, 1.636, 2.004,-1.9392,0.666,0.567),#
c("GO:0051235","", 0.032,-1.949, 6.873, 3.556,-1.9771,0.861,0.584),#
c("GO:0005977","glycogen metabolic process", 0.128,-2.440,-1.665, 4.164,-1.8918,0.840,0.589),#
c("GO:0043933","", 1.085, 4.880, 6.508, 5.092,-2.5019,0.781,0.593),#
c("GO:0042775","", 0.315,-0.424,-1.022, 4.555,-2.1471,0.906,0.598),#
c("GO:0044042","", 0.249,-2.591,-1.536, 4.452,-1.3150,0.900,0.600),#
c("GO:0000302","response to reactive oxygen species", 0.096,-1.618, 1.005, 4.039,-2.2784,0.942,0.602),#
c("GO:0009791","", 0.098, 6.683,-3.550, 4.048,-1.0400,0.805,0.606),#
c("GO:0051881","", 0.003,-1.699, 6.373, 2.477,-1.1929,0.875,0.610),#
c("GO:0051187","", 0.531,-2.027,-1.695, 4.781,-5.0487,0.857,0.615),#
c("GO:0006397","mRNA processing", 0.620,-4.822,-0.359, 4.849,-8.9747,0.856,0.621),#
c("GO:0007265","Ras protein signal transduction", 0.221,-2.956, 5.997, 4.402,-2.4889,0.855,0.623),#
c("GO:0010324","", 0.005, 4.607, 6.144, 2.777,-1.5812,0.822,0.623),#
c("GO:0006122","", 0.011,-0.080,-1.282, 3.105,-1.6685,0.925,0.627),#
c("GO:0016339","", 0.001, 1.439,-0.992, 2.201,-1.0433,0.961,0.632),#
c("GO:0030030","", 0.278, 4.677, 6.193, 4.500,-2.1762,0.754,0.635),#
c("GO:0006559","", 0.019,-3.253,-4.084, 3.331,-2.2959,0.838,0.636),#
c("GO:0006911","", 0.005, 4.011, 6.037, 2.743,-1.0521,0.800,0.646),#
c("GO:0006979","", 0.231,-1.317, 0.827, 4.420,-2.0583,0.950,0.646),#
c("GO:0060537","", 0.036, 7.028,-3.549, 3.618,-1.5332,0.829,0.653),#
c("GO:0050684","regulation of mRNA processing", 0.005,-4.394, 4.770, 2.748,-1.7936,0.831,0.653),#
c("GO:0008064","", 0.026, 2.387, 7.863, 3.464,-7.1506,0.637,0.655),#
c("GO:0016358","", 0.014, 7.794, 1.720, 3.188,-1.3150,0.635,0.658),#
c("GO:0006897","endocytosis", 0.075, 1.131, 3.355, 3.934,-1.4100,0.960,0.660),#
c("GO:0002165","", 0.010, 6.716,-3.572, 3.036,-1.3715,0.823,0.662),#
c("GO:0032268","", 0.389,-5.544, 4.690, 4.647,-2.1629,0.775,0.664),#
c("GO:0030163","", 0.408,-4.836,-1.080, 4.667,-1.3202,0.857,0.670),#
c("GO:0010033","", 0.355,-1.417, 1.182, 4.607,-1.1732,0.949,0.670),#
c("GO:0034220","", 1.198, 0.136, 2.096, 5.135,-2.0607,0.923,0.670),#
c("GO:0006570","", 0.045,-2.154,-4.133, 3.706,-1.3029,0.876,0.672),#
c("GO:0042554","", 0.002, 1.269,-1.060, 2.350,-1.0462,0.957,0.675),#
c("GO:0006119","", 0.910,-0.125,-1.330, 5.016,-4.2692,0.905,0.680),#
c("GO:0019362","", 0.466,-3.592,-4.539, 4.725,-3.9281,0.786,0.682),#
c("GO:0006631","", 0.734,-2.148,-4.054, 4.923,-1.1916,0.860,0.684),#
c("GO:0007052","", 0.006, 4.749, 6.355, 2.839,-4.1726,0.739,0.688),#
c("GO:0060711","", 0.005, 6.754,-3.633, 2.740,-1.0462,0.819,0.689),#
c("GO:0009109","", 0.518,-2.422,-2.497, 4.771,-5.2684,0.849,0.689),#
c("GO:0030865","", 0.007, 4.950, 6.686, 2.873,-1.7936,0.757,0.691),#
c("GO:0009208","", 0.044,-2.712,-4.135, 3.698,-1.0960,0.830,0.694),#
c("GO:0032989","cellular component morphogenesis", 0.840, 7.542, 2.233, 4.981,-1.0284,0.622,0.695),#
c("GO:0051100","", 0.024,-2.219, 5.334, 3.430,-1.0433,0.890,0.699))
one.data <- data.frame(revigo.data2);#
names(one.data) <- revigo.names;#
one.data <- one.data [(one.data$plot_X != "null" & one.data$plot_Y != "null"), ];#
one.data$plot_X <- as.numeric( as.character(one.data$plot_X) );#
one.data$plot_Y <- as.numeric( as.character(one.data$plot_Y) );#
one.data$plot_size <- as.numeric( as.character(one.data$plot_size) );#
one.data$log10_p_value <- as.numeric( as.character(one.data$log10_p_value) );#
one.data$frequency <- as.numeric( as.character(one.data$frequency) );#
one.data$uniqueness <- as.numeric( as.character(one.data$uniqueness) );#
one.data$dispensability <- as.numeric( as.character(one.data$dispensability) );#
#
p1 <- ggplot( data = one.data );#
p1 <- p1 + geom_point( aes( plot_X, plot_Y, colour = log10_p_value, size = plot_size), alpha = I(0.6) ) + scale_area();#
p1 <- p1 + scale_colour_gradientn( colours = c("blue", "green", "yellow", "red"), limits = c( min(one.data$log10_p_value), 0) );#
p1 <- p1 + geom_point( aes(plot_X, plot_Y, size = plot_size), shape = 21, fill = "transparent", colour = I (alpha ("black", 0.6) )) + scale_area();#
p1 <- p1 + scale_size( range=c(5, 30)) + theme_bw(); # + scale_fill_gradientn(colours = heat_hcl(7), limits = c(-300, 0) );#
ex <- one.data [ one.data$dispensability < 0.15, ]; #
p1 <- p1 + geom_text( data = ex, aes(plot_X, plot_Y, label = description), colour = I(alpha("black", 0.85)), size = 3 );#
p1 <- p1 + labs (y = "semantic space x", x = "semantic space y");#
p1 <- p1 + opts(legend.key = theme_blank()) ;#
one.x_range = max(one.data$plot_X) - min(one.data$plot_X);#
one.y_range = max(one.data$plot_Y) - min(one.data$plot_Y);#
