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R/derived.traits.2014.R
In glycanr: Tools for Analysing N-Glycan Data
Defines functions
iudt.translate.2014
ildt.translate.2014
igg.lcms.derived.traits.2014
igg.uplc.derived.traits.2014
# Derived traits for Glycan peaks in IgG for UPLC
# based on paper from 2014.
#
# @references
# Jennifer E. Huffman et al.
# "Comparative Performance of Four Methods for High-throughput Glycosylation Analysis of Immunoglobulin G in Genetic and Epidemiological Research*"
# \doi{10.1074/mcp.M113.037465}
igg.uplc.derived.traits.2014 <- function(data, print.exp.names=FALSE) {
if(print.exp.names){
return(paste0("GP", 1:24))
}
# derived glycans
dteh(data$IGP24 <- with(data, (GP16 + GP18 + GP23)/(GP16 + GP18 + GP23 + GP8 + GP9 + GP14)) * 100)
dteh(data$IGP25 <- with(data, (GP19 + GP24)/(GP19 + GP24 + GP10 + GP11 + GP15)) * 100)
dteh(data$IGP26 <- with(data, (GP16 + GP18 + GP23)/(GP16 + GP18 + GP23 + GP4 + GP8 + GP9 + GP14)) * 100)
dteh(data$IGP27 <- with(data, (GP19 + GP24)/(GP19 + GP24 + GP6 + GP10 + GP11 + GP15)) * 100)
dteh(data$IGP28 <- with(data, GP16/(GP16 + GP8 + GP9)) * 100)
dteh(data$IGP29 <- with(data, GP18/(GP18 + GP14 + GP23)) * 100)
dteh(data$IGP30 <- with(data, GP23/(GP23 + GP14 + GP18)) * 100)
dteh(data$IGP31 <- with(data, GP19/(GP19 + GP15 + GP24)) * 100)
dteh(data$IGP32 <- with(data, GP24/(GP24 + GP15 + GP19)) * 100)
dteh(data$IGP33 <- with(data, (GP16 + GP18 + GP19)/(GP23 + GP24)))
dteh(data$IGP34 <- with(data, (GP16 + GP18)/GP23))
dteh(data$IGP35 <- with(data, GP19/GP24))
dteh(data$IGP36 <- with(data, (GP19 + GP24)/(GP16 + GP18 + GP23)))
dteh(data$IGP37 <- with(data, GP19/(GP16 + GP18)))
dteh(data$IGP38 <- with(data, GP19/(GP16 + GP18 + GP19)) * 100)
dteh(data$IGP39 <- with(data, GP24/GP23))
dteh(data$IGP40 <- with(data, GP24/(GP23 + GP24)) * 100)
# neutral glycans
dteh(GPn <- with(data, GP1 + GP2 + GP4 + GP6 + GP7 + GP8 + GP9 + GP10 + GP11 + GP12 + GP13 + GP14 + GP15))
dteh(data$IGP41 <- with(data, GP1/GPn) * 100)
dteh(data$IGP42 <- with(data, GP2/GPn) * 100)
dteh(data$IGP43 <- with(data, GP4/GPn) * 100)
dteh(data$IGP44 <- with(data, GP5/GPn) * 100)
dteh(data$IGP45 <- with(data, GP6/GPn) * 100)
dteh(data$IGP46 <- with(data, GP7/GPn) * 100)
dteh(data$IGP47 <- with(data, GP8/GPn) * 100)
dteh(data$IGP48 <- with(data, GP9/GPn) * 100)
dteh(data$IGP49 <- with(data, GP10/GPn) * 100)
dteh(data$IGP50 <- with(data, GP11/GPn) * 100)
dteh(data$IGP51 <- with(data, GP12/GPn) * 100)
dteh(data$IGP52 <- with(data, GP13/GPn) * 100)
dteh(data$IGP53 <- with(data, GP14/GPn) * 100)
dteh(data$IGP54 <- with(data, GP15/GPn) * 100)
# neutral derived glycans
dteh(data$IGP55 <- with(data, (IGP41 + IGP42 + IGP43 + IGP45)))
dteh(data$IGP56 <- with(data, (IGP46 + IGP47 + IGP48 + IGP49 + IGP50)))
dteh(data$IGP57 <- with(data, (IGP51 + IGP52 + IGP53 + IGP54)))
dteh(data$IGP58 <- with(data, (IGP41 + IGP43 + IGP45 + IGP47 + IGP48 + IGP49 + IGP50 + IGP53 + IGP54)))
dteh(data$IGP59 <- with(data, (IGP41 + IGP43 + IGP45)/IGP55) * 100)
dteh(data$IGP60 <- with(data, (IGP47 + IGP48 + IGP49 + IGP50)/IGP56) * 100)
dteh(data$IGP61 <- with(data, (IGP53 + IGP54)/IGP57) * 100)
dteh(data$IGP62 <- with(data, (IGP41 + IGP43 + IGP47 + IGP48 + IGP53)))
dteh(data$IGP63 <- with(data, (IGP41 + IGP43)/IGP55) * 100)
dteh(data$IGP64 <- with(data, (IGP47 + IGP48)/IGP56) * 100)
dteh(data$IGP65 <- with(data, IGP53/IGP57) * 100)
dteh(data$IGP66 <- with(data, (IGP45 + IGP49 + IGP50 + IGP54)))
dteh(data$IGP67 <- with(data, IGP45/IGP55) * 100)
dteh(data$IGP68 <- with(data, (IGP49 + IGP50)/IGP56) * 100)
dteh(data$IGP69 <- with(data, IGP54/IGP57) * 100)
dteh(data$IGP70 <- with(data, IGP66/IGP62) * 100)
dteh(data$IGP71 <- with(data, IGP66/IGP58) * 100)
dteh(data$IGP72 <- with(data, IGP62/(IGP52 + IGP66)))
dteh(data$IGP73 <- with(data, IGP52/(IGP62 + IGP66)) * 1000)
dteh(data$IGP74 <- with(data, IGP54/IGP53))
dteh(data$IGP75 <- with(data, IGP54/(IGP53 + IGP54)) * 100)
dteh(data$IGP76 <- with(data, IGP53/(IGP52 + IGP54)))
dteh(data$IGP77 <- with(data, IGP52/(IGP53 + IGP54)) * 1000)
return(data)
}
# Derived traits for Glycan peaks in IgG for LCMS
# based on paper from 2014.
#
# @references
# Jennifer E. Huffman et al.
# "Comparative Performance of Four Methods for High-throughput Glycosylation Analysis of Immunoglobulin G in Genetic and Epidemiological Research*"
# \doi{10.1074/mcp.M113.037465}
igg.lcms.derived.traits.2014 <- function(data, print.exp.names=FALSE) {
if(print.exp.names){
return(c("IgG1_G0F","IgG1_G1F","IgG1_G2F","IgG1_G0FN","IgG1_G1FN",
"IgG1_G2FN","IgG1_G1FS1","IgG1_G2FS1","IgG1_G1FNS1","IgG1_G2FNS1",
"IgG1_G0","IgG1_G1","IgG1_G2","IgG1_G0N","IgG1_G1N",
"IgG1_G2N","IgG1_G1S1","IgG1_G2S1","IgG1_G1NS1","IgG1_G2NS1",
"IgG2_G0F","IgG2_G1F","IgG2_G2F","IgG2_G0FN","IgG2_G1FN",
"IgG2_G2FN","IgG2_G1FS1","IgG2_G2FS1","IgG2_G1FNS1","IgG2_G2FNS1",
"IgG2_G0","IgG2_G1","IgG2_G2","IgG2_G0N","IgG2_G1N",
"IgG2_G2N","IgG2_G1S1","IgG2_G2S1","IgG2_G1NS1","IgG2_G2NS1",
"IgG4_G0F","IgG4_G1F","IgG4_G2F","IgG4_G0FN","IgG4_G1FN",
"IgG4_G2FN","IgG4_G1FS1","IgG4_G2FS1","IgG4_G1FNS1","IgG4_G2FNS1",
"IgG4_G0","IgG4_G1","IgG4_G2","IgG4_G0N","IgG4_G1N",
"IgG4_G2N","IgG4_G1S1","IgG4_G2S1","IgG4_G1NS1","IgG4_G2NS1"))
}
# =======================================
# IgG1 derived traits
# =======================================
dteh(data$LC_IGP21 <- with(data, IgG1_G0F+IgG1_G1F+IgG1_G2F+IgG1_G0FN+IgG1_G1FN+IgG1_G2FN+IgG1_G1FS1+IgG1_G2FS1+IgG1_G1FNS1+IgG1_G2FNS1))
dteh(data$LC_IGP22 <- with(data, IgG1_G0FN+IgG1_G1FN+IgG1_G2FN+IgG1_G1FNS1+IgG1_G2FNS1+IgG1_G0N+IgG1_G1N+IgG1_G2N+IgG1_G1NS1+IgG1_G2NS1))
dteh(data$LC_IGP23 <- with(data, (IgG1_G1F+IgG1_G1FN+IgG1_G1FS1+IgG1_G1FNS1+IgG1_G1+IgG1_G1N+IgG1_G1S1+IgG1_G1NS1)*0.5+(IgG1_G2F+IgG1_G2FN+IgG1_G2FS1+IgG1_G2FNS1+IgG1_G2+IgG1_G2N+IgG1_G2S1+IgG1_G2NS1)))
dteh(data$LC_IGP24 <- with(data, IgG1_G1FS1+IgG1_G2FS1+IgG1_G1FNS1+IgG1_G2FNS1+IgG1_G1S1+IgG1_G2S1+IgG1_G1NS1+IgG1_G2NS1))
dteh(data$LC_IGP25 <- with(data, LC_IGP24/(2*LC_IGP23)*100))
dteh(data$LC_IGP26 <- with(data, (IgG1_G1S1+IgG1_G2S1)/(IgG1_G1+IgG1_G1S1+IgG1_G2+IgG1_G2S1)*100))
dteh(data$LC_IGP27 <- with(data, (IgG1_G1S1+IgG1_G2S1)/(IgG1_G0+IgG1_G1+IgG1_G1S1+IgG1_G2+IgG1_G2S1)*100))
