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0
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1 /home/pjb/galaxy-tools/ceas/test.tool_dependencies.ceas/bx_python/0.7.1/lib/python2.7/site-packages/pkg_resources.py:1054: UserWarning: /home/pjb/.python-eggs is writable by group/others and vulnerable to attack when used with get_resource_filename. Consider a more secure location (set with .set_extraction_path or the PYTHON_EGG_CACHE environment variable).
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2 warnings.warn(msg, UserWarning)
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3 ceasBW -- 0.9.9.7 (package version 1.0.2)
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4 /home/pjb/galaxy-tools/ceas/test.tool_dependencies.ceas/bx_python/0.7.1/lib/python2.7/site-packages/pkg_resources.py:1054: UserWarning: /home/pjb/.python-eggs is writable by group/others and vulnerable to attack when used with get_resource_filename. Consider a more secure location (set with .set_extraction_path or the PYTHON_EGG_CACHE environment variable).
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5 warnings.warn(msg, UserWarning)
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6 INFO @ Tue, 23 Jun 2015 13:03:32:
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7 # ARGUMENTS:
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8 # name = ceas
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9 # gene annotation table = galGal3.refGene
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10 # BED file = ceas_in.bed
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11 # WIG file = ceas_in.bigwig
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12 # extra BED file = None
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13 # ChIP annotation = On
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14 # gene-centered annotation = On
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15 # average profiling = On
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16 # dump profiles = Off
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17 # re-annotation for genome background (ChIP region annotation) = False
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18 # promoter sizes (ChIP region annotation) = 1000,2000,3000 bp
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19 # downstream sizes (ChIP region annotation) = 1000,2000,3000 bp
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20 # bidrectional promoter sizes (ChIP region annotation) = 2500,5000 bp
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21 # span size (gene-centered annotation) = 3000 bp
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22 # profiling resolution (average profiling) = 50 bp
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23 # relative distance wrt TSS and TTS (average profiling) = 3000 bp
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24 INFO @ Tue, 23 Jun 2015 13:03:32: #1 read the gene table...
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25 INFO @ Tue, 23 Jun 2015 13:03:32: #2 read the bed file of ChIP regions...
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26 INFO @ Tue, 23 Jun 2015 13:03:32: #3 perform gene-centered annotation...
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27 INFO @ Tue, 23 Jun 2015 13:03:32: #4 See ceas.xls for gene-centered annotation!
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28 INFO @ Tue, 23 Jun 2015 13:03:32: #5 read the pre-computed genome bg annotation...
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29 INFO @ Tue, 23 Jun 2015 13:03:32: #6 perform ChIP region annotation...
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30 INFO @ Tue, 23 Jun 2015 13:03:32: #7 write a R script of ChIP region annotation...
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31 INFO @ Tue, 23 Jun 2015 13:03:32: #8-1 run wig profiling of chr26...
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32 INFO @ Tue, 23 Jun 2015 13:03:32: #9 append an R script of wig profiling...
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33
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34 R version 3.1.2 (2014-10-31) -- "Pumpkin Helmet"
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35 Copyright (C) 2014 The R Foundation for Statistical Computing
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36 Platform: x86_64-redhat-linux-gnu (64-bit)
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37
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38 R is free software and comes with ABSOLUTELY NO WARRANTY.
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39 You are welcome to redistribute it under certain conditions.
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40 Type 'license()' or 'licence()' for distribution details.
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41
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42 Natural language support but running in an English locale
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43
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44 R is a collaborative project with many contributors.
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45 Type 'contributors()' for more information and
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46 'citation()' on how to cite R or R packages in publications.
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47
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48 Type 'demo()' for some demos, 'help()' for on-line help, or
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49 'help.start()' for an HTML browser interface to help.
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50 Type 'q()' to quit R.