p1 <- p1 + xlim(min(one.data$plot_X)-one.x_range/10,max(one.data$plot_X)+one.x_range/10);#
p1 <- p1 + ylim(min(one.data$plot_Y)-one.y_range/10,max(one.data$plot_Y)+one.y_range/10)
p1
one.data <- data.frame(revigo.data);
#
names(one.data) <- revigo.names;
#
one.data <- one.data [(one.data$plot_X != "null" & one.data$plot_Y != "null"), ];
#
one.data$plot_X <- as.numeric( as.character(one.data$plot_X) );
#
one.data$plot_Y <- as.numeric( as.character(one.data$plot_Y) );
#
one.data$plot_size <- as.numeric( as.character(one.data$plot_size) );
#
one.data$log10_p_value <- as.numeric( as.character(one.data$log10_p_value) );
#
one.data$frequency <- as.numeric( as.character(one.data$frequency) );
#
one.data$uniqueness <- as.numeric( as.character(one.data$uniqueness) );
#
one.data$dispensability <- as.numeric( as.character(one.data$dispensability) )
p1 <- ggplot( data = one.data );
#
p1 <- p1 + geom_point( aes( plot_X, plot_Y, colour = log10_p_value, size = plot_size), alpha = I(0.6) ) + scale_area();
#
p1 <- p1 + scale_colour_gradientn( colours = c("blue", "green", "yellow", "red"), limits = c( min(one.data$log10_p_value), 0) );
#
p1 <- p1 + geom_point( aes(plot_X, plot_Y, size = plot_size), shape = 21, fill = "transparent", colour = I (alpha ("black", 0.6) )) + scale_area();
#
p1 <- p1 + scale_size( range=c(5, 30)) + theme_bw(); # + scale_fill_gradientn(colours = heat_hcl(7), limits = c(-300, 0) );
#
ex <- one.data [ one.data$dispensability < 0.15, ]; 
#
p1 <- p1 + geom_text( data = ex, aes(plot_X, plot_Y, label = description), colour = I(alpha("black", 0.85)), size = 3 );
#
p1 <- p1 + labs (y = "semantic space x", x = "semantic space y");
#
p1 <- p1 + opts(legend.key = theme_blank()) ;
#
one.x_range = max(one.data$plot_X) - min(one.data$plot_X);
#
one.y_range = max(one.data$plot_Y) - min(one.data$plot_Y);
#
p1 <- p1 + xlim(min(one.data$plot_X)-one.x_range/10,max(one.data$plot_X)+one.x_range/10);
#
p1 <- p1 + ylim(min(one.data$plot_Y)-one.y_range/10,max(one.data$plot_Y)+one.y_range/10)
p1
revigo.data2<- rbind(c("GO:0006800","", 0.154, 1.858, 0.396, 4.210,-2.0916,0.993,0.000),#
c("GO:0007626"," ", 0.020,-1.112, 1.133, 3.364,-1.6635,0.971,0.000),#
c("GO:0008283","", 0.143, 0.694,-0.161, 4.213,-1.0233,0.993,0.000),#
c("GO:0008380","RNA splicing", 0.170,-4.408,-0.013, 4.287,-10.7570,0.873,0.000),#
c("GO:0016192","vesicle-mediated transport", 0.348, 0.764, 3.164, 4.598,-3.0506,0.963,0.000),#
c("GO:0022610","", 0.544, 1.207, 0.368, 4.792,-2.2067,0.993,0.000),#
c("GO:0055114","",16.676, 1.629, 0.426, 6.279,-6.6635,0.982,0.013),#
c("GO:0030716","oocyte fate determination", 0.001, 6.988,-3.504, 1.949,-2.6073,0.831,0.014),#
c("GO:0035088","", 0.002, 0.328, 0.023, 2.453,-1.3493,0.967,0.015),#
c("GO:0007163","", 0.016, 1.499, 0.542, 3.262,-1.3900,0.971,0.016),#
c("GO:0030029","", 0.106, 0.178,-0.029, 4.084,-6.2848,0.968,0.019),#
c("GO:0007010","cytoskeleton organization", 0.203, 4.735, 6.336, 4.363,-10.4486,0.734,0.020),#
c("GO:0007017","", 0.308, 0.566, 0.210, 4.546,-5.2226,0.965,0.021),#
c("GO:0000910","", 0.236, 1.601, 0.587, 4.429,-1.2966,0.966,0.021),#
c("GO:0045454","cell redox homeostasis", 0.541,-2.252, 6.619, 4.790,-4.6421,0.830,0.022),#
c("GO:0007155","", 0.540, 0.897,-0.558, 4.789,-2.3218,0.949,0.024),#
c("GO:0042743","", 0.046, 0.049,-0.207, 3.718,-1.8137,0.950,0.035),#
c("GO:0017144","", 0.079, 1.661, 0.611, 3.954,-1.4425,0.953,0.036),#
c("GO:0015980","energy derivation by oxidation of organic compounds", 4.971, 0.029,-1.557, 5.753,-9.0182,0.887,0.052),#
c("GO:0006518","peptide metabolic process", 0.211, 0.787,-0.160, 4.381,-1.4665,0.950,0.054),#
c("GO:0006084","", 0.531,-0.875,-1.660, 4.782,-6.2684,0.897,0.060),#
c("GO:0006006","glucose metabolic process", 1.107,-2.536,-4.315, 5.101,-8.4908,0.805,0.065),#
c("GO:0009820","", 0.004, 0.980,-0.151, 2.614,-2.7758,0.962,0.077),#
c("GO:0051186","", 3.543, 0.040, 0.069, 5.606,-3.3125,0.937,0.077),#
c("GO:0006091","", 6.142, 0.623,-0.201, 5.845,-18.0615,0.934,0.085),#
c("GO:0043603","cellular amide metabolic process", 0.201,-0.518,-1.157, 4.361,-1.3966,0.926,0.108),#
c("GO:0006890","", 0.005, 1.319, 3.630, 2.757,-1.6644,0.933,0.176),#
c("GO:0048678","", 0.005,-1.154, 0.732, 2.717,-1.0101,0.968,0.214),#
c("GO:0006090","", 0.041,-2.007,-3.845, 3.667,-4.3215,0.891,0.227),#
c("GO:0006414","", 0.665,-5.221, 0.298, 4.880,-6.7905,0.856,0.251),#
c("GO:0051443","", 0.002,-4.697, 4.427, 2.332,-3.1308,0.797,0.259),#
c("GO:0008104","", 1.847, 0.620, 3.155, 5.323,-2.8214,0.936,0.277),#
c("GO:0001539","", 0.387, 0.225, 2.329, 4.645,-2.3615,0.932,0.280),#
c("GO:0010608","", 0.218,-4.398, 5.559, 4.395,-2.4001,0.860,0.289),#