dteh(data$LC_IGP28 <- with(data, IgG1_G1S1/(IgG1_G1+IgG1_G1S1)*100))
dteh(data$LC_IGP29 <- with(data, IgG1_G2S1/(IgG1_G2+IgG1_G2S1)*100))
dteh(data$LC_IGP30 <- with(data, (IgG1_G1NS1+IgG1_G2NS1)/(IgG1_G1N+IgG1_G1NS1+IgG1_G2N+IgG1_G2NS1)*100))
dteh(data$LC_IGP31 <- with(data, (IgG1_G1NS1+IgG1_G2NS1)/(IgG1_G0N+IgG1_G1N+IgG1_G1NS1+IgG1_G2N+IgG1_G2NS1)*100))
dteh(data$LC_IGP32 <- with(data, IgG1_G1NS1/(IgG1_G1N+IgG1_G1NS1)*100))
dteh(data$LC_IGP33 <- with(data, IgG1_G2NS1/(IgG1_G2N+IgG1_G2NS1)*100))
dteh(data$LC_IGP34 <- with(data, (IgG1_G1FS1+IgG1_G2FS1)/(IgG1_G1F+IgG1_G1FS1+IgG1_G2F+IgG1_G2FS1)*100))
dteh(data$LC_IGP35 <- with(data, (IgG1_G1FS1+IgG1_G2FS1)/(IgG1_G0F+IgG1_G1F+IgG1_G1FS1+IgG1_G2F+IgG1_G2FS1)*100))
dteh(data$LC_IGP36 <- with(data, IgG1_G1FS1/(IgG1_G1F+IgG1_G1FS1)*100))
dteh(data$LC_IGP37 <- with(data, IgG1_G2FS1/(IgG1_G2F+IgG1_G2FS1)*100))
dteh(data$LC_IGP38 <- with(data, (IgG1_G1FNS1+IgG1_G2FNS1)/(IgG1_G1FN+IgG1_G1FNS1+IgG1_G2FN+IgG1_G2FNS1)*100))
dteh(data$LC_IGP39 <- with(data, (IgG1_G1FNS1+IgG1_G2FNS1)/(IgG1_G0FN+IgG1_G1FN+IgG1_G1FNS1+IgG1_G2FN+IgG1_G2FNS1)*100))
dteh(data$LC_IGP40 <- with(data, IgG1_G1FNS1/(IgG1_G1FN+IgG1_G1FNS1)*100))
dteh(data$LC_IGP41 <- with(data, IgG1_G2FNS1/(IgG1_G2FN+IgG1_G2FNS1)*100))
dteh(data$LC_IGP42 <- with(data, (IgG1_G1NS1+IgG1_G2NS1)/(IgG1_G1S1+IgG1_G2S1)))
dteh(data$LC_IGP43 <- with(data, (IgG1_G1FNS1+IgG1_G2FNS1)/(IgG1_G1FS1+IgG1_G2FS1)))
dteh(data$LC_IGP44 <- with(data, (IgG1_G1NS1+IgG1_G2NS1)/(IgG1_G1S1+IgG1_G1NS1+IgG1_G2S1+IgG1_G2NS1)))
dteh(data$LC_IGP45 <- with(data, (IgG1_G1FNS1+IgG1_G2FNS1)/(IgG1_G1FS1+IgG1_G1FNS1+IgG1_G2FS1+IgG1_G2FNS1)))
# neutral
dteh(IgG1.neutral <- with(data, IgG1_G0F+IgG1_G1F+IgG1_G2F+IgG1_G0FN+IgG1_G1FN+IgG1_G2FN+IgG1_G0+IgG1_G1+IgG1_G2+IgG1_G0N+IgG1_G1N+IgG1_G2N),
mess="Not all neutral glycans for IgG1 where found in the data frame")
dteh(data$LC_IGP46 <- with(data, IgG1_G0F/IgG1.neutral) * 100)
dteh(data$LC_IGP47 <- with(data, IgG1_G1F/IgG1.neutral) * 100)
dteh(data$LC_IGP48 <- with(data, IgG1_G2F/IgG1.neutral) * 100)
dteh(data$LC_IGP49 <- with(data, IgG1_G0FN/IgG1.neutral) * 100)
dteh(data$LC_IGP50 <- with(data, IgG1_G1FN/IgG1.neutral) * 100)
dteh(data$LC_IGP51 <- with(data, IgG1_G2FN/IgG1.neutral) * 100)
dteh(data$LC_IGP52 <- with(data, IgG1_G0/IgG1.neutral) * 100)
dteh(data$LC_IGP53 <- with(data, IgG1_G1/IgG1.neutral) * 100)
dteh(data$LC_IGP54 <- with(data, IgG1_G2/IgG1.neutral) * 100)
dteh(data$LC_IGP55 <- with(data, IgG1_G0N/IgG1.neutral) * 100)
dteh(data$LC_IGP56 <- with(data, IgG1_G1N/IgG1.neutral) * 100)
dteh(data$LC_IGP57 <- with(data, IgG1_G2N/IgG1.neutral) * 100)
# neutral - derived traits
dteh(data$LC_IGP58 <- with(data, (LC_IGP52+LC_IGP46+LC_IGP49+LC_IGP55)))
dteh(data$LC_IGP59 <- with(data, (LC_IGP53+LC_IGP47+LC_IGP50+LC_IGP56)))
dteh(data$LC_IGP60 <- with(data, (LC_IGP54+LC_IGP48+LC_IGP51+LC_IGP57)))
dteh(data$LC_IGP61 <- with(data, (LC_IGP46+LC_IGP49+LC_IGP47+LC_IGP50+LC_IGP48+LC_IGP51)))
dteh(data$LC_IGP62 <- with(data, (LC_IGP46+LC_IGP49)/LC_IGP58*100))
dteh(data$LC_IGP63 <- with(data, (LC_IGP47+LC_IGP50)/LC_IGP59*100))
dteh(data$LC_IGP64 <- with(data, (LC_IGP48+LC_IGP51)/LC_IGP60*100))
dteh(data$LC_IGP65 <- with(data, (LC_IGP46+LC_IGP47+LC_IGP48)))
dteh(data$LC_IGP66 <- with(data, LC_IGP46/LC_IGP58*100))
dteh(data$LC_IGP67 <- with(data, LC_IGP47/LC_IGP59*100))
dteh(data$LC_IGP68 <- with(data, LC_IGP48/LC_IGP60*100))
dteh(data$LC_IGP69 <- with(data, (LC_IGP49+LC_IGP50+LC_IGP51)))
dteh(data$LC_IGP70 <- with(data, LC_IGP49/LC_IGP58*100))
dteh(data$LC_IGP71 <- with(data, LC_IGP50/LC_IGP59*100))
dteh(data$LC_IGP72 <- with(data, LC_IGP51/LC_IGP60*100))
dteh(data$LC_IGP73 <- with(data, (LC_IGP55+LC_IGP56+LC_IGP57+LC_IGP49+LC_IGP50+LC_IGP51)))
dteh(data$LC_IGP74 <- with(data, (LC_IGP55+LC_IGP49)/LC_IGP58*100))
dteh(data$LC_IGP75 <- with(data, (LC_IGP56+LC_IGP50)/LC_IGP59*100))
dteh(data$LC_IGP76 <- with(data, (LC_IGP57+LC_IGP51)/LC_IGP60*100))
dteh(data$LC_IGP77 <- with(data, (LC_IGP55+LC_IGP56+LC_IGP57)))
dteh(data$LC_IGP78 <- with(data, LC_IGP55/LC_IGP58*100))
dteh(data$LC_IGP79 <- with(data, LC_IGP56/LC_IGP59*100))
dteh(data$LC_IGP80 <- with(data, LC_IGP57/LC_IGP60*100))
dteh(data$LC_IGP81 <- with(data, LC_IGP65/LC_IGP77))
dteh(data$LC_IGP82 <- with(data, LC_IGP69/LC_IGP65))
dteh(data$LC_IGP83 <- with(data, LC_IGP69/LC_IGP61*100))
dteh(data$LC_IGP84 <- with(data, LC_IGP69/LC_IGP73*100))
dteh(data$LC_IGP85 <- with(data, LC_IGP65/LC_IGP73))
dteh(data$LC_IGP86 <- with(data, LC_IGP77/LC_IGP61*1000))
# =======================================
# IgG2 derived traits
# =======================================
dteh(data$LC_IGP107 <- with(data, IgG2_G0F+IgG2_G1F+IgG2_G2F+IgG2_G0FN+IgG2_G1FN+IgG2_G2FN+IgG2_G1FS1+IgG2_G2FS1+IgG2_G1FNS1+IgG2_G2FNS1))
dteh(data$LC_IGP108 <- with(data, IgG2_G0FN+IgG2_G1FN+IgG2_G2FN+IgG2_G1FNS1+IgG2_G2FNS1+IgG2_G0N+IgG2_G1N+IgG2_G2N+IgG2_G1NS1+IgG2_G2NS1))
dteh(data$LC_IGP109 <- with(data, (IgG2_G1F+IgG2_G1FN+IgG2_G1FS1+IgG2_G1FNS1+IgG2_G1+IgG2_G1N+IgG2_G1S1+IgG2_G1NS1)*0.5+(IgG2_G2F+IgG2_G2FN+IgG2_G2FS1+IgG2_G2FNS1+IgG2_G2+IgG2_G2N+IgG2_G2S1+IgG2_G2NS1)))
dteh(data$LC_IGP110 <- with(data, IgG2_G1FS1+IgG2_G2FS1+IgG2_G1FNS1+IgG2_G2FNS1+IgG2_G1S1+IgG2_G2S1+IgG2_G1NS1+IgG2_G2NS1))
dteh(data$LC_IGP111 <- with(data, LC_IGP110/(2*LC_IGP109)*100))
dteh(data$LC_IGP112 <- with(data, (IgG2_G1S1+IgG2_G2S1)/(IgG2_G1+IgG2_G1S1+IgG2_G2+IgG2_G2S1)*100))
dteh(data$LC_IGP113 <- with(data, (IgG2_G1S1+IgG2_G2S1)/(IgG2_G0+IgG2_G1+IgG2_G1S1+IgG2_G2+IgG2_G2S1)*100))
dteh(data$LC_IGP114 <- with(data, IgG2_G1S1/(IgG2_G1+IgG2_G1S1)*100))
dteh(data$LC_IGP115 <- with(data, IgG2_G2S1/(IgG2_G2+IgG2_G2S1)*100))
dteh(data$LC_IGP116 <- with(data, (IgG2_G1NS1+IgG2_G2NS1)/(IgG2_G1N+IgG2_G1NS1+IgG2_G2N+IgG2_G2NS1)*100))
dteh(data$LC_IGP117 <- with(data, (IgG2_G1NS1+IgG2_G2NS1)/(IgG2_G0N+IgG2_G1N+IgG2_G1NS1+IgG2_G2N+IgG2_G2NS1)*100))
dteh(data$LC_IGP118 <- with(data, IgG2_G1NS1/(IgG2_G1N+IgG2_G1NS1)*100))
dteh(data$LC_IGP119 <- with(data, IgG2_G2NS1/(IgG2_G2N+IgG2_G2NS1)*100))
dteh(data$LC_IGP120 <- with(data, (IgG2_G1FS1+IgG2_G2FS1)/(IgG2_G1F+IgG2_G1FS1+IgG2_G2F+IgG2_G2FS1)*100))
dteh(data$LC_IGP121 <- with(data, (IgG2_G1FS1+IgG2_G2FS1)/(IgG2_G0F+IgG2_G1F+IgG2_G1FS1+IgG2_G2F+IgG2_G2FS1)*100))
dteh(data$LC_IGP122 <- with(data, IgG2_G1FS1/(IgG2_G1F+IgG2_G1FS1)*100))
dteh(data$LC_IGP123 <- with(data, IgG2_G2FS1/(IgG2_G2F+IgG2_G2FS1)*100))
dteh(data$LC_IGP124 <- with(data, (IgG2_G1FNS1+IgG2_G2FNS1)/(IgG2_G1FN+IgG2_G1FNS1+IgG2_G2FN+IgG2_G2FNS1)*100))
dteh(data$LC_IGP125 <- with(data, (IgG2_G1FNS1+IgG2_G2FNS1)/(IgG2_G0FN+IgG2_G1FN+IgG2_G1FNS1+IgG2_G2FN+IgG2_G2FNS1)*100))
dteh(data$LC_IGP126 <- with(data, IgG2_G1FNS1/(IgG2_G1FN+IgG2_G1FNS1)*100))
dteh(data$LC_IGP127 <- with(data, IgG2_G2FNS1/(IgG2_G2FN+IgG2_G2FNS1)*100))
dteh(data$LC_IGP128 <- with(data, (IgG2_G1NS1+IgG2_G2NS1)/(IgG2_G1S1+IgG2_G2S1)))
dteh(data$LC_IGP129 <- with(data, (IgG2_G1FNS1+IgG2_G2FNS1)/(IgG2_G1FS1+IgG2_G2FS1)))
dteh(data$LC_IGP130 <- with(data, (IgG2_G1NS1+IgG2_G2NS1)/(IgG2_G1S1+IgG2_G1NS1+IgG2_G2S1+IgG2_G2NS1)))
dteh(data$LC_IGP131 <- with(data, (IgG2_G1FNS1+IgG2_G2FNS1)/(IgG2_G1FS1+IgG2_G1FNS1+IgG2_G2FS1+IgG2_G2FNS1)))
# neutral
dteh(IgG2.neutral <- with(data, IgG2_G0F+IgG2_G1F+IgG2_G2F+IgG2_G0FN+IgG2_G1FN+IgG2_G2FN+IgG2_G0+IgG2_G1+IgG2_G2+IgG2_G0N+IgG2_G1N+IgG2_G2N),
mess="Not all neutral glycans for IgG2 where found in the data frame")
dteh(data$LC_IGP132 <- with(data, IgG2_G0F/IgG2.neutral) * 100)
dteh(data$LC_IGP133 <- with(data, IgG2_G1F/IgG2.neutral) * 100)
dteh(data$LC_IGP134 <- with(data, IgG2_G2F/IgG2.neutral) * 100)
dteh(data$LC_IGP135 <- with(data, IgG2_G0FN/IgG2.neutral) * 100)
dteh(data$LC_IGP136 <- with(data, IgG2_G1FN/IgG2.neutral) * 100)
dteh(data$LC_IGP137 <- with(data, IgG2_G2FN/IgG2.neutral) * 100)
dteh(data$LC_IGP138 <- with(data, IgG2_G0/IgG2.neutral) * 100)
dteh(data$LC_IGP139 <- with(data, IgG2_G1/IgG2.neutral) * 100)
dteh(data$LC_IGP140 <- with(data, IgG2_G2/IgG2.neutral) * 100)
dteh(data$LC_IGP141 <- with(data, IgG2_G0N/IgG2.neutral) * 100)
dteh(data$LC_IGP142 <- with(data, IgG2_G1N/IgG2.neutral) * 100)
dteh(data$LC_IGP143 <- with(data, IgG2_G2N/IgG2.neutral) * 100)
# neutral - derived traits
dteh(data$LC_IGP144 <- with(data, (LC_IGP138+LC_IGP132+LC_IGP135+LC_IGP141)))
dteh(data$LC_IGP145 <- with(data, (LC_IGP139+LC_IGP133+LC_IGP136+LC_IGP142)))
dteh(data$LC_IGP146 <- with(data, (LC_IGP140+LC_IGP134+LC_IGP137+LC_IGP143)))
dteh(data$LC_IGP147 <- with(data, (LC_IGP132+LC_IGP135+LC_IGP133+LC_IGP136+LC_IGP134+LC_IGP137)))
dteh(data$LC_IGP148 <- with(data, (LC_IGP132+LC_IGP135)/LC_IGP144*100))
dteh(data$LC_IGP149 <- with(data, (LC_IGP133+LC_IGP136)/LC_IGP145*100))
dteh(data$LC_IGP150 <- with(data, (LC_IGP134+LC_IGP137)/LC_IGP146*100))
dteh(data$LC_IGP151 <- with(data, (LC_IGP132+LC_IGP133+LC_IGP134)))
dteh(data$LC_IGP152 <- with(data, LC_IGP132/LC_IGP144*100))
dteh(data$LC_IGP153 <- with(data, LC_IGP133/LC_IGP145*100))
dteh(data$LC_IGP154 <- with(data, LC_IGP134/LC_IGP146*100))
dteh(data$LC_IGP155 <- with(data, (LC_IGP135+LC_IGP136+LC_IGP137)))
dteh(data$LC_IGP156 <- with(data, LC_IGP135/LC_IGP144*100))
dteh(data$LC_IGP157 <- with(data, LC_IGP136/LC_IGP145*100))
dteh(data$LC_IGP158 <- with(data, LC_IGP137/LC_IGP146*100))
dteh(data$LC_IGP159 <- with(data, (LC_IGP141+LC_IGP142+LC_IGP143+LC_IGP135+LC_IGP136+LC_IGP137)))
dteh(data$LC_IGP160 <- with(data, (LC_IGP141+LC_IGP135)/LC_IGP144*100))
dteh(data$LC_IGP161 <- with(data, (LC_IGP142+LC_IGP136)/LC_IGP145*100))
dteh(data$LC_IGP162 <- with(data, (LC_IGP143+LC_IGP137)/LC_IGP146*100))
dteh(data$LC_IGP163 <- with(data, (LC_IGP141+LC_IGP142+LC_IGP143)))
dteh(data$LC_IGP164 <- with(data, LC_IGP141/LC_IGP144*100))
dteh(data$LC_IGP165 <- with(data, LC_IGP142/LC_IGP145*100))
dteh(data$LC_IGP166 <- with(data, LC_IGP143/LC_IGP146*100))
dteh(data$LC_IGP167 <- with(data, LC_IGP151/LC_IGP163))
dteh(data$LC_IGP168 <- with(data, LC_IGP155/LC_IGP151))
dteh(data$LC_IGP169 <- with(data, LC_IGP155/LC_IGP147*100))
dteh(data$LC_IGP170 <- with(data, LC_IGP155/LC_IGP159*100))
dteh(data$LC_IGP171 <- with(data, LC_IGP151/LC_IGP159))
dteh(data$LC_IGP172 <- with(data, LC_IGP163/LC_IGP147*1000))
# =======================================
# IgG4 derived traits
# =======================================
dteh(data$LC_IGP183 <- with(data, (IgG4_G0FN+IgG4_G1FN+IgG4_G2FN+IgG4_G1FNS1+IgG4_G2FNS1) ))
dteh(data$LC_IGP184 <- with(data, (IgG4_G1F+IgG4_G1FN+IgG4_G1FS1+IgG4_G1FNS1)*0.5+(IgG4_G2F+IgG4_G2FN+IgG4_G2FS1+IgG4_G2FNS1)))
dteh(data$LC_IGP185 <- with(data, (IgG4_G1FS1+IgG4_G2FS1+IgG4_G1FNS1+IgG4_G2FNS1)))
dteh(data$LC_IGP186 <- with(data, LC_IGP185/(2*LC_IGP184)*100))
dteh(data$LC_IGP187 <- with(data, (IgG4_G1FS1+IgG4_G2FS1)/(IgG4_G1F+IgG4_G1FS1+IgG4_G2F+IgG4_G2FS1)*100))
dteh(data$LC_IGP188 <- with(data, (IgG4_G1FS1+IgG4_G2FS1)/(IgG4_G0F+IgG4_G1F+IgG4_G1FS1+IgG4_G2F+IgG4_G2FS1)*100))
dteh(data$LC_IGP189 <- with(data, IgG4_G1FS1/(IgG4_G1F+IgG4_G1FS1)*100))
dteh(data$LC_IGP190 <- with(data, IgG4_G2FS1/(IgG4_G2F+IgG4_G2FS1)*100))
dteh(data$LC_IGP191 <- with(data, (IgG4_G1FNS1+IgG4_G2FNS1)/(IgG4_G1FN+IgG4_G1FNS1+IgG4_G2FN+IgG4_G2FNS1)*100))
dteh(data$LC_IGP192 <- with(data, (IgG4_G1FNS1+IgG4_G2FNS1)/(IgG4_G0FN+IgG4_G1FN+IgG4_G1FNS1+IgG4_G2FN+IgG4_G2FNS1)*100))
dteh(data$LC_IGP193 <- with(data, IgG4_G1FNS1/(IgG4_G1FN+IgG4_G1FNS1)*100))
dteh(data$LC_IGP194 <- with(data, IgG4_G2FNS1/(IgG4_G2FN+IgG4_G2FNS1)*100))
dteh(data$LC_IGP195 <- with(data, (IgG4_G1FNS1+IgG4_G2FNS1)/(IgG4_G1FS1+IgG4_G2FS1)))
dteh(data$LC_IGP196 <- with(data, (IgG4_G1FNS1+IgG4_G2FNS1)/(IgG4_G1FS1+IgG4_G1FNS1+IgG4_G2FS1+IgG4_G2FNS1)))
# neutral
dteh(IgG4.neutral <- with(data, IgG4_G0F+IgG4_G1F+IgG4_G2F+IgG4_G0FN+IgG4_G1FN+IgG4_G2FN),
mess="Not all neutral glycans for IgG4 where found in the data frame")
dteh(data$LC_IGP197 <- with(data, IgG4_G0F/IgG4.neutral) * 100)
dteh(data$LC_IGP198 <- with(data, IgG4_G1F/IgG4.neutral) * 100)
dteh(data$LC_IGP199 <- with(data, IgG4_G2F/IgG4.neutral) * 100)
dteh(data$LC_IGP200 <- with(data, IgG4_G0FN/IgG4.neutral) * 100)
dteh(data$LC_IGP201 <- with(data, IgG4_G1FN/IgG4.neutral) * 100)
dteh(data$LC_IGP202 <- with(data, IgG4_G2FN/IgG4.neutral) * 100)
# neutral - derived traits
dteh(data$LC_IGP203 <- with(data, LC_IGP197 + LC_IGP200))
dteh(data$LC_IGP204 <- with(data, LC_IGP198 + LC_IGP201))
dteh(data$LC_IGP205 <- with(data, LC_IGP199 + LC_IGP202))
return(data)
}
# Translate names between computer readable and human readable
# for derived traits of IgG with LCMS
# based on paper from 2014.
#
# Translates names between computer readable and human readable
# for derived traits of IgG with LCMS
#
# @author Ivo Ugrina
# @param orignames vector; type string
# @param to type of translation. If \code{inverse} is used everything will be
# translated. For \code{computer} names will be translated to computer
# readable, and for \code{human} names will be translated to human readable.
# @return Returns a character vector with original and translated names
# @references
# Jennifer E. Huffman et al.
# "Comparative Performance of Four Methods for High-throughput Glycosylation Analysis of Immunoglobulin G in Genetic and Epidemiological Research*"
# \doi{10.1074/mcp.M113.037465}
ildt.translate.2014 <- function(orignames, to="inverse") {
allnames <- "computer human
LC_IGP1 IgG1_G0F
LC_IGP2 IgG1_G1F
LC_IGP3 IgG1_G2F
LC_IGP4 IgG1_G0FN
LC_IGP5 IgG1_G1FN
LC_IGP6 IgG1_G2FN
LC_IGP7 IgG1_G1FS1
LC_IGP8 IgG1_G2FS1
LC_IGP9 IgG1_G1FNS1
LC_IGP10 IgG1_G2FNS1
LC_IGP11 IgG1_G0
LC_IGP12 IgG1_G1
LC_IGP13 IgG1_G2
LC_IGP14 IgG1_G0N
LC_IGP15 IgG1_G1N
LC_IGP16 IgG1_G2N
LC_IGP17 IgG1_G1S1
LC_IGP18 IgG1_G2S1
LC_IGP19 IgG1_G1NS1
LC_IGP20 IgG1_G2NS1
LC_IGP21 IgG1 Fucosylation
LC_IGP22 IgG1 Bisecting_GlcNAc
LC_IGP23 IgG1 Galactosylation
LC_IGP24 IgG1 Sialylation
LC_IGP25 IgG1 SA per Gal
LC_IGP26 IgG1 GS1/(G+GS1)
LC_IGP27 IgG1 GS1/(G0+G+GS1)
LC_IGP28 IgG1 G1S1/(G1+G1S1)
LC_IGP29 IgG1 G2S1/(G2+G2S1)
LC_IGP30 IgG1 BGS1/(BG+BGS1)
LC_IGP31 IgG1 BGS1/(BG0+BG+BGS1)
LC_IGP32 IgG1 BG1S1/(BG1+BG1S1)
LC_IGP33 IgG1 BG2S1/(BG2+BG2S1)
LC_IGP34 IgG1 FGS1/(FG+FGS1)
LC_IGP35 IgG1 FGS1/(F+FG+FGS1)
LC_IGP36 IgG1 FG1S1/(FG1+FG1S1)
LC_IGP37 IgG1 FG2S1/(FG2+FG2S1)
LC_IGP38 IgG1 FBGS1/(FBG+FBGS1)
LC_IGP39 IgG1 FBGS1/(FB+FBG+FBGS1)
LC_IGP40 IgG1 FBG1S1/(FBG1+FBG1S1)
LC_IGP41 IgG1 FBG2S1/(FBG2+FBG2S1)
LC_IGP42 IgG1 BS1/S1
LC_IGP43 IgG1 FBS1/FS1
LC_IGP44 IgG1 BS1/(S1+BS1)
LC_IGP45 IgG1 FBS1/(FS1+FBS1)
LC_IGP46 IgG1_G0Fn
LC_IGP47 IgG1_G1Fn
LC_IGP48 IgG1_G2Fn
LC_IGP49 IgG1_G0FNn
LC_IGP50 IgG1_G1FNn
LC_IGP51 IgG1_G2FNn
LC_IGP52 IgG1_G0n
LC_IGP53 IgG1_G1n
LC_IGP54 IgG1_G2n
LC_IGP55 IgG1_G0Nn
LC_IGP56 IgG1_G1Nn
LC_IGP57 IgG1_G2Nn
LC_IGP58 IgG1G0n
LC_IGP59 IgG1G1n
LC_IGP60 IgG1G2n
LC_IGP61 IgG1 Fn total
LC_IGP62 IgG1 FG0n total/G0n
LC_IGP63 IgG1 FG1n total/G1n
LC_IGP64 IgG1 FG2n total/G2n
LC_IGP65 IgG1 Fn
LC_IGP66 IgG1 FG0n/G0n
LC_IGP67 IgG1 FG1n/G1n
LC_IGP68 IgG1 FG2n/G2n
LC_IGP69 IgG1 FBn
LC_IGP70 IgG1 FBG0n/G0n
LC_IGP71 IgG1 FBG1n/G1n
LC_IGP72 IgG1 FBG2n/G2n
LC_IGP73 IgG1 Bn total
LC_IGP74 IgG1 BG0n total/G0n
LC_IGP75 IgG1 BG1n total/G1n
LC_IGP76 IgG1 BG2n total/G2n
LC_IGP77 IgG1 Bn
LC_IGP78 IgG1 BG0n/G0n
LC_IGP79 IgG1 BG1n/G1n
LC_IGP80 IgG1 BG2n/G2n
LC_IGP81 IgG1 Fn/Bn
LC_IGP82 IgG1 FBn/Fn
LC_IGP83 IgG1 FBn/Fn total
LC_IGP84 IgG1 FBn/Bn total
LC_IGP85 IgG1 Fn/Bn total
LC_IGP86 IgG1 Bn/Fn total
LC_IGP87 IgG2_G0F
LC_IGP88 IgG2_G1F
LC_IGP89 IgG2_G2F
LC_IGP90 IgG2_G0FN
LC_IGP91 IgG2_G1FN
LC_IGP92 IgG2_G2FN
LC_IGP93 IgG2_G1FS1
LC_IGP94 IgG2_G2FS1
LC_IGP95 IgG2_G1FNS1
LC_IGP96 IgG2_G2FNS1
LC_IGP97 IgG2_G0
LC_IGP98 IgG2_G1
LC_IGP99 IgG2_G2
LC_IGP100 IgG2_G0N
LC_IGP101 IgG2_G1N
LC_IGP102 IgG2_G2N
LC_IGP103 IgG2_G1S1
LC_IGP104 IgG2_G2S1
LC_IGP105 IgG2_G1NS1
LC_IGP106 IgG2_G2NS1
LC_IGP107 IgG2 Fucosylation
LC_IGP108 IgG2 Bisecting GlcNAc
LC_IGP109 IgG2 Galactosylation
LC_IGP110 IgG2 Sialylation
LC_IGP111 IgG2 SA per Gal
LC_IGP112 IgG2 GS1/(G+GS1)
LC_IGP113 IgG2 GS1/(G0+G+GS1)
LC_IGP114 IgG2 G1S1/(G1+G1S1)
LC_IGP115 IgG2 G2S1/(G2+G2S1)
LC_IGP116 IgG2 BGS1/(BG+BGS1)
LC_IGP117 IgG2 BGS1/(BG0+BG+BGS1)
LC_IGP118 IgG2 BG1S1/(BG1+BG1S1)
LC_IGP119 IgG2 BG2S1/(BG2+BG2S1)
LC_IGP120 IgG2 FGS1/(FG+FGS1)
LC_IGP121 IgG2 FGS1/(F+FG+FGS1)
LC_IGP122 IgG2 FG1S1/(FG1+FG1S1)
LC_IGP123 IgG2 FG2S1/(FG2+FG2S1)
LC_IGP124 IgG2 FBGS1/(FBG+FBGS1)
LC_IGP125 IgG2 FBGS1/(FB+FBG+FBGS1)
LC_IGP126 IgG2 FBG1S1/(FBG1+FBG1S1)
LC_IGP127 IgG2 FBG2S1/(FBG2+FBG2S1)
LC_IGP128 IgG2 BS1/S1
LC_IGP129 IgG2 FBS1/FS1
LC_IGP130 IgG2 BS1/(S1+BS1)
LC_IGP131 IgG2 FBS1/(FS1+FBS1)
LC_IGP132 IgG2_G0Fn
LC_IGP133 IgG2_G1Fn
LC_IGP134 IgG2_G2Fn
LC_IGP135 IgG2_G0FNn
LC_IGP136 IgG2_G1FNn
LC_IGP137 IgG2_G2FNn
LC_IGP138 IgG2_G0n
LC_IGP139 IgG2_G1n
LC_IGP140 IgG2_G2n
LC_IGP141 IgG2_G0Nn
LC_IGP142 IgG2_G1Nn
LC_IGP143 IgG2_G2Nn
LC_IGP144 IgG2G0n
LC_IGP145 IgG2G1n
LC_IGP146 IgG2G2n
LC_IGP147 IgG2 Fn total
LC_IGP148 IgG2 FG0n total/G0n
LC_IGP149 IgG2 FG1n total/G1n
LC_IGP150 IgG2 FG2n total/G2n
LC_IGP151 IgG2 Fn
LC_IGP152 IgG2 FG0n/G0n
LC_IGP153 IgG2 FG1n/G1n
LC_IGP154 IgG2 FG2n/G2n
LC_IGP155 IgG2 FBn
LC_IGP156 IgG2 FBG0n/G0n
LC_IGP157 IgG2 FBG1n/G1n
LC_IGP158 IgG2 FBG2n/G2n
LC_IGP159 IgG2 Bn total
LC_IGP160 IgG2 BG0n total/G0n
LC_IGP161 IgG2 BG1n total/G1n
LC_IGP162 IgG2 BG2n total/G2n
LC_IGP163 IgG2 Bn
LC_IGP164 IgG2 BG0n/G0n
LC_IGP165 IgG2 BG1n/G1n
LC_IGP166 IgG2 BG2n/G2n
LC_IGP167 IgG2 Fn/Bn
LC_IGP168 IgG2 FBn/Fn
LC_IGP169 IgG2 FBn/Fn total
LC_IGP170 IgG2 FBn/Bn total
LC_IGP171 IgG2 Fn/Bn total
LC_IGP172 IgG2 Bn/Fn total
LC_IGP173 IgG4_G0F
LC_IGP174 IgG4_G1F
LC_IGP175 IgG4_G2F
LC_IGP176 IgG4_G0FN
LC_IGP177 IgG4_G1FN
LC_IGP178 IgG4_G2FN
LC_IGP179 IgG4_G1FS1
LC_IGP180 IgG4_G2FS1
LC_IGP181 IgG4_G1FNS1
LC_IGP182 IgG4_G2FNS1
LC_IGP183 IgG4 Bisecting GlcNAc
LC_IGP184 IgG4 Galactosylation
LC_IGP185 IgG4 Sialylation
LC_IGP186 IgG4 SA per Gal
LC_IGP187 IgG4 FGS1/(FG+FGS1)
LC_IGP188 IgG4 FGS1/(F+FG+FGS1)
LC_IGP189 IgG4 FG1S1/(FG1+FG1S1)
LC_IGP190 IgG4 FG2S1/(FG2+FG2S1)
LC_IGP191 IgG4 FBGS1/(FBG+FBGS1)
LC_IGP192 IgG4 FBGS1/(FB+FBG+FBGS1)
LC_IGP193 IgG4 FBG1S1/(FBG1+FBG1S1)
LC_IGP194 IgG4 FBG2S1/(FBG2+FBG2S1)
LC_IGP195 IgG4 FBS1/FS1
LC_IGP196 IgG4 FBS1/(FS1+FBS1)
LC_IGP197 IgG4_G0Fn
LC_IGP198 IgG4_G1Fn
LC_IGP199 IgG4_G2Fn
LC_IGP200 IgG4_G0FNn
LC_IGP201 IgG4_G1FNn
LC_IGP202 IgG4_G2FNn
LC_IGP203 IgG4G0n
LC_IGP204 IgG4G1n
LC_IGP205 IgG4G2n"
con <- textConnection(allnames)
allnames <- read.delim(con, sep="\t", header=TRUE, stringsAsFactors=FALSE)
close(con)
cn <- match(orignames, allnames$computer)
hn <- match(orignames, allnames$human)
if(to=="inverse"){
newnames <- ifelse(!is.na(cn),
allnames$human[cn],
allnames$computer[hn])
}
if(to=="computer"){
newnames <- ifelse(!is.na(cn),
allnames$computer[cn],
allnames$computer[hn])
}
if(to=="human"){
newnames <- ifelse(!is.na(hn),
allnames$human[hn],
allnames$human[cn])
}
return(newnames)
}
# Translate names between computer readable and human readable
# for derived traits of IgG with UPLC
# based on an article from 2014.
#
# Translates names between computer readable and human readable
# for derived traits of IgG with UPLC
#
# @author Ivo Ugrina
# @param orignames vector; type string
# @param to type of translation. If \code{inverse} is used everything will be
# translated. For \code{computer} names will be translated to computer
# readable, and for \code{human} names will be translated to human readable.
# @return Returns a character vector with original and translated names
# @references
# Jennifer E. Huffman et al.
# "Comparative Performance of Four Methods for High-throughput Glycosylation Analysis of Immunoglobulin G in Genetic and Epidemiological Research*"
# \doi{10.1074/mcp.M113.037465}
iudt.translate.2014 <- function(orignames, to="inverse") {
allnames <- "computer human
IGP1 GP1
IGP2 GP2
IGP3 GP4
IGP4 GP5
IGP5 GP6
IGP6 GP7
IGP7 GP8
IGP8 GP9
IGP9 GP10
IGP10 GP11
IGP11 GP12
IGP12 GP13
IGP13 GP14
IGP14 GP15
IGP15 GP16
IGP16 GP17
IGP17 GP18
IGP18 GP19
IGP19 GP20
IGP20 GP21
IGP21 GP22
IGP22 GP23
IGP23 GP24
IGP24 FGS/(FG+FGS)
IGP25 FBGS/(FBG+FBGS)
IGP26 FGS/(F+FG+FGS)
IGP27 FBGS/(FB+FBG+FBGS)
IGP28 FG1S1/(FG1+FG1S1)
IGP29 FG2S1/(FG2+FG2S1+FG2S2)
IGP30 FG2S2/(FG2+FG2S1+FG2S2)
IGP31 FBG2S1/(FBG2+FBG2S1+FBG2S2)
IGP32 FBG2S2/(FBG2+FBG2S1+FBG2S2)
IGP33 FtotalS1/FtotalS2
IGP34 FS1/FS2
IGP35 FBS1/FBS2
IGP36 FBStotal/FStotal
IGP37 FBS1/FS1
IGP38 FBS1/(FS1+FBS1)
IGP39 FBS2/FS2
IGP40 FBS2/(FS2+FBS2)
IGP41 GP1n
IGP42 GP2n
IGP43 GP4n
IGP44 GP5n
IGP45 GP6n
IGP46 GP7n
IGP47 GP8n
IGP48 GP9n
IGP49 GP10n
IGP50 GP11n
IGP51 GP12n
IGP52 GP13n
IGP53 GP14n
IGP54 GP15n
IGP55 G0n
IGP56 G1n
IGP57 G2n
IGP58 Fn total
IGP59 FG0n total/G0n
IGP60 FG1n total/G1n
IGP61 FG2n total/G2n
IGP62 Fn
IGP63 FG0n/G0n
IGP64 FG1n/G1n
IGP65 FG2n/G2n
IGP66 FBn
IGP67 FBG0n/G0n
IGP68 FBG1n/G1n
IGP69 FBG2n/G2n
IGP70 FBn/Fn
IGP71 FBn/Fn total
IGP72 Fn/(Bn+ FBn)
IGP73 Bn/(Fn+ FBn)
IGP74 FBG2n/FG2n
IGP75 FBG2n/(FG2n+ FBG2n)
IGP76 FG2n/(BG2n+ FBG2n)
IGP77 BG2n/(FG2n+ FBG2n)"
con <- textConnection(allnames)
allnames <- read.delim(con, sep="\t", header=TRUE, stringsAsFactors=FALSE)
close(con)
cn <- match(orignames, allnames$computer)
hn <- match(orignames, allnames$human)
if(to=="inverse"){
newnames <- ifelse(!is.na(cn),
allnames$human[cn],
allnames$computer[hn])
}
if(to=="computer"){
newnames <- ifelse(!is.na(cn),
allnames$computer[cn],
allnames$computer[hn])
}
if(to=="human"){
newnames <- ifelse(!is.na(hn),
allnames$human[hn],
allnames$human[cn])
}
return(newnames)
}
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Defines functions iudt.translate.2014 ildt.translate.2014 igg.lcms.derived.traits.2014 igg.uplc.derived.traits.2014
# Derived traits for Glycan peaks in IgG for UPLC
# based on paper from 2014.
#
# @references
# Jennifer E. Huffman et al.
# "Comparative Performance of Four Methods for High-throughput Glycosylation Analysis of Immunoglobulin G in Genetic and Epidemiological Research*"
# \doi{10.1074/mcp.M113.037465}
igg.uplc.derived.traits.2014 <- function(data, print.exp.names=FALSE) {
if(print.exp.names){
return(paste0("GP", 1:24))
}
# derived glycans
dteh(data$IGP24 <- with(data, (GP16 + GP18 + GP23)/(GP16 + GP18 + GP23 + GP8 + GP9 + GP14)) * 100)
dteh(data$IGP25 <- with(data, (GP19 + GP24)/(GP19 + GP24 + GP10 + GP11 + GP15)) * 100)
dteh(data$IGP26 <- with(data, (GP16 + GP18 + GP23)/(GP16 + GP18 + GP23 + GP4 + GP8 + GP9 + GP14)) * 100)
dteh(data$IGP27 <- with(data, (GP19 + GP24)/(GP19 + GP24 + GP6 + GP10 + GP11 + GP15)) * 100)
dteh(data$IGP28 <- with(data, GP16/(GP16 + GP8 + GP9)) * 100)
dteh(data$IGP29 <- with(data, GP18/(GP18 + GP14 + GP23)) * 100)
dteh(data$IGP30 <- with(data, GP23/(GP23 + GP14 + GP18)) * 100)
dteh(data$IGP31 <- with(data, GP19/(GP19 + GP15 + GP24)) * 100)
dteh(data$IGP32 <- with(data, GP24/(GP24 + GP15 + GP19)) * 100)
dteh(data$IGP33 <- with(data, (GP16 + GP18 + GP19)/(GP23 + GP24)))
dteh(data$IGP34 <- with(data, (GP16 + GP18)/GP23))
dteh(data$IGP35 <- with(data, GP19/GP24))
dteh(data$IGP36 <- with(data, (GP19 + GP24)/(GP16 + GP18 + GP23)))
dteh(data$IGP37 <- with(data, GP19/(GP16 + GP18)))
dteh(data$IGP38 <- with(data, GP19/(GP16 + GP18 + GP19)) * 100)
dteh(data$IGP39 <- with(data, GP24/GP23))
dteh(data$IGP40 <- with(data, GP24/(GP23 + GP24)) * 100)
# neutral glycans
dteh(GPn <- with(data, GP1 + GP2 + GP4 + GP6 + GP7 + GP8 + GP9 + GP10 + GP11 + GP12 + GP13 + GP14 + GP15))
dteh(data$IGP41 <- with(data, GP1/GPn) * 100)
dteh(data$IGP42 <- with(data, GP2/GPn) * 100)
dteh(data$IGP43 <- with(data, GP4/GPn) * 100)
dteh(data$IGP44 <- with(data, GP5/GPn) * 100)
dteh(data$IGP45 <- with(data, GP6/GPn) * 100)
dteh(data$IGP46 <- with(data, GP7/GPn) * 100)
dteh(data$IGP47 <- with(data, GP8/GPn) * 100)
dteh(data$IGP48 <- with(data, GP9/GPn) * 100)
dteh(data$IGP49 <- with(data, GP10/GPn) * 100)
dteh(data$IGP50 <- with(data, GP11/GPn) * 100)
dteh(data$IGP51 <- with(data, GP12/GPn) * 100)
dteh(data$IGP52 <- with(data, GP13/GPn) * 100)
dteh(data$IGP53 <- with(data, GP14/GPn) * 100)
dteh(data$IGP54 <- with(data, GP15/GPn) * 100)
# neutral derived glycans
dteh(data$IGP55 <- with(data, (IGP41 + IGP42 + IGP43 + IGP45)))
dteh(data$IGP56 <- with(data, (IGP46 + IGP47 + IGP48 + IGP49 + IGP50)))
dteh(data$IGP57 <- with(data, (IGP51 + IGP52 + IGP53 + IGP54)))
dteh(data$IGP58 <- with(data, (IGP41 + IGP43 + IGP45 + IGP47 + IGP48 + IGP49 + IGP50 + IGP53 + IGP54)))
dteh(data$IGP59 <- with(data, (IGP41 + IGP43 + IGP45)/IGP55) * 100)
dteh(data$IGP60 <- with(data, (IGP47 + IGP48 + IGP49 + IGP50)/IGP56) * 100)
dteh(data$IGP61 <- with(data, (IGP53 + IGP54)/IGP57) * 100)
dteh(data$IGP62 <- with(data, (IGP41 + IGP43 + IGP47 + IGP48 + IGP53)))
dteh(data$IGP63 <- with(data, (IGP41 + IGP43)/IGP55) * 100)
dteh(data$IGP64 <- with(data, (IGP47 + IGP48)/IGP56) * 100)
dteh(data$IGP65 <- with(data, IGP53/IGP57) * 100)
dteh(data$IGP66 <- with(data, (IGP45 + IGP49 + IGP50 + IGP54)))
dteh(data$IGP67 <- with(data, IGP45/IGP55) * 100)
dteh(data$IGP68 <- with(data, (IGP49 + IGP50)/IGP56) * 100)
dteh(data$IGP69 <- with(data, IGP54/IGP57) * 100)
dteh(data$IGP70 <- with(data, IGP66/IGP62) * 100)
dteh(data$IGP71 <- with(data, IGP66/IGP58) * 100)
dteh(data$IGP72 <- with(data, IGP62/(IGP52 + IGP66)))
dteh(data$IGP73 <- with(data, IGP52/(IGP62 + IGP66)) * 1000)
dteh(data$IGP74 <- with(data, IGP54/IGP53))
dteh(data$IGP75 <- with(data, IGP54/(IGP53 + IGP54)) * 100)
dteh(data$IGP76 <- with(data, IGP53/(IGP52 + IGP54)))
dteh(data$IGP77 <- with(data, IGP52/(IGP53 + IGP54)) * 1000)
return(data)
}
# Derived traits for Glycan peaks in IgG for LCMS
# based on paper from 2014.
#
# @references
# Jennifer E. Huffman et al.
# "Comparative Performance of Four Methods for High-throughput Glycosylation Analysis of Immunoglobulin G in Genetic and Epidemiological Research*"
# \doi{10.1074/mcp.M113.037465}
igg.lcms.derived.traits.2014 <- function(data, print.exp.names=FALSE) {
if(print.exp.names){
return(c("IgG1_G0F","IgG1_G1F","IgG1_G2F","IgG1_G0FN","IgG1_G1FN",
"IgG1_G2FN","IgG1_G1FS1","IgG1_G2FS1","IgG1_G1FNS1","IgG1_G2FNS1",
"IgG1_G0","IgG1_G1","IgG1_G2","IgG1_G0N","IgG1_G1N",
"IgG1_G2N","IgG1_G1S1","IgG1_G2S1","IgG1_G1NS1","IgG1_G2NS1",
"IgG2_G0F","IgG2_G1F","IgG2_G2F","IgG2_G0FN","IgG2_G1FN",
"IgG2_G2FN","IgG2_G1FS1","IgG2_G2FS1","IgG2_G1FNS1","IgG2_G2FNS1",
"IgG2_G0","IgG2_G1","IgG2_G2","IgG2_G0N","IgG2_G1N",
"IgG2_G2N","IgG2_G1S1","IgG2_G2S1","IgG2_G1NS1","IgG2_G2NS1",
"IgG4_G0F","IgG4_G1F","IgG4_G2F","IgG4_G0FN","IgG4_G1FN",
"IgG4_G2FN","IgG4_G1FS1","IgG4_G2FS1","IgG4_G1FNS1","IgG4_G2FNS1",
"IgG4_G0","IgG4_G1","IgG4_G2","IgG4_G0N","IgG4_G1N",
"IgG4_G2N","IgG4_G1S1","IgG4_G2S1","IgG4_G1NS1","IgG4_G2NS1"))
}
# =======================================
# IgG1 derived traits
# =======================================
dteh(data$LC_IGP21 <- with(data, IgG1_G0F+IgG1_G1F+IgG1_G2F+IgG1_G0FN+IgG1_G1FN+IgG1_G2FN+IgG1_G1FS1+IgG1_G2FS1+IgG1_G1FNS1+IgG1_G2FNS1))
dteh(data$LC_IGP22 <- with(data, IgG1_G0FN+IgG1_G1FN+IgG1_G2FN+IgG1_G1FNS1+IgG1_G2FNS1+IgG1_G0N+IgG1_G1N+IgG1_G2N+IgG1_G1NS1+IgG1_G2NS1))
dteh(data$LC_IGP23 <- with(data, (IgG1_G1F+IgG1_G1FN+IgG1_G1FS1+IgG1_G1FNS1+IgG1_G1+IgG1_G1N+IgG1_G1S1+IgG1_G1NS1)*0.5+(IgG1_G2F+IgG1_G2FN+IgG1_G2FS1+IgG1_G2FNS1+IgG1_G2+IgG1_G2N+IgG1_G2S1+IgG1_G2NS1)))
dteh(data$LC_IGP24 <- with(data, IgG1_G1FS1+IgG1_G2FS1+IgG1_G1FNS1+IgG1_G2FNS1+IgG1_G1S1+IgG1_G2S1+IgG1_G1NS1+IgG1_G2NS1))
dteh(data$LC_IGP25 <- with(data, LC_IGP24/(2*LC_IGP23)*100))
dteh(data$LC_IGP26 <- with(data, (IgG1_G1S1+IgG1_G2S1)/(IgG1_G1+IgG1_G1S1+IgG1_G2+IgG1_G2S1)*100))
dteh(data$LC_IGP27 <- with(data, (IgG1_G1S1+IgG1_G2S1)/(IgG1_G0+IgG1_G1+IgG1_G1S1+IgG1_G2+IgG1_G2S1)*100))
dteh(data$LC_IGP28 <- with(data, IgG1_G1S1/(IgG1_G1+IgG1_G1S1)*100))
dteh(data$LC_IGP29 <- with(data, IgG1_G2S1/(IgG1_G2+IgG1_G2S1)*100))
dteh(data$LC_IGP30 <- with(data, (IgG1_G1NS1+IgG1_G2NS1)/(IgG1_G1N+IgG1_G1NS1+IgG1_G2N+IgG1_G2NS1)*100))
dteh(data$LC_IGP31 <- with(data, (IgG1_G1NS1+IgG1_G2NS1)/(IgG1_G0N+IgG1_G1N+IgG1_G1NS1+IgG1_G2N+IgG1_G2NS1)*100))
dteh(data$LC_IGP32 <- with(data, IgG1_G1NS1/(IgG1_G1N+IgG1_G1NS1)*100))
dteh(data$LC_IGP33 <- with(data, IgG1_G2NS1/(IgG1_G2N+IgG1_G2NS1)*100))
dteh(data$LC_IGP34 <- with(data, (IgG1_G1FS1+IgG1_G2FS1)/(IgG1_G1F+IgG1_G1FS1+IgG1_G2F+IgG1_G2FS1)*100))
dteh(data$LC_IGP35 <- with(data, (IgG1_G1FS1+IgG1_G2FS1)/(IgG1_G0F+IgG1_G1F+IgG1_G1FS1+IgG1_G2F+IgG1_G2FS1)*100))
dteh(data$LC_IGP36 <- with(data, IgG1_G1FS1/(IgG1_G1F+IgG1_G1FS1)*100))
dteh(data$LC_IGP37 <- with(data, IgG1_G2FS1/(IgG1_G2F+IgG1_G2FS1)*100))
dteh(data$LC_IGP38 <- with(data, (IgG1_G1FNS1+IgG1_G2FNS1)/(IgG1_G1FN+IgG1_G1FNS1+IgG1_G2FN+IgG1_G2FNS1)*100))
dteh(data$LC_IGP39 <- with(data, (IgG1_G1FNS1+IgG1_G2FNS1)/(IgG1_G0FN+IgG1_G1FN+IgG1_G1FNS1+IgG1_G2FN+IgG1_G2FNS1)*100))
dteh(data$LC_IGP40 <- with(data, IgG1_G1FNS1/(IgG1_G1FN+IgG1_G1FNS1)*100))
dteh(data$LC_IGP41 <- with(data, IgG1_G2FNS1/(IgG1_G2FN+IgG1_G2FNS1)*100))
dteh(data$LC_IGP42 <- with(data, (IgG1_G1NS1+IgG1_G2NS1)/(IgG1_G1S1+IgG1_G2S1)))
dteh(data$LC_IGP43 <- with(data, (IgG1_G1FNS1+IgG1_G2FNS1)/(IgG1_G1FS1+IgG1_G2FS1)))
dteh(data$LC_IGP44 <- with(data, (IgG1_G1NS1+IgG1_G2NS1)/(IgG1_G1S1+IgG1_G1NS1+IgG1_G2S1+IgG1_G2NS1)))
dteh(data$LC_IGP45 <- with(data, (IgG1_G1FNS1+IgG1_G2FNS1)/(IgG1_G1FS1+IgG1_G1FNS1+IgG1_G2FS1+IgG1_G2FNS1)))
# neutral
dteh(IgG1.neutral <- with(data, IgG1_G0F+IgG1_G1F+IgG1_G2F+IgG1_G0FN+IgG1_G1FN+IgG1_G2FN+IgG1_G0+IgG1_G1+IgG1_G2+IgG1_G0N+IgG1_G1N+IgG1_G2N),
mess="Not all neutral glycans for IgG1 where found in the data frame")
dteh(data$LC_IGP46 <- with(data, IgG1_G0F/IgG1.neutral) * 100)
dteh(data$LC_IGP47 <- with(data, IgG1_G1F/IgG1.neutral) * 100)
dteh(data$LC_IGP48 <- with(data, IgG1_G2F/IgG1.neutral) * 100)
dteh(data$LC_IGP49 <- with(data, IgG1_G0FN/IgG1.neutral) * 100)
dteh(data$LC_IGP50 <- with(data, IgG1_G1FN/IgG1.neutral) * 100)
dteh(data$LC_IGP51 <- with(data, IgG1_G2FN/IgG1.neutral) * 100)
dteh(data$LC_IGP52 <- with(data, IgG1_G0/IgG1.neutral) * 100)
dteh(data$LC_IGP53 <- with(data, IgG1_G1/IgG1.neutral) * 100)
dteh(data$LC_IGP54 <- with(data, IgG1_G2/IgG1.neutral) * 100)
dteh(data$LC_IGP55 <- with(data, IgG1_G0N/IgG1.neutral) * 100)
dteh(data$LC_IGP56 <- with(data, IgG1_G1N/IgG1.neutral) * 100)
dteh(data$LC_IGP57 <- with(data, IgG1_G2N/IgG1.neutral) * 100)
# neutral - derived traits
dteh(data$LC_IGP58 <- with(data, (LC_IGP52+LC_IGP46+LC_IGP49+LC_IGP55)))
dteh(data$LC_IGP59 <- with(data, (LC_IGP53+LC_IGP47+LC_IGP50+LC_IGP56)))
dteh(data$LC_IGP60 <- with(data, (LC_IGP54+LC_IGP48+LC_IGP51+LC_IGP57)))
dteh(data$LC_IGP61 <- with(data, (LC_IGP46+LC_IGP49+LC_IGP47+LC_IGP50+LC_IGP48+LC_IGP51)))
dteh(data$LC_IGP62 <- with(data, (LC_IGP46+LC_IGP49)/LC_IGP58*100))
dteh(data$LC_IGP63 <- with(data, (LC_IGP47+LC_IGP50)/LC_IGP59*100))
dteh(data$LC_IGP64 <- with(data, (LC_IGP48+LC_IGP51)/LC_IGP60*100))
dteh(data$LC_IGP65 <- with(data, (LC_IGP46+LC_IGP47+LC_IGP48)))
dteh(data$LC_IGP66 <- with(data, LC_IGP46/LC_IGP58*100))
dteh(data$LC_IGP67 <- with(data, LC_IGP47/LC_IGP59*100))
dteh(data$LC_IGP68 <- with(data, LC_IGP48/LC_IGP60*100))
dteh(data$LC_IGP69 <- with(data, (LC_IGP49+LC_IGP50+LC_IGP51)))
dteh(data$LC_IGP70 <- with(data, LC_IGP49/LC_IGP58*100))
dteh(data$LC_IGP71 <- with(data, LC_IGP50/LC_IGP59*100))
dteh(data$LC_IGP72 <- with(data, LC_IGP51/LC_IGP60*100))
dteh(data$LC_IGP73 <- with(data, (LC_IGP55+LC_IGP56+LC_IGP57+LC_IGP49+LC_IGP50+LC_IGP51)))
dteh(data$LC_IGP74 <- with(data, (LC_IGP55+LC_IGP49)/LC_IGP58*100))
dteh(data$LC_IGP75 <- with(data, (LC_IGP56+LC_IGP50)/LC_IGP59*100))
dteh(data$LC_IGP76 <- with(data, (LC_IGP57+LC_IGP51)/LC_IGP60*100))
dteh(data$LC_IGP77 <- with(data, (LC_IGP55+LC_IGP56+LC_IGP57)))
dteh(data$LC_IGP78 <- with(data, LC_IGP55/LC_IGP58*100))
dteh(data$LC_IGP79 <- with(data, LC_IGP56/LC_IGP59*100))
dteh(data$LC_IGP80 <- with(data, LC_IGP57/LC_IGP60*100))
dteh(data$LC_IGP81 <- with(data, LC_IGP65/LC_IGP77))
dteh(data$LC_IGP82 <- with(data, LC_IGP69/LC_IGP65))
dteh(data$LC_IGP83 <- with(data, LC_IGP69/LC_IGP61*100))
dteh(data$LC_IGP84 <- with(data, LC_IGP69/LC_IGP73*100))
dteh(data$LC_IGP85 <- with(data, LC_IGP65/LC_IGP73))
dteh(data$LC_IGP86 <- with(data, LC_IGP77/LC_IGP61*1000))
# =======================================
# IgG2 derived traits
# =======================================
dteh(data$LC_IGP107 <- with(data, IgG2_G0F+IgG2_G1F+IgG2_G2F+IgG2_G0FN+IgG2_G1FN+IgG2_G2FN+IgG2_G1FS1+IgG2_G2FS1+IgG2_G1FNS1+IgG2_G2FNS1))
dteh(data$LC_IGP108 <- with(data, IgG2_G0FN+IgG2_G1FN+IgG2_G2FN+IgG2_G1FNS1+IgG2_G2FNS1+IgG2_G0N+IgG2_G1N+IgG2_G2N+IgG2_G1NS1+IgG2_G2NS1))
dteh(data$LC_IGP109 <- with(data, (IgG2_G1F+IgG2_G1FN+IgG2_G1FS1+IgG2_G1FNS1+IgG2_G1+IgG2_G1N+IgG2_G1S1+IgG2_G1NS1)*0.5+(IgG2_G2F+IgG2_G2FN+IgG2_G2FS1+IgG2_G2FNS1+IgG2_G2+IgG2_G2N+IgG2_G2S1+IgG2_G2NS1)))
dteh(data$LC_IGP110 <- with(data, IgG2_G1FS1+IgG2_G2FS1+IgG2_G1FNS1+IgG2_G2FNS1+IgG2_G1S1+IgG2_G2S1+IgG2_G1NS1+IgG2_G2NS1))
dteh(data$LC_IGP111 <- with(data, LC_IGP110/(2*LC_IGP109)*100))
dteh(data$LC_IGP112 <- with(data, (IgG2_G1S1+IgG2_G2S1)/(IgG2_G1+IgG2_G1S1+IgG2_G2+IgG2_G2S1)*100))
dteh(data$LC_IGP113 <- with(data, (IgG2_G1S1+IgG2_G2S1)/(IgG2_G0+IgG2_G1+IgG2_G1S1+IgG2_G2+IgG2_G2S1)*100))
dteh(data$LC_IGP114 <- with(data, IgG2_G1S1/(IgG2_G1+IgG2_G1S1)*100))
dteh(data$LC_IGP115 <- with(data, IgG2_G2S1/(IgG2_G2+IgG2_G2S1)*100))
dteh(data$LC_IGP116 <- with(data, (IgG2_G1NS1+IgG2_G2NS1)/(IgG2_G1N+IgG2_G1NS1+IgG2_G2N+IgG2_G2NS1)*100))
dteh(data$LC_IGP117 <- with(data, (IgG2_G1NS1+IgG2_G2NS1)/(IgG2_G0N+IgG2_G1N+IgG2_G1NS1+IgG2_G2N+IgG2_G2NS1)*100))
dteh(data$LC_IGP118 <- with(data, IgG2_G1NS1/(IgG2_G1N+IgG2_G1NS1)*100))
dteh(data$LC_IGP119 <- with(data, IgG2_G2NS1/(IgG2_G2N+IgG2_G2NS1)*100))
dteh(data$LC_IGP120 <- with(data, (IgG2_G1FS1+IgG2_G2FS1)/(IgG2_G1F+IgG2_G1FS1+IgG2_G2F+IgG2_G2FS1)*100))
dteh(data$LC_IGP121 <- with(data, (IgG2_G1FS1+IgG2_G2FS1)/(IgG2_G0F+IgG2_G1F+IgG2_G1FS1+IgG2_G2F+IgG2_G2FS1)*100))
dteh(data$LC_IGP122 <- with(data, IgG2_G1FS1/(IgG2_G1F+IgG2_G1FS1)*100))
dteh(data$LC_IGP123 <- with(data, IgG2_G2FS1/(IgG2_G2F+IgG2_G2FS1)*100))
dteh(data$LC_IGP124 <- with(data, (IgG2_G1FNS1+IgG2_G2FNS1)/(IgG2_G1FN+IgG2_G1FNS1+IgG2_G2FN+IgG2_G2FNS1)*100))
dteh(data$LC_IGP125 <- with(data, (IgG2_G1FNS1+IgG2_G2FNS1)/(IgG2_G0FN+IgG2_G1FN+IgG2_G1FNS1+IgG2_G2FN+IgG2_G2FNS1)*100))
dteh(data$LC_IGP126 <- with(data, IgG2_G1FNS1/(IgG2_G1FN+IgG2_G1FNS1)*100))
dteh(data$LC_IGP127 <- with(data, IgG2_G2FNS1/(IgG2_G2FN+IgG2_G2FNS1)*100))
dteh(data$LC_IGP128 <- with(data, (IgG2_G1NS1+IgG2_G2NS1)/(IgG2_G1S1+IgG2_G2S1)))
dteh(data$LC_IGP129 <- with(data, (IgG2_G1FNS1+IgG2_G2FNS1)/(IgG2_G1FS1+IgG2_G2FS1)))
dteh(data$LC_IGP130 <- with(data, (IgG2_G1NS1+IgG2_G2NS1)/(IgG2_G1S1+IgG2_G1NS1+IgG2_G2S1+IgG2_G2NS1)))
dteh(data$LC_IGP131 <- with(data, (IgG2_G1FNS1+IgG2_G2FNS1)/(IgG2_G1FS1+IgG2_G1FNS1+IgG2_G2FS1+IgG2_G2FNS1)))
# neutral
dteh(IgG2.neutral <- with(data, IgG2_G0F+IgG2_G1F+IgG2_G2F+IgG2_G0FN+IgG2_G1FN+IgG2_G2FN+IgG2_G0+IgG2_G1+IgG2_G2+IgG2_G0N+IgG2_G1N+IgG2_G2N),
mess="Not all neutral glycans for IgG2 where found in the data frame")
dteh(data$LC_IGP132 <- with(data, IgG2_G0F/IgG2.neutral) * 100)
dteh(data$LC_IGP133 <- with(data, IgG2_G1F/IgG2.neutral) * 100)
dteh(data$LC_IGP134 <- with(data, IgG2_G2F/IgG2.neutral) * 100)
dteh(data$LC_IGP135 <- with(data, IgG2_G0FN/IgG2.neutral) * 100)
dteh(data$LC_IGP136 <- with(data, IgG2_G1FN/IgG2.neutral) * 100)
dteh(data$LC_IGP137 <- with(data, IgG2_G2FN/IgG2.neutral) * 100)
dteh(data$LC_IGP138 <- with(data, IgG2_G0/IgG2.neutral) * 100)
dteh(data$LC_IGP139 <- with(data, IgG2_G1/IgG2.neutral) * 100)
dteh(data$LC_IGP140 <- with(data, IgG2_G2/IgG2.neutral) * 100)
dteh(data$LC_IGP141 <- with(data, IgG2_G0N/IgG2.neutral) * 100)
dteh(data$LC_IGP142 <- with(data, IgG2_G1N/IgG2.neutral) * 100)
dteh(data$LC_IGP143 <- with(data, IgG2_G2N/IgG2.neutral) * 100)
# neutral - derived traits
dteh(data$LC_IGP144 <- with(data, (LC_IGP138+LC_IGP132+LC_IGP135+LC_IGP141)))
dteh(data$LC_IGP145 <- with(data, (LC_IGP139+LC_IGP133+LC_IGP136+LC_IGP142)))
dteh(data$LC_IGP146 <- with(data, (LC_IGP140+LC_IGP134+LC_IGP137+LC_IGP143)))
dteh(data$LC_IGP147 <- with(data, (LC_IGP132+LC_IGP135+LC_IGP133+LC_IGP136+LC_IGP134+LC_IGP137)))
dteh(data$LC_IGP148 <- with(data, (LC_IGP132+LC_IGP135)/LC_IGP144*100))
dteh(data$LC_IGP149 <- with(data, (LC_IGP133+LC_IGP136)/LC_IGP145*100))
dteh(data$LC_IGP150 <- with(data, (LC_IGP134+LC_IGP137)/LC_IGP146*100))
dteh(data$LC_IGP151 <- with(data, (LC_IGP132+LC_IGP133+LC_IGP134)))
dteh(data$LC_IGP152 <- with(data, LC_IGP132/LC_IGP144*100))
dteh(data$LC_IGP153 <- with(data, LC_IGP133/LC_IGP145*100))
dteh(data$LC_IGP154 <- with(data, LC_IGP134/LC_IGP146*100))
dteh(data$LC_IGP155 <- with(data, (LC_IGP135+LC_IGP136+LC_IGP137)))
dteh(data$LC_IGP156 <- with(data, LC_IGP135/LC_IGP144*100))
dteh(data$LC_IGP157 <- with(data, LC_IGP136/LC_IGP145*100))
dteh(data$LC_IGP158 <- with(data, LC_IGP137/LC_IGP146*100))
dteh(data$LC_IGP159 <- with(data, (LC_IGP141+LC_IGP142+LC_IGP143+LC_IGP135+LC_IGP136+LC_IGP137)))
dteh(data$LC_IGP160 <- with(data, (LC_IGP141+LC_IGP135)/LC_IGP144*100))
dteh(data$LC_IGP161 <- with(data, (LC_IGP142+LC_IGP136)/LC_IGP145*100))
dteh(data$LC_IGP162 <- with(data, (LC_IGP143+LC_IGP137)/LC_IGP146*100))
dteh(data$LC_IGP163 <- with(data, (LC_IGP141+LC_IGP142+LC_IGP143)))
dteh(data$LC_IGP164 <- with(data, LC_IGP141/LC_IGP144*100))
dteh(data$LC_IGP165 <- with(data, LC_IGP142/LC_IGP145*100))
dteh(data$LC_IGP166 <- with(data, LC_IGP143/LC_IGP146*100))
dteh(data$LC_IGP167 <- with(data, LC_IGP151/LC_IGP163))
dteh(data$LC_IGP168 <- with(data, LC_IGP155/LC_IGP151))
dteh(data$LC_IGP169 <- with(data, LC_IGP155/LC_IGP147*100))
dteh(data$LC_IGP170 <- with(data, LC_IGP155/LC_IGP159*100))
dteh(data$LC_IGP171 <- with(data, LC_IGP151/LC_IGP159))
dteh(data$LC_IGP172 <- with(data, LC_IGP163/LC_IGP147*1000))
# =======================================
# IgG4 derived traits
# =======================================
dteh(data$LC_IGP183 <- with(data, (IgG4_G0FN+IgG4_G1FN+IgG4_G2FN+IgG4_G1FNS1+IgG4_G2FNS1) ))
dteh(data$LC_IGP184 <- with(data, (IgG4_G1F+IgG4_G1FN+IgG4_G1FS1+IgG4_G1FNS1)*0.5+(IgG4_G2F+IgG4_G2FN+IgG4_G2FS1+IgG4_G2FNS1)))
dteh(data$LC_IGP185 <- with(data, (IgG4_G1FS1+IgG4_G2FS1+IgG4_G1FNS1+IgG4_G2FNS1)))
dteh(data$LC_IGP186 <- with(data, LC_IGP185/(2*LC_IGP184)*100))
dteh(data$LC_IGP187 <- with(data, (IgG4_G1FS1+IgG4_G2FS1)/(IgG4_G1F+IgG4_G1FS1+IgG4_G2F+IgG4_G2FS1)*100))
dteh(data$LC_IGP188 <- with(data, (IgG4_G1FS1+IgG4_G2FS1)/(IgG4_G0F+IgG4_G1F+IgG4_G1FS1+IgG4_G2F+IgG4_G2FS1)*100))
dteh(data$LC_IGP189 <- with(data, IgG4_G1FS1/(IgG4_G1F+IgG4_G1FS1)*100))
dteh(data$LC_IGP190 <- with(data, IgG4_G2FS1/(IgG4_G2F+IgG4_G2FS1)*100))
dteh(data$LC_IGP191 <- with(data, (IgG4_G1FNS1+IgG4_G2FNS1)/(IgG4_G1FN+IgG4_G1FNS1+IgG4_G2FN+IgG4_G2FNS1)*100))
dteh(data$LC_IGP192 <- with(data, (IgG4_G1FNS1+IgG4_G2FNS1)/(IgG4_G0FN+IgG4_G1FN+IgG4_G1FNS1+IgG4_G2FN+IgG4_G2FNS1)*100))
dteh(data$LC_IGP193 <- with(data, IgG4_G1FNS1/(IgG4_G1FN+IgG4_G1FNS1)*100))
dteh(data$LC_IGP194 <- with(data, IgG4_G2FNS1/(IgG4_G2FN+IgG4_G2FNS1)*100))
dteh(data$LC_IGP195 <- with(data, (IgG4_G1FNS1+IgG4_G2FNS1)/(IgG4_G1FS1+IgG4_G2FS1)))
dteh(data$LC_IGP196 <- with(data, (IgG4_G1FNS1+IgG4_G2FNS1)/(IgG4_G1FS1+IgG4_G1FNS1+IgG4_G2FS1+IgG4_G2FNS1)))
# neutral
dteh(IgG4.neutral <- with(data, IgG4_G0F+IgG4_G1F+IgG4_G2F+IgG4_G0FN+IgG4_G1FN+IgG4_G2FN),
mess="Not all neutral glycans for IgG4 where found in the data frame")
dteh(data$LC_IGP197 <- with(data, IgG4_G0F/IgG4.neutral) * 100)
dteh(data$LC_IGP198 <- with(data, IgG4_G1F/IgG4.neutral) * 100)
dteh(data$LC_IGP199 <- with(data, IgG4_G2F/IgG4.neutral) * 100)
dteh(data$LC_IGP200 <- with(data, IgG4_G0FN/IgG4.neutral) * 100)
dteh(data$LC_IGP201 <- with(data, IgG4_G1FN/IgG4.neutral) * 100)
dteh(data$LC_IGP202 <- with(data, IgG4_G2FN/IgG4.neutral) * 100)
# neutral - derived traits
dteh(data$LC_IGP203 <- with(data, LC_IGP197 + LC_IGP200))
dteh(data$LC_IGP204 <- with(data, LC_IGP198 + LC_IGP201))
dteh(data$LC_IGP205 <- with(data, LC_IGP199 + LC_IGP202))
return(data)
}
# Translate names between computer readable and human readable
# for derived traits of IgG with LCMS
# based on paper from 2014.
#
# Translates names between computer readable and human readable
# for derived traits of IgG with LCMS
#
# @author Ivo Ugrina
# @param orignames vector; type string
# @param to type of translation. If \code{inverse} is used everything will be
# translated. For \code{computer} names will be translated to computer
# readable, and for \code{human} names will be translated to human readable.
# @return Returns a character vector with original and translated names
# @references
# Jennifer E. Huffman et al.
# "Comparative Performance of Four Methods for High-throughput Glycosylation Analysis of Immunoglobulin G in Genetic and Epidemiological Research*"
# \doi{10.1074/mcp.M113.037465}
ildt.translate.2014 <- function(orignames, to="inverse") {
allnames <- "computer human
LC_IGP1 IgG1_G0F
LC_IