Mercurial > repos > davidvanzessen > shm_csr

comparison pattern_plots.r @ 38:05c62efdc393 draft

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
Uploaded
author davidvanzessen
date Tue, 20 Dec 2016 09:03:15 -0500
parents 81453585dfc3
children a24f8c93583a
comparison
equal deleted inserted replaced
37:767dd9327009 38:05c62efdc393
45 45
46 data1 = melt(t(data1)) 46 data1 = melt(t(data1))
47 47
48 names(data1) = c("Class", "Type", "value") 48 names(data1) = c("Class", "Type", "value")
49 49
50 chk = is.na(data1$value)
51 if(any(chk)){
52 data1[chk, "value"] = 0
53 }
54
50 data1 = data1[order(data1$Type),] 55 data1 = data1[order(data1$Type),]
51 56
52 write.table(data1, plot1.txt, quote=F, sep="\t", na="", row.names=F, col.names=T) 57 write.table(data1, plot1.txt, quote=F, sep="\t", na="", row.names=F, col.names=T)
53 58
54 p = ggplot(data1, aes(Class, value)) + geom_bar(aes(fill=Type), stat="identity", position="dodge", colour = "black") + ylab("% of mutations") + guides(fill=guide_legend(title=NULL)) 59 p = ggplot(data1, aes(Class, value)) + geom_bar(aes(fill=Type), stat="identity", position="dodge", colour = "black") + ylab("% of mutations") + guides(fill=guide_legend(title=NULL))
77 82
78 data2 = melt(t(data2[c("A/T","G/C transitions","G/C transversions"),])) 83 data2 = melt(t(data2[c("A/T","G/C transitions","G/C transversions"),]))
79 84
80 names(data2) = c("Class", "Type", "value") 85 names(data2) = c("Class", "Type", "value")
81 86
87 chk = is.na(data2$value)
88 if(any(chk)){
89 data2[chk, "value"] = 0
90 }
91
82 data2 = data2[order(data2$Type),] 92 data2 = data2[order(data2$Type),]
83 93
84 write.table(data2, plot2.txt, quote=F, sep="\t", na="", row.names=F, col.names=T) 94 write.table(data2, plot2.txt, quote=F, sep="\t", na="", row.names=F, col.names=T)
85 95
86 p = ggplot(data2, aes(x=Class, y=value, fill=Type)) + geom_bar(position="fill", stat="identity", colour = "black") + scale_y_continuous(labels=percent_format()) + guides(fill=guide_legend(title=NULL)) + ylab("% of mutations") 96 p = ggplot(data2, aes(x=Class, y=value, fill=Type)) + geom_bar(position="fill", stat="identity", colour = "black") + scale_y_continuous(labels=percent_format()) + guides(fill=guide_legend(title=NULL)) + ylab("% of mutations")
91 dev.off() 101 dev.off()
92 102
93 data3 = dat[c(5, 6, 8, 17:20),] 103 data3 = dat[c(5, 6, 8, 17:20),]
94 data3 = data3[,names(data3)[grepl("\\.x", names(data3))]] 104 data3 = data3[,names(data3)[grepl("\\.x", names(data3))]]
95 names(data3) = gsub(".x", "", names(data3)) 105 names(data3) = gsub(".x", "", names(data3))
96
97 data3[is.na(data3)] = 0
98 #data3[is.infinite(data3)] = 0
99 106
100 data3["G/C transitions",] = round(data3["Transitions at G C (%)",] / (data3["C",] + data3["G",]) * 100, 1) 107 data3["G/C transitions",] = round(data3["Transitions at G C (%)",] / (data3["C",] + data3["G",]) * 100, 1)
101 108
102 data3["G/C transversions",] = round((data3["Targeting of G C (%)",] - data3["Transitions at G C (%)",]) / (data3["C",] + data3["G",]) * 100, 1) 109 data3["G/C transversions",] = round((data3["Targeting of G C (%)",] - data3["Transitions at G C (%)",]) / (data3["C",] + data3["G",]) * 100, 1)
103 110
112 data3["A/T",is.nan(unlist(data3["A/T",]))] = 0 119 data3["A/T",is.nan(unlist(data3["A/T",]))] = 0
113 data3["A/T",is.infinite(unlist(data3["A/T",]))] = 0 120 data3["A/T",is.infinite(unlist(data3["A/T",]))] = 0
114 121
115 data3 = melt(t(data3[8:10,])) 122 data3 = melt(t(data3[8:10,]))
116 names(data3) = c("Class", "Type", "value") 123 names(data3) = c("Class", "Type", "value")
124
125 chk = is.na(data1$data3)
126 if(any(chk)){
127 data3[chk, "value"] = 0
128 }
117 129
118 data3 = data3[order(data3$Type),] 130 data3 = data3[order(data3$Type),]
119 131
120 write.table(data3, plot3.txt, quote=F, sep="\t", na="", row.names=F, col.names=T) 132 write.table(data3, plot3.txt, quote=F, sep="\t", na="", row.names=F, col.names=T)
121 133