c("GO:0006458","", 0.014,-3.541,-0.418, 3.201,-1.7523,0.904,0.296),#
c("GO:0015985","", 0.663, 0.574, 2.899, 4.879,-2.4501,0.923,0.297),#
c("GO:0016071","", 0.719,-6.026,-1.368, 4.913,-7.6253,0.876,0.300),#
c("GO:0018149","", 0.009,-4.101,-0.343, 3.019,-2.2912,0.901,0.306),#
c("GO:0006818","", 1.025, 0.901, 3.433, 5.067,-2.3529,0.961,0.312),#
c("GO:0021682","", 0.000, 6.949,-3.836, 1.398,-1.6685,0.841,0.315),#
c("GO:0007264","", 0.496,-2.983, 6.084, 4.753,-2.5153,0.847,0.320),#
c("GO:0010498","", 0.042,-5.261,-1.329, 3.680,-2.8750,0.847,0.321),#
c("GO:0006558","", 0.058,-2.232,-4.159, 3.818,-2.1048,0.874,0.323),#
c("GO:0006471","", 0.013,-3.683,-0.341, 3.180,-1.0960,0.899,0.339),#
c("GO:0009894","", 0.238,-3.396, 4.831, 4.433,-1.5155,0.836,0.345),#
c("GO:0006108","", 0.111,-2.053,-3.984, 4.103,-1.3029,0.885,0.346),#
c("GO:0010035","", 0.247,-1.386, 1.132, 4.449,-2.4658,0.950,0.350),#
c("GO:0007164","", 0.004, 6.764,-3.366, 2.685,-1.3497,0.853,0.359),#
c("GO:0009205","", 4.768,-3.673,-3.935, 5.735,-4.6946,0.775,0.369),#
c("GO:0006749","", 0.072,-2.360,-4.572, 3.915,-1.5837,0.878,0.372),#
c("GO:0006769","", 0.000,-1.715,-3.752, 0.954,-2.4131,0.874,0.373),#
c("GO:0006396","", 2.591,-5.116,-0.789, 5.470,-1.4256,0.857,0.395),#
c("GO:0007566","", 0.003, 6.449,-3.641, 2.507,-1.6644,0.834,0.397),#
c("GO:0051289","", 0.007, 4.930, 6.755, 2.888,-1.7869,0.804,0.403),#
c("GO:0019991","", 0.000, 4.749, 6.216, 1.690,-1.1969,0.816,0.413),#
c("GO:0006457","", 0.973,-4.392,-0.306, 5.045,-5.6180,0.875,0.426),#
c("GO:0044087","regulation of cellular component biogenesis", 0.077, 2.289, 7.845, 3.943,-3.2426,0.769,0.428),#
c("GO:0043484","regulation of RNA splicing", 0.006,-4.334, 4.564, 2.846,-1.9392,0.824,0.443),#
c("GO:0001700","", 0.003, 6.337,-3.379, 2.504,-1.0998,0.832,0.446),#
c("GO:0030721","", 0.000, 4.817, 6.552, 0.699,-1.6685,0.826,0.450),#
c("GO:0051129","", 0.045, 2.265, 7.425, 3.711,-1.8220,0.737,0.458),#
c("GO:0051340","", 0.003,-2.596, 6.152, 2.598,-2.3526,0.892,0.470),#
c("GO:0035152","", 0.001, 6.080, 0.005, 2.196,-2.7903,0.745,0.472),#
c("GO:0008340","", 0.009, 6.407,-3.413, 3.035,-1.6606,0.825,0.473),#
c("GO:0006085","", 0.004,-1.213,-1.643, 2.697,-2.2385,0.910,0.474),#
c("GO:0045478","", 0.000, 4.829, 6.460, 1.279,-1.6685,0.815,0.484),#
c("GO:0051591","", 0.005,-1.258, 0.746, 2.749,-1.7936,0.959,0.490),#
c("GO:0006213","", 0.201,-3.187,-4.297, 4.359,-1.4180,0.828,0.495),#
c("GO:0043433","", 0.009,-4.260, 4.614, 2.999,-1.0960,0.817,0.499),#
c("GO:0007276","", 0.062, 5.891,-4.046, 3.846,-1.4704,0.848,0.500),#
c("GO:0007444","", 0.009, 6.446,-3.405, 2.991,-1.7166,0.816,0.504),#
c("GO:0016044","", 0.166, 5.067, 6.954, 4.276,-1.6677,0.785,0.505),#
c("GO:0060047","", 0.013, 5.819,-3.867, 3.159,-1.1929,0.879,0.508),#
c("GO:0019953","", 0.086, 3.339,-2.209, 3.990,-1.0008,0.959,0.510),#
c("GO:0051084","", 0.014,-3.660,-0.386, 3.194,-1.0462,0.904,0.516),#
c("GO:0048754","", 0.021, 6.380,-3.373, 3.372,-1.3150,0.814,0.526),#
c("GO:0010927","", 0.019, 7.406, 2.247, 3.332,-1.1170,0.660,0.527),#
c("GO:0006413","", 0.337,-5.138, 0.300, 4.584,-1.7656,0.863,0.533),#
c("GO:0001763","", 0.026, 6.478,-3.423, 3.470,-1.3294,0.820,0.537),#
c("GO:0006412","", 4.967,-5.423, 0.276, 5.753,-5.2041,0.832,0.538),#
c("GO:0045429","", 0.004,-2.690, 5.902, 2.619,-1.0462,0.842,0.541),#
c("GO:0009992","", 0.000,-1.437, 6.111, 1.623,-1.6685,0.886,0.541),#
c("GO:0006112","energy reserve metabolic process", 0.129,-0.107,-1.299, 4.169,-1.8918,0.915,0.543),#
c("GO:0007016","", 0.002, 2.191, 7.245, 2.401,-3.1273,0.682,0.560),#
c("GO:0042692","", 0.034, 6.774,-3.330, 3.589,-2.5846,0.785,0.563),#
c("GO:0016052","", 1.399,-2.781,-2.512, 5.203,-5.3516,0.867,0.564),#
c("GO:0035317","", 0.001, 7.750, 1.636, 2.004,-1.9392,0.666,0.567),#
c("GO:0051235","", 0.032,-1.949, 6.873, 3.556,-1.9771,0.861,0.584),#
c("GO:0005977","glycogen metabolic process", 0.128,-2.440,-1.665, 4.164,-1.8918,0.840,0.589),#
c("GO:0043933","", 1.085, 4.880, 6.508, 5.092,-2.5019,0.781,0.593),#
c("GO:0042775","", 0.315,-0.424,-1.022, 4.555,-2.1471,0.906,0.598),#
c("GO:0044042","", 0.249,-2.591,-1.536, 4.452,-1.3150,0.900,0.600),#
c("GO:0000302","response to reactive oxygen species", 0.096,-1.618, 1.005, 4.039,-2.2784,0.942,0.602),#
c("GO:0009791","", 0.098, 6.683,-3.550, 4.048,-1.0400,0.805,0.606),#
c("GO:0051881","", 0.003,-1.699, 6.373, 2.477,-1.1929,0.875,0.610),#
c("GO:0051187","", 0.531,-2.027,-1.695, 4.781,-5.0487,0.857,0.615),#
c("GO:0006397","mRNA processing", 0.620,-4.822,-0.359, 4.849,-8.9747,0.856,0.621),#
c("GO:0007265","Ras protein signal transduction", 0.221,-2.956, 5.997, 4.402,-2.4889,0.855,0.623),#
c("GO:0010324","", 0.005, 4.607, 6.144, 2.777,-1.5812,0.822,0.623),#