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51
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52 > # ARGUMENTS:
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53 > # name = ceas
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54 > # gene annotation table = galGal3.refGene
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55 > # BED file = ceas_in.bed
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56 > # WIG file = ceas_in.bigwig
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57 > # extra BED file = None
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58 > # ChIP annotation = On
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59 > # gene-centered annotation = On
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60 > # average profiling = On
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61 > # dump profiles = Off
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62 > # re-annotation for genome background (ChIP region annotation) = False
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63 > # promoter sizes (ChIP region annotation) = 1000,2000,3000 bp
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64 > # downstream sizes (ChIP region annotation) = 1000,2000,3000 bp
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65 > # bidrectional promoter sizes (ChIP region annotation) = 2500,5000 bp
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66 > # span size (gene-centered annotation) = 3000 bp
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67 > # profiling resolution (average profiling) = 50 bp
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68 > # relative distance wrt TSS and TTS (average profiling) = 3000 bp
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69 > pdf("ceas.pdf",height=11.5,width=8.5)
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70 >
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71 > # 13:03:32 Tue, 23 Jun 2015
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72 > #
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73 > # ChIP annotation
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74 > #
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75 >
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76 >
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77 > #
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78 > # Chromosomal Distribution
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79 > #
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80 >
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81 > par(mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2))
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82 > r0<-c(100.0)
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83 > r1<-c(100.0)
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84 > height<-rbind(r0,r1)
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85 > names=c("26")
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86 > mp<-barplot(height=height,names=names,beside=TRUE,horiz=TRUE,col=c("#5FA1C1","#EB9D86"),main="Chromosomal Distribution of ChIP Regions",xlab="Percentage %",ylab="Chromosome",border=FALSE,xlim=c(0.000000,183.333333),cex.names=1)
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87 > text(x=c(100.0),y=mp[1,],label=c("100.0 %"),pos=4,offset=0.2,cex=0.9)
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88 > text(x=c(100.0),y=mp[2,],label=c("100.0 % (<=4.9e-324)"),pos=4,offset=0.2,cex=0.9)
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89 > legend("right",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n")
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90 >
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91 > #
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92 > # Promoter,Bipromoter,Downstream, Gene and Regions of interest
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93 > #
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94 >
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95 > par(mfrow=c(4, 1),mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2))
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96 > r0<-c(1.8532425688606797, 3.616851183410451, 5.322318854623416)
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97 > r1<-c(0.0, 0.0, 0.0)
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98 > height<-rbind(r0,r1)
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99 > names=c("<=1000 bp","<=2000 bp","<=3000 bp")
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100 > mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Promoter",ylab="Percentage %",border=FALSE,ylim=c(0.000000,9.757585),cex.names=1)
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101 > text(x=mp[1,],y=c(1.8532425688606797, 3.616851183410451, 5.322318854623416),label=c("1.9 %","3.6 %","5.3 %"),pos=3,offset=0.2)
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102 > text(x=mp[2,],y=c(0.0, 0.0, 0.0),label=c("0.000 %
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103 + (0.981)","0.000 %
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104 + (0.964)","0.000 %
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105 + (0.947)"),pos=3,offset=0.2)
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106 > legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n")
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107 > r0<-c(0.03876062889120376, 0.03876062889120376)
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108 > r1<-c(0.0, 0.0)
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109 > height<-rbind(r0,r1)
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110 > names=c("<=2500 bp","<=5000 bp")
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111 > mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Bidirectional Promoter",ylab="Percentage %",border=FALSE,ylim=c(0.000000,0.071061),cex.names=1)
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112 > text(x=mp[1,],y=c(0.03876062889120376, 0.03876062889120376),label=c("0.04 %","0.04 %"),pos=3,offset=0.2)
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113 > text(x=mp[2,],y=c(0.0, 0.0),label=c("0.000 %
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114 + (1.000)","0.000 %
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115 + (1.000)"),pos=3,offset=0.2)
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116 > legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n")
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117 > r0<-c(1.8290171758036773, 3.4690762857627364, 4.980740812519683)
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118 > r1<-c(0.0, 0.0, 0.0)
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119 > height<-rbind(r0,r1)
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120 > names=c("<=1000 bp","<=2000 bp","<=3000 bp")
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121 > mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Downstream",ylab="Percentage %",border=FALSE,ylim=c(0.000000,9.131358),cex.names=1)
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122 > text(x=mp[1,],y=c(1.8290171758036773, 3.4690762857627364, 4.980740812519683),label=c("1.8 %","3.5 %","5.0 %"),pos=3,offset=0.2)
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123 > text(x=mp[2,],y=c(0.0, 0.0, 0.0),label=c("0.000 %
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124 + (0.982)","0.000 %
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125 + (0.965)","0.000 %
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126 + (0.950)"),pos=3,offset=0.2)
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127 > legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n")
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128 > r0<-c(0.2034933016788197, 1.3978051793890356, 2.359553283752029, 19.734005184234114, 23.694856949054)
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129 > r1<-c(0.0, 0.0, 0.0, 0.0, 0.0)
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130 > height<-rbind(r0,r1)
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131 > names=c("5'UTR","3'UTR","Coding Exon","Intron","All")
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132 > mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Gene",ylab="Percentage %",border=FALSE,ylim=c(0.000000,43.440571),cex.names=1)
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133 > text(x=mp[1,],y=c(0.2034933016788197, 1.3978051793890356, 2.359553283752029, 19.734005184234114, 23.694856949054),label=c("0.2 %","1.4 %","2.4 %","19.7 %","23.7 %"),pos=3,offset=0.2)
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134 > text(x=mp[2,],y=c(0.0, 0.0, 0.0, 0.0, 0.0),label=c("0.000 %
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135 + (0.998)","0.000 %
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136 + (0.986)","0.000 %
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137 + (0.976)","0.000 %
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138 + (0.803)","0.000 %
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139 + (0.763)"),pos=3,offset=0.2)
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140 > legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n")
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141 >
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142 > #
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143 > # Distribution of Genome and ChIP regions over cis-regulatory element
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144 > # Note that the x may be modified for better graphics in case a value is too small
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145 > # Thus, look at the labels of the pie chart to get the real percentage values
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146 > #
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147 >
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148 > par(mfcol=c(2, 2),mar=c(3, 3, 4, 2.8),oma=c(4, 2, 4, 2))
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149 > x<-c(0.018532,0.017055,0.016037,0.017830,0.015092,0.014051,0.010000,0.013833,0.023014,0.192592,0.670292)
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150 > pie(x=x,labels=c("1.9 %","1.7 %","1.6 %","1.8 %","1.5 %","1.4 %","0.2 %","1.4 %","2.3 %","19.3 %","67.0 %"),main="Genome",col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),clockwise=TRUE,border=FALSE,radius=0.9,cex=0.8,init.angle=90,density=100)
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151 > x<-c(0.000000,1.000000)
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152 > y<-c(0.000000,1.000000)
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153 > plot(x, y,type="n",main="",xlab="",ylab="",frame=FALSE,axes=FALSE,xaxt="s",yaxt="s")
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154 > legend("top",legend=c("Promoter (<=1000 bp): 1.9 %","Promoter (1000-2000 bp): 1.7 %","Promoter (2000-3000 bp): 1.6 %","Downstream (<=1000 bp): 1.8 %","Downstream (1000-2000 bp): 1.5 %","Downstream (2000-3000 bp): 1.4 %","5'UTR: 0.2 %","3'UTR: 1.4 %","Coding exon: 2.3 %","Intron: 19.3 %","Distal intergenic: 67.0 %"),col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),pch=15,bty="n")
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155 > x<-c(0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,1.000000)
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156 > pie(x=x,labels=c("0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","100.0 %"),main="ChIP",col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),clockwise=TRUE,border=FALSE,radius=0.9,cex=0.8,init.angle=90,density=100)
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157 > x<-c(0.000000,1.000000)
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158 > y<-c(0.000000,1.000000)
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159 > plot(x, y,type="n",main="",xlab="",ylab="",frame=FALSE,axes=FALSE,xaxt="s",yaxt="s")
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160 > legend("top",legend=c("Promoter (<=1000 bp): 0.000 %","Promoter (1000-2000 bp): 0.000 %","Promoter (2000-3000 bp): 0.000 %","Downstream (<=1000 bp): 0.000 %","Downstream (1000-2000 bp): 0.000 %","Downstream (2000-3000 bp): 0.000 %","5'UTR: 0.000 %","3'UTR: 0.000 %","Coding exon: 0.000 %","Intron: 0.000 %","Distal intergenic: 100.0 %"),col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),pch=15,bty="n")
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161 >
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162 > #
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163 > # ChIP regions over the genome
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164 > #
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165 >
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166 > par(mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2))
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167 > layout(matrix(c(1, 0, 2, 2), 2, 2, byrow = TRUE),widths=c(1, 1),heights=c(1, 5))
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168 > x<-c(0.000000,0.000000)
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169 > y<-c(0.000000,1.000000)
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170 > plot(x, y,type="n",main="Distribution of Peak Heights",xlab="",ylab="",xlim=c(0.000000,0.000000),ylim=c(0.000000,1.000000),frame=FALSE,xaxt="s",yaxt="n",cex=0.9)
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171 > x<-c(0.000000,0.000000,0.000000,0.000000)
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172 > y<-c(0.000000,0.000000,1.000000,1.000000)
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173 > polygon(x,y,col=c("black"))
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174 > x <- c(0.000000)
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175 > y<-c(0.800000)
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176 > lines(x, y,xlim=c(0, 0.0),ylim=c(0, 1),type="l",col=c("cyan"),lwd=2)
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177 > x<-c(0.000000,4127518.000000)
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178 > y<-c(0.855556,1.144444)
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179 > plot(x, y,type="n",main="ChIP Regions (Peaks) over Chromosomes",xlab="Chromosome Size (bp)",ylab="Chromosome",xlim=c(0.000000,4127518.000000),ylim=c(0.855556,1.144444),frame=FALSE,xaxt="s",yaxt="n")
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180 > start <- c(4119129)
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181 > end <- c(4119130)
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182 > vals <- c(0.0)
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183 > vals[vals > 0.0] <- 0.0
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184 > vals[vals < 0] <- 0
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185 > heights <- 0.288889 * ((vals - 0)/(0.0 - 0)) + 0.855555555556
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186 > for (i in 1:length(heights)) {
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187 + polygon(x=c(start[i], end[i], end[i], start[i]), y=c(0.855555555556, 0.855555555556, heights[i], heights[i]), col=c("#CC0000"), border=c("#CC0000"))
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188 + }
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189 > mtext("26",side=2,line=0,outer=FALSE,at=1.0)
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190 > par(mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2))
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191 > layout(matrix(c(1, 2, 3, 3, 4, 5), 3, 2, byrow = TRUE),widths=c(1, 1),heights=c(1, 1, 1))
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192 > x<-c(-3000.000000,-2950.000000,-2900.000000,-2850.000000,-2800.000000,-2750.000000,-2700.000000,-2650.000000,-2600.000000,-2550.000000,-2500.000000,-2450.000000,-2400.000000,-2350.000000,-2300.000000,-2250.000000,-2200.000000,-2150.000000,-2100.000000,-2050.000000,-2000.000000,-1950.000000,-1900.000000,-1850.000000,-1800.000000,-1750.000000,-1700.000000,-1650.000000,-1600.000000,-1550.000000,-1500.000000,-1450.000000,-1400.000000,-1350.000000,-1300.000000,-1250.000000,-1200.000000,-1150.000000,-1100.000000,-1050.000000,-1000.000000,-950.000000,-900.000000,-850.000000,-800.000000,-750.000000,-700.000000,-650.000000,-600.000000,-550.000000,-500.000000,-450.000000,-400.000000,-350.000000,-300.000000,-250.000000,-200.000000,-150.000000,-100.000000,-50.000000,0.000000,50.000000,100.000000,150.000000,200.000000,250.000000,300.000000,350.000000,400.000000,450.000000,500.000000,550.000000,600.000000,650.000000,700.000000,750.000000,800.000000,850.000000,900.000000,950.000000,1000.000000,1050.000000,1100.000000,1150.000000,1200.000000,1250.000000,1300.000000,1350.000000,1400.000000,1450.000000,1500.000000,1550.000000,1600.000000,1650.000000,1700.000000,1750.000000,1800.000000,1850.000000,1900.000000,1950.000000,2000.000000,2050.000000,2100.000000,2150.000000,2200.000000,2250.000000,2300.000000,2350.000000,2400.000000,2450.000000,2500.000000,2550.000000,2600.000000,2650.000000,2700.000000,2750.000000,2800.000000,2850.000000,2900.000000,2950.000000,3000.000000)
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193 > y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000)
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194 > plot(x, y,type="l",main="Average Profile near TSS",xlab="Relative Distance to TSS (bp)",ylab="Average Profile",col=c("#C8524D"),xaxt="s",yaxt="s",lwd=2)
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195 > abline(v=0.000000,lty=2,col=c("black"))
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196 > x<-c(-3000.000000,-2950.000000,-2900.000000,-2850.000000,-2800.000000,-2750.000000,-2700.000000,-2650.000000,-2600.000000,-2550.000000,-2500.000000,-2450.000000,-2400.000000,-2350.000000,-2300.000000,-2250.000000,-2200.000000,-2150.000000,-2100.000000,-2050.000000,-2000.000000,-1950.000000,-1900.000000,-1850.000000,-1800.000000,-1750.000000,-1700.000000,-1650.000000,-1600.000000,-1550.000000,-1500.000000,-1450.000000,-1400.000000,-1350.000000,-1300.000000,-1250.000000,-1200.000000,-1150.000000,-1100.000000,-1050.000000,-1000.000000,-950.000000,-900.000000,-850.000000,-800.000000,-750.000000,-700.000000,-650.000000,-600.000000,-550.000000,-500.000000,-450.000000,-400.000000,-350.000000,-300.000000,-250.000000,-200.000000,-150.000000,-100.000000,-50.000000,0.000000,50.000000,100.000000,150.000000,200.000000,250.000000,300.000000,350.000000,400.000000,450.000000,500.000000,550.000000,600.000000,650.000000,700.000000,750.000000,800.000000,850.000000,900.000000,950.000000,1000.000000,1050.000000,1100.000000,1150.000000,1200.000000,1250.000000,1300.000000,1350.000000,1400.000000,1450.000000,1500.000000,1550.000000,1600.000000,1650.000000,1700.000000,1750.000000,1800.000000,1850.000000,1900.000000,1950.000000,2000.000000,2050.000000,2100.000000,2150.000000,2200.000000,2250.000000,2300.000000,2350.000000,2400.000000,2450.000000,2500.000000,2550.000000,2600.000000,2650.000000,2700.000000,2750.000000,2800.000000,2850.000000,2900.000000,2950.000000,3000.000000)
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197 > y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000)
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198 > plot(x, y,type="l",main="Average Profile near TTS",xlab="Relative Distance to TTS (bp)",ylab="Average Profile",col=c("#C8524D"),xaxt="s",yaxt="s",lwd=2)
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199 > abline(v=0.000000,lty=2,col=c("black"))
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200 > x<-c(-1000.000000,-950.000000,-900.000000,-850.000000,-800.000000,-750.000000,-700.000000,-650.000000,-600.000000,-550.000000,-500.000000,-450.000000,-400.000000,-350.000000,-300.000000,-250.000000,-200.000000,-150.000000,-100.000000,-50.000000,0.000000,50.000000,100.000000,150.000000,200.000000,250.000000,300.000000,350.000000,400.000000,450.000000,500.000000,550.000000,600.000000,650.000000,700.000000,750.000000,800.000000,850.000000,900.000000,950.000000,1000.000000,1050.000000,1100.000000,1150.000000,1200.000000,1250.000000,1300.000000,1350.000000,1400.000000,1450.000000,1500.000000,1550.000000,1600.000000,1650.000000,1700.000000,1750.000000,1800.000000,1850.000000,1900.000000,1950.000000,2000.000000,2050.000000,2100.000000,2150.000000,2200.000000,2250.000000,2300.000000,2350.000000,2400.000000,2450.000000,2500.000000,2550.000000,2600.000000,2650.000000,2700.000000,2750.000000,2800.000000,2850.000000,2900.000000,2950.000000,3000.000000,3050.000000,3100.000000,3150.000000,3200.000000,3250.000000,3300.000000,3350.000000,3400.000000,3450.000000,3500.000000,3550.000000,3600.000000,3650.000000,3700.000000,3750.000000,3800.000000,3850.000000,3900.000000,3950.000000,4000.000000)
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201 > y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000)
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202 > plot(x, y,type="l",main="Average Gene Profile",xlab="Upstream (bp), 3000 bp of Meta-gene, Downstream (bp)",ylab="Average Profile",col=c("#C8524D"),xaxt="s",yaxt="s",lwd=2)
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203 > abline(v=0.000000,lty=2,col=c("black"))
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204 > abline(v=3000.000000,lty=2,col=c("black"))
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205 > x<-c(0.000000,3.333333,6.666667,10.000000,13.333333,16.666667,20.000000,23.333333,26.666667,30.000000,33.333333,36.666667,40.000000,43.333333,46.666667,50.000000,53.333333,56.666667,60.000000,63.333333,66.666667,70.000000,73.333333,76.666667,80.000000,83.333333,86.666667,90.000000,93.333333,96.666667,100.000000)
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206 > y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000)
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207 > plot(x, y,type="l",main="Average Concatenated Exon Profile",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,20000.000000),xaxt="s",yaxt="s",lwd=2)
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208 > x<-c(0.000000,3.333333,6.666667,10.000000,13.333333,16.666667,20.000000,23.333333,26.666667,30.000000,33.333333,36.666667,40.000000,43.333333,46.666667,50.000000,53.333333,56.666667,60.000000,63.333333,66.666667,70.000000,73.333333,76.666667,80.000000,83.333333,86.666667,90.000000,93.333333,96.666667,100.000000)
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209 > y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000)
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210 > plot(x, y,type="l",main="Average Concatenated Intron Profile",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,20000.000000),xaxt="s",yaxt="s",lwd=2)
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211 > par(mfrow=c(3, 2),mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2))
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212 > x<-c(-3.000000,3.000000)
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213 > y<-c(0.000000,1.000000)
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214 > plot(x, y,type="n",main="",xlab="",ylab="",xlim=c(-3.000000,3.000000),ylim=c(0.000000,1.000000),axes=FALSE,xaxt="s",yaxt="s")
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215 > x<-c(-3.000000,3.000000)
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216 > y<-c(0.000000,1.000000)
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217 > plot(x, y,type="n",main="",xlab="",ylab="",xlim=c(-3.000000,3.000000),ylim=c(0.000000,1.000000),axes=FALSE,xaxt="s",yaxt="s")
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218 > x<-c(-3.000000,3.000000)
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219 > y<-c(0.000000,1.000000)
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220 > plot(x, y,type="n",main="",xlab="",ylab="",xlim=c(-3.000000,3.000000),ylim=c(0.000000,1.000000),axes=FALSE,xaxt="s",yaxt="s")
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221 > x<-c(-3.000000,3.000000)
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222 > y<-c(0.000000,1.000000)
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223 > plot(x, y,type="n",main="",xlab="",ylab="",xlim=c(-3.000000,3.000000),ylim=c(0.000000,1.000000),axes=FALSE,xaxt="s",yaxt="s")
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224 > x<-c(-3.000000,3.000000)
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225 > y<-c(0.000000,1.000000)
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226 > plot(x, y,type="n",main="",xlab="",ylab="",xlim=c(-3.000000,3.000000),ylim=c(0.000000,1.000000),axes=FALSE,xaxt="s",yaxt="s")
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227 > x<-c(0.000000,4.761905,9.523810,14.285714,19.047619,23.809524,28.571429,33.333333,38.095238,42.857143,47.619048,52.380952,57.142857,61.904762,66.666667,71.428571,76.190476,80.952381,85.714286,90.476190,95.238095,100.000000)
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228 > y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000)
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229 > plot(x, y,type="l",main="Average Intron Profile
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230 + (685 <= length < 2653 bp)",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,24000.000000),xaxt="s",yaxt="s",lwd=2)
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231 > dev.off()
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232 null device
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233 1
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234 >
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235 INFO @ Tue, 23 Jun 2015 13:03:33: #... cong! See ceas.pdf for the graphical results of CEAS!
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