c("GO:0006122","", 0.011,-0.080,-1.282, 3.105,-1.6685,0.925,0.627),#
c("GO:0016339","", 0.001, 1.439,-0.992, 2.201,-1.0433,0.961,0.632),#
c("GO:0030030","", 0.278, 4.677, 6.193, 4.500,-2.1762,0.754,0.635),#
c("GO:0006559","", 0.019,-3.253,-4.084, 3.331,-2.2959,0.838,0.636),#
c("GO:0006911","", 0.005, 4.011, 6.037, 2.743,-1.0521,0.800,0.646),#
c("GO:0006979","", 0.231,-1.317, 0.827, 4.420,-2.0583,0.950,0.646),#
c("GO:0060537","", 0.036, 7.028,-3.549, 3.618,-1.5332,0.829,0.653),#
c("GO:0050684","regulation of mRNA processing", 0.005,-4.394, 4.770, 2.748,-1.7936,0.831,0.653),#
c("GO:0008064","", 0.026, 2.387, 7.863, 3.464,-7.1506,0.637,0.655),#
c("GO:0016358","", 0.014, 7.794, 1.720, 3.188,-1.3150,0.635,0.658),#
c("GO:0006897","endocytosis", 0.075, 1.131, 3.355, 3.934,-1.4100,0.960,0.660),#
c("GO:0002165","", 0.010, 6.716,-3.572, 3.036,-1.3715,0.823,0.662),#
c("GO:0032268","", 0.389,-5.544, 4.690, 4.647,-2.1629,0.775,0.664),#
c("GO:0030163","", 0.408,-4.836,-1.080, 4.667,-1.3202,0.857,0.670),#
c("GO:0010033","", 0.355,-1.417, 1.182, 4.607,-1.1732,0.949,0.670),#
c("GO:0034220","", 1.198, 0.136, 2.096, 5.135,-2.0607,0.923,0.670),#
c("GO:0006570","", 0.045,-2.154,-4.133, 3.706,-1.3029,0.876,0.672),#
c("GO:0042554","", 0.002, 1.269,-1.060, 2.350,-1.0462,0.957,0.675),#
c("GO:0006119","", 0.910,-0.125,-1.330, 5.016,-4.2692,0.905,0.680),#
c("GO:0019362","", 0.466,-3.592,-4.539, 4.725,-3.9281,0.786,0.682),#
c("GO:0006631","", 0.734,-2.148,-4.054, 4.923,-1.1916,0.860,0.684),#
c("GO:0007052","", 0.006, 4.749, 6.355, 2.839,-4.1726,0.739,0.688),#
c("GO:0060711","", 0.005, 6.754,-3.633, 2.740,-1.0462,0.819,0.689),#
c("GO:0009109","", 0.518,-2.422,-2.497, 4.771,-5.2684,0.849,0.689),#
c("GO:0030865","", 0.007, 4.950, 6.686, 2.873,-1.7936,0.757,0.691),#
c("GO:0009208","", 0.044,-2.712,-4.135, 3.698,-1.0960,0.830,0.694),#
c("GO:0032989","cellular component morphogenesis", 0.840, 7.542, 2.233, 4.981,-1.0284,0.622,0.695),#
c("GO:0051100","", 0.024,-2.219, 5.334, 3.430,-1.0433,0.890,0.699))
one.data <- data.frame(revigo.data2);#
names(one.data) <- revigo.names;#
one.data <- one.data [(one.data$plot_X != "null" & one.data$plot_Y != "null"), ];#
one.data$plot_X <- as.numeric( as.character(one.data$plot_X) );#
one.data$plot_Y <- as.numeric( as.character(one.data$plot_Y) );#
one.data$plot_size <- as.numeric( as.character(one.data$plot_size) );#
one.data$log10_p_value <- as.numeric( as.character(one.data$log10_p_value) );#
one.data$frequency <- as.numeric( as.character(one.data$frequency) );#
one.data$uniqueness <- as.numeric( as.character(one.data$uniqueness) );#
one.data$dispensability <- as.numeric( as.character(one.data$dispensability) );#
#
p1 <- ggplot( data = one.data );#
p1 <- p1 + geom_point( aes( plot_X, plot_Y, colour = log10_p_value, size = plot_size), alpha = I(0.6) ) + scale_area();#
p1 <- p1 + scale_colour_gradientn( colours = c("blue", "green", "yellow", "red"), limits = c( min(one.data$log10_p_value), 0) );#
p1 <- p1 + geom_point( aes(plot_X, plot_Y, size = plot_size), shape = 21, fill = "transparent", colour = I (alpha ("black", 0.6) )) + scale_area();#
p1 <- p1 + scale_size( range=c(5, 30)) + theme_bw(); # + scale_fill_gradientn(colours = heat_hcl(7), limits = c(-300, 0) );#
ex <- one.data [ one.data$dispensability < 0.15, ]; #
p1 <- p1 + geom_text( data = ex, aes(plot_X, plot_Y, label = description), colour = I(alpha("black", 0.85)), size = 3 );#
p1 <- p1 + labs (y = "semantic space x", x = "semantic space y");#
p1 <- p1 + opts(legend.key = theme_blank()) ;#
one.x_range = max(one.data$plot_X) - min(one.data$plot_X);#
one.y_range = max(one.data$plot_Y) - min(one.data$plot_Y);#
p1 <- p1 + xlim(min(one.data$plot_X)-one.x_range/10,max(one.data$plot_X)+one.x_range/10);#
p1 <- p1 + ylim(min(one.data$plot_Y)-one.y_range/10,max(one.data$plot_Y)+one.y_range/10)
p1
no.peps<-c(1000,5000,10000,12000,500,15000,50000,30000,40000,70000)#
no.prots<-c(587,1344,1773,1864,331,1936,2658,2400,2516,2833)
plot(no.peps, no.prots, xlab="Number of Sequenced Peptides", ylab='Number of Unique Proteins Identified', pch=19)
citation()
source('http://bioconductor.org/biocLite.R')
biocLite('DESeq')
library(lattice)
library(locfit)
biocLite('DESeq')
source('http://bioconductor.org/biocLite.R')
biocLite('DESeq')
source('http://bioconductor.org/biocLite.R')
biocLite('DESeq')
library(vegdist)
source('http://bioconductor.org/biocLite.R')
biocLite('goseq')
citation()
library(pheatmap)
?pheatmap
?metaMDS
library(vegan)
?metaMDS
citation('vegan')
citation()
revigo.names <- c("term_ID","description","frequency_%","plot_X","plot_Y","plot_size","log10_p_value","uniqueness","dispensability");
revigo.data <- rbind(c("GO:0007156","homophilic cell adhesion", 0.056, 2.343,-0.125, 4.022,-1.2257,0.603,0.000),
c("GO:0009611","response to wounding", 0.223,-5.266, 1.816, 4.622,-1.3865,0.698,0.000),
#
c("GO:0030866","cortical actin cytoskeleton organization", 0.004, 4.020, 4.646, 2.916,-1.0511,0.513,0.141),
#
c("GO:0051651","maintenance of location in cell", 0.022, 3.440,-3.668, 3.619,-1.2257,0.436,0.156),
#
c("GO:0006355","regulation of transcription, DNA-dependent", 8.764,-0.510,-6.210, 6.216,-1.3387,0.728,0.284),
#
c("GO:0045216","cell-cell junction organization", 0.015, 5.908, 2.870, 3.437,-1.0511,0.551,0.322),
#
c("GO:0006954","inflammatory response", 0.173,-4.942, 3.120, 4.510,-1.2425,0.698,0.481),
#
c("GO:0030865","cortical cytoskeleton organization", 0.005, 4.733, 4.340, 2.976,-1.0511,0.512,0.608),
#
c("GO:0046907","intracellular transport", 0.834, 5.396,-1.507, 5.194,-1.0755,0.417,0.611))
one.data <- data.frame(revigo.data);
names(one.data) <- revigo.names;
one.data <- one.data [(one.data$plot_X != "null" & one.data$plot_Y != "null"), ];
#
one.data$plot_X <- as.numeric( as.character(one.data$plot_X) );
#
one.data$plot_Y <- as.numeric( as.character(one.data$plot_Y) );
#
one.data$plot_size <- as.numeric( as.character(one.data$plot_size) );
#
one.data$log10_p_value <- as.numeric( as.character(one.data$log10_p_value) );
#
one.data$frequency <- as.numeric( as.character(one.data$frequency) );
#
one.data$uniqueness <- as.numeric( as.character(one.data$uniqueness) );
#
one.data$dispensability <- as.numeric( as.character(one.data$dispensability) )
p1 <- ggplot( data = one.data );
library(ggplot)
library(ggplot2)
p1 <- ggplot( data = one.data );
p1 <- p1 + geom_point( aes( plot_X, plot_Y, colour = log10_p_value, size = plot_size), alpha = I(0.6) ) + scale_area()
p1 <- p1 + geom_point( aes( plot_X, plot_Y, colour = log10_p_value, size = plot_size), alpha = I(0.6) ) + scale_size_area();
p1 <- p1 + geom_point( aes( plot_X, plot_Y, colour = log10_p_value, alpha = I(0.6) ) + scale_size_area();
p1 <- p1 + geom_point( aes( plot_X, plot_Y, colour = log10_p_value, alpha = I(0.6) ) + scale_size_area()
)
?scale_size_area
p1 <- p1 + geom_point( aes( plot_X, plot_Y, colour = log10_p_value, alpha = I(0.6) ) + scale_size_area();
p1 <- p1 + geom_point( aes( plot_X, plot_Y, colour = log10_p_value, size = plot_size), alpha = I(0.6) );
p1 <- p1 + scale_colour_gradientn( colours = c("blue", "green", "yellow", "red"), limits = c( min(one.data$log10_p_value), 0) );
p1 <- p1 + geom_point( aes(plot_X, plot_Y, size = plot_size), shape = 21, fill = "transparent", colour = I (alpha ("black", 0.6) )) + scale_area();
p1 <- p1 + geom_point( aes( plot_X, plot_Y, colour = log10_p_value, size = plot_size), alph = I(0.6) );
p1 <- p1 + scale_colour_gradientn( colours = c("blue", "green", "yellow", "red"), limits = c( min(one.data$log10_p_value), 0) );
p1 <- p1 + geom_point( aes(plot_X, plot_Y, size = plot_size), shape = 21, fill = "transparent", colour = I (alph ("black", 0.6) )) + scale_area();
library(scales)
p1 <- p1 + geom_point( aes( plot_X, plot_Y, colour = log10_p_value, size = plot_size), alpha = I(0.6) );
p1 <- p1 + scale_colour_gradientn( colours = c("blue", "green", "yellow", "red"), limits = c( min(one.data$log10_p_value), 0) );
p1 <- p1 + geom_point( aes(plot_X, plot_Y, size = plot_size), shape = 21, fill = "transparent", colour = I (alpha ("black", 0.6) )) + scale_area();
rm(p1)
plot.mort<-par(mfrow=c(1,2))
ggplot(df) + geom_step(aes(x=Jour, y=Inf1), colour='darkred') + geom_step(aes(x=Jour, y=Inf2), colour='red') + geom_step(aes(x=Jour, y=Inf3), colour='deeppink3') + scale_y_continuous(name='Number of Mortalities') + scale_x_continuous(name='Day')
library(ggplot2)
ggplot(df) + geom_step(aes(x=Jour, y=Inf1), colour='darkred') + geom_step(aes(x=Jour, y=Inf2), colour='red') + geom_step(aes(x=Jour, y=Inf3), colour='deeppink3') + scale_y_continuous(name='Number of Mortalities') + scale_x_continuous(name='Day')
library(qvalue)
citation(qvalue)
citation()
citation('qvalue')
citation()
citation("vegan")
citation("qvalue")
?pichart
?piechart
oyster.norm<-c(0.25, 0.25, 0.25, 0.25)
piechart(osyter.norm)
?pie
pie(oyster.norm)
pie(oyster.norm, labels=c('growth and development', 'maintenance of pH', 'response to stress', 'shell deposition'), col=c('deeppink3', 'goldenrod1', 'slateblue4', 'darkolivegreen'))
pie(oyster.norm, labels=c('growth and development', 'maintenance of pH', 'response to stress', 'shell deposition'), col=c('deeppink3', 'goldenrod1', 'slateblue4', 'darkgreen'))
oyster.oa<-c(0.07, 0.4, 0.4, 0.13)
pie(oyster.oa, labels=c('growth and development', 'maintenance of pH', 'response to stress', 'shell deposition'), col=c('deeppink3', 'goldenrod1', 'slateblue4', 'darkgreen'))
pie(oyster.oa, labels=c('growth and \ndevelopment', 'maintenance of pH', 'response to stress', 'shell deposition'), col=c('deeppink3', 'goldenrod1', 'slateblue4', 'darkgreen'))
pie(oyster.norm, labels=c('growth and \ndevelopment', 'maintenance of pH', 'response to stress', 'shell deposition'), col=c('deeppink3', 'goldenrod1', 'slateblue4', 'darkgreen'))
setwd('/Users/emmatimminsschiffman/Documents/Dissertation/dissertation drafts/images for prezi')
install.packages( "treemap" );
library(treemap) 								# treemap package by Martijn Tennekes
revigo.names <- c("term_ID","description","freqInDbPercent","abslog10pvalue","uniqueness","dispensability","representative");
#
revigo.data <- rbind(c("GO:0006006","glucose metabolic process",1.142,10.2798,0.873,0.000,"glucose metabolism"),
#
c("GO:0016052","carbohydrate catabolic process",1.307,5.0857,0.864,0.586,"glucose metabolism"),
#
c("GO:0044275","cellular carbohydrate catabolic process",0.178,7.1325,0.850,0.604,"glucose metabolism"),
#
c("GO:0005977","glycogen metabolic process",0.133,2.2693,0.829,0.635,"glucose metabolism"),
#
c("GO:0006800","oxygen and reactive oxygen species metabolic process",0.172,1.4660,0.992,0.000,"oxygen and reactive oxygen species metabolism"),
#
c("GO:0007010","cytoskeleton organization",0.232,11.6517,0.653,0.000,"cytoskeleton organization"),
#
c("GO:0032271","regulation of protein polymerization",0.030,5.7645,0.684,0.429,"cytoskeleton organization"),
#
c("GO:0006323","DNA packaging",0.289,1.4721,0.638,0.591,"cytoskeleton organization"),
#
c("GO:0000305","response to oxygen radical",0.000,1.2714,0.954,0.613,"cytoskeleton organization"),
#
c("GO:0003006","developmental process involved in reproduction",0.106,1.3626,0.832,0.553,"cytoskeleton organization"),
#
c("GO:0006818","hydrogen transport",0.884,2.7486,0.833,0.400,"cytoskeleton organization"),
#
c("GO:0051235","maintenance of location",0.034,2.0559,0.856,0.545,"cytoskeleton organization"),
#
c("GO:0016044","cellular membrane organization",0.245,1.2654,0.700,0.656,"cytoskeleton organization"),
#
c("GO:0021700","developmental maturation",0.031,1.1148,0.789,0.547,"cytoskeleton organization"),
#
c("GO:0016337","cell-cell adhesion",0.088,1.2908,0.844,0.625,"cytoskeleton organization"),
#
c("GO:0030721","spectrosome organization",0.000,2.0520,0.778,0.435,"cytoskeleton organization"),
#
c("GO:0007294","germarium-derived oocyte fate determination",0.000,3.1864,0.726,0.134,"cytoskeleton organization"),
#
c("GO:0048610","cellular process involved in reproduction",0.597,1.4523,0.903,0.510,"cytoskeleton organization"),
#
c("GO:0006890","retrograde vesicle-mediated transport, Golgi to ER",0.007,1.4951,0.829,0.508,"cytoskeleton organization"),
#
c("GO:0007265","Ras protein signal transduction",0.169,2.6557,0.767,0.606,"cytoskeleton organization"),
#
c("GO:0070271","protein complex biogenesis",0.661,1.0762,0.778,0.568,"cytoskeleton organization"),
#
c("GO:0007264","small GTPase mediated signal transduction",0.405,3.3019,0.754,0.308,"cytoskeleton organization"),
#
c("GO:0019953","sexual reproduction",0.079,1.5435,0.932,0.320,"cytoskeleton organization"),
#
c("GO:0010038","response to metal ion",0.103,1.0356,0.945,0.608,"cytoskeleton organization"),
#
c("GO:0045995","regulation of embryonic development",0.013,1.2753,0.716,0.691,"cytoskeleton organization"),
#
c("GO:0008637","apoptotic mitochondrial changes",0.007,1.3290,0.714,0.596,"cytoskeleton organization"),
#
c("GO:0035317","imaginal disc-derived wing hair organization",0.001,1.6981,0.667,0.570,"cytoskeleton organization"),
#
c("GO:0044087","regulation of cellular component biogenesis",0.142,3.9914,0.734,0.449,"cytoskeleton organization"),
#
c("GO:0016192","vesicle-mediated transport",0.652,1.1679,0.952,0.325,"cytoskeleton organization"),
#
c("GO:0045454","cell redox homeostasis",0.592,5.0867,0.738,0.226,"cytoskeleton organization"),
#
c("GO:0010035","response to inorganic substance",0.221,2.3199,0.949,0.347,"cytoskeleton organization"),
#
c("GO:0030865","cortical cytoskeleton organization",0.005,2.4892,0.694,0.598,"cytoskeleton organization"),
#
c("GO:0045478","fusome organization",0.000,2.0520,0.765,0.468,"cytoskeleton organization"),
#
c("GO:0015985","energy coupled proton transport, down electrochemical gradient",0.595,3.0915,0.798,0.242,"cytoskeleton organization"),
#
c("GO:0060047","heart contraction",0.017,1.6981,0.790,0.524,"cytoskeleton organization"),
#
c("GO:0008104","protein localization",1.977,1.7869,0.928,0.322,"cytoskeleton organization"),
#
c("GO:0060711","labyrinthine layer development",0.005,1.4015,0.767,0.644,"cytoskeleton organization"),
#
c("GO:0007155","cell adhesion",0.622,1.6206,0.823,0.243,"cytoskeleton organization"),
#
c("GO:0002165","instar larval or pupal development",0.007,1.3760,0.772,0.694,"cytoskeleton organization"),
#
c("GO:0032504","multicellular organism reproduction",0.084,1.2534,0.842,0.576,"cytoskeleton organization"),
#
c("GO:0031034","myosin filament assembly",0.001,1.9553,0.688,0.532,"cytoskeleton organization"),
#
c("GO:0031033","myosin filament organization",0.001,1.9553,0.709,0.567,"cytoskeleton organization"),
#
c("GO:0043933","macromolecular complex subunit organization",1.196,2.8589,0.761,0.579,"cytoskeleton organization"),
#
c("GO:0045103","intermediate filament-based process",0.003,1.1624,0.872,0.151,"cytoskeleton organization"),
#
c("GO:0045104","intermediate filament cytoskeleton organization",0.003,1.2714,0.700,0.598,"cytoskeleton organization"),
#
c("GO:0007566","embryo implantation",0.004,1.4951,0.747,0.619,"cytoskeleton organization"),
#
c("GO:0001539","ciliary or flagellar motility",0.444,2.5042,0.812,0.276,"cytoskeleton organization"),
#
c("GO:0009791","post-embryonic development",0.053,1.1678,0.750,0.631,"cytoskeleton organization"),
#
c("GO:0007017","microtubule-based process",0.294,5.4437,0.835,0.208,"cytoskeleton organization"),
#
c("GO:0007016","cytoskeletal anchoring at plasma membrane",0.003,2.5241,0.633,0.568,"cytoskeleton organization"),
#
c("GO:0001763","morphogenesis of a branching structure",0.028,1.5036,0.761,0.544,"cytoskeleton organization"),
#
c("GO:0048667","cell morphogenesis involved in neuron differentiation",0.053,1.3765,0.598,0.676,"cytoskeleton organization"),
#
c("GO:0051591","response to cAMP",0.004,1.5911,0.950,0.694,"cytoskeleton organization"),
#
c("GO:0006979","response to oxidative stress",0.274,1.3131,0.959,0.354,"cytoskeleton organization"),
#
c("GO:0007517","muscle organ development",0.045,1.8117,0.731,0.429,"cytoskeleton organization"),
#
c("GO:0007444","imaginal disc development",0.007,1.6491,0.767,0.653,"cytoskeleton organization"),
#
c("GO:0051129","negative regulation of cellular component organization",0.071,1.5830,0.655,0.603,"cytoskeleton organization"),
#
c("GO:0030029","actin filament-based process",0.123,7.4921,0.844,0.194,"cytoskeleton organization"),
#
c("GO:0030030","cell projection organization",0.456,2.4575,0.692,0.619,"cytoskeleton organization"),
#
c("GO:0034220","ion transmembrane transport",1.746,2.7158,0.787,0.631,"cytoskeleton organization"),
#
c("GO:0034614","cellular response to reactive oxygen species",0.088,2.1264,0.799,0.601,"cytoskeleton organization"),
#
c("GO:0006928","cellular component movement",0.674,1.5740,0.825,0.246,"cytoskeleton organization"),
#
c("GO:0006911","phagocytosis, engulfment",0.004,1.8754,0.744,0.374,"cytoskeleton organization"),
#
c("GO:0006901","vesicle coating",0.010,1.4081,0.687,0.619,"cytoskeleton organization"),
#
c("GO:0048754","branching morphogenesis of an epithelial tube",0.022,1.3552,0.751,0.616,"cytoskeleton organization"),
#
c("GO:0007626","locomotory behavior",0.022,1.5859,0.969,0.000,"locomotory behavior"),
#
c("GO:0022610","biological adhesion",2.091,1.5544,0.993,0.000,"biological adhesion"),
#
c("GO:0015980","energy derivation by oxidation of organic compounds",3.979,7.7721,0.873,0.022,"energy derivation by oxidation of organic compounds"),
#
c("GO:0055114","oxidation-reduction process",16.017,3.5317,0.922,0.275,"energy derivation by oxidation of organic compounds"),
#
c("GO:0043648","dicarboxylic acid metabolic process",1.097,1.2032,0.873,0.429,"energy derivation by oxidation of organic compounds"),
#
c("GO:0009074","aromatic amino acid family catabolic process",0.045,1.5788,0.842,0.662,"energy derivation by oxidation of organic compounds"),
#
c("GO:0010608","posttranscriptional regulation of gene expression",0.540,1.5996,0.835,0.354,"energy derivation by oxidation of organic compounds"),
#
c("GO:0009109","coenzyme catabolic process",0.036,3.5331,0.889,0.493,"energy derivation by oxidation of organic compounds"),
#
c("GO:0006732","coenzyme metabolic process",2.516,3.3116,0.904,0.642,"energy derivation by oxidation of organic compounds"),
#
c("GO:0009205","purine ribonucleoside triphosphate metabolic process",4.744,4.6615,0.792,0.293,"energy derivation by oxidation of organic compounds"),
#
c("GO:0006570","tyrosine metabolic process",0.048,1.8184,0.877,0.664,"energy derivation by oxidation of organic compounds"),
#
c("GO:0006559","L-phenylalanine catabolic process",0.017,3.0255,0.849,0.623,"energy derivation by oxidation of organic compounds"),
#
c("GO:0006558","L-phenylalanine metabolic process",0.058,2.8229,0.875,0.336,"energy derivation by oxidation of organic compounds"),
#
c("GO:0006112","energy reserve metabolic process",0.134,2.2693,0.904,0.564,"energy derivation by oxidation of organic compounds"),
#
c("GO:0006108","malate metabolic process",0.113,1.8184,0.894,0.354,"energy derivation by oxidation of organic compounds"),
#
c("GO:0006099","tricarboxylic acid cycle",0.480,3.2418,0.887,0.648,"energy derivation by oxidation of organic compounds"),
#
c("GO:0006090","pyruvate metabolic process",0.213,4.8013,0.889,0.206,"energy derivation by oxidation of organic compounds"),
#
c("GO:0046164","alcohol catabolic process",0.099,6.6383,0.867,0.137,"energy derivation by oxidation of organic compounds"),
#
c("GO:0006084","acetyl-CoA metabolic process",0.129,3.9626,0.883,0.300,"energy derivation by oxidation of organic compounds"),
#
c("GO:0009894","regulation of catabolic process",0.220,1.6654,0.839,0.346,"energy derivation by oxidation of organic compounds"),
#
c("GO:0051187","cofactor catabolic process",0.051,3.3990,0.891,0.466,"energy derivation by oxidation of organic compounds"),
#
c("GO:0042743","hydrogen peroxide metabolic process",0.044,1.5772,0.959,0.044,"hydrogen peroxide metabolism"),
#
c("GO:0008380","RNA splicing",0.164,8.7212,0.881,0.056,"RNA splicing"),
#
c("GO:0032268","regulation of cellular protein metabolic process",0.675,1.6298,0.773,0.596,"RNA splicing"),
#
c("GO:0016071","mRNA metabolic process",0.651,6.2111,0.881,0.292,"RNA splicing"),
#
c("GO:0051340","regulation of ligase activity",0.004,1.9638,0.883,0.475,"RNA splicing"),
#
c("GO:0043603","cellular amide metabolic process",0.824,1.1508,0.919,0.130,"RNA splicing"),
#
c("GO:0045429","positive regulation of nitric oxide biosynthetic process",0.003,1.4015,0.850,0.508,"RNA splicing"),
#
c("GO:0010498","proteasomal protein catabolic process",0.047,1.4353,0.857,0.671,"RNA splicing"),
#
c("GO:0051443","positive regulation of ubiquitin-protein ligase activity",0.002,2.5042,0.793,0.276,"RNA splicing"),
#
c("GO:0043433","negative regulation of sequence-specific DNA binding transcription factor activity",0.012,1.5911,0.800,0.489,"RNA splicing"),
#
c("GO:0043392","negative regulation of DNA binding",0.031,1.2565,0.877,0.652,"RNA splicing"),
#
c("GO:0051084","'de novo' posttranslational protein folding",0.016,1.4015,0.906,0.541,"RNA splicing"),
#
c("GO:0006412","translation",5.031,4.3625,0.838,0.561,"RNA splicing"),
#
c("GO:0006414","translational elongation",0.839,4.9747,0.861,0.455,"RNA splicing"),
#
c("GO:0006396","RNA processing",2.803,1.7651,0.861,0.388,"RNA splicing"),
#
c("GO:0006397","mRNA processing",0.542,7.1481,0.866,0.597,"RNA splicing"),
#
c("GO:0006458","'de novo' protein folding",0.016,2.2993,0.906,0.322,"RNA splicing"),
#
c("GO:0006457","protein folding",0.852,5.0560,0.881,0.148,"RNA splicing"),
#
c("GO:0031145","anaphase-promoting complex-dependent proteasomal ubiquitin-dependent protein catabolic process",0.006,1.9032,0.871,0.301,"RNA splicing"),
#
c("GO:0009820","alkaloid metabolic process",0.003,2.0805,0.941,0.070,"alkaloid metabolism"),
#
c("GO:0006749","glutathione metabolic process",0.128,1.8217,0.871,0.457,"alkaloid metabolism"),
#
c("GO:0006769","nicotinamide metabolic process",0.000,2.1820,0.925,0.118,"alkaloid metabolism"),
#
c("GO:0051186","cofactor metabolic process",3.252,1.9611,0.944,0.072,"cofactor metabolism"),
#
c("GO:0006091","generation of precursor metabolites and energy",5.328,14.8447,0.941,0.078,"generation of precursor metabolites and energy"))
stuff <- data.frame(revigo.data);
names(stuff) <- revigo.names;
stuff$abslog10pvalue <- as.numeric( as.character(stuff$abslog10pvalue) );
#
stuff$freqInDbPercent <- as.numeric( as.character(stuff$freqInDbPercent) );
#
stuff$uniqueness <- as.numeric( as.character(stuff$uniqueness) );
#
stuff$dispensability <- as.numeric( as.character(stuff$dispensability) )
pdf( file="revigo_treemap.pdf", width=16, height=9 ) # width and height are in inches
tmPlot(
#
	stuff,
#
	index = c("representative","description"),
#
	vSize = "abslog10pvalue",
#
	type = "categorical",
#
	vColor = "representative",
#
	title = "REVIGO Gene Ontology treemap",
#
	inflate.labels = FALSE,      # set this to TRUE for space-filling group labels - good for posters
#
	lowerbound.cex.labels = 0,   # try to draw as many labels as possible (still, some small squares may not get a label)
#
	bg.labels = "#CCCCCCAA",     # define background color of group labels
#
												       # "#CCCCCC00" is fully transparent, "#CCCCCCAA" is semi-transparent grey, NA is opaque
#
	position.legend = "none"
#
)
dev.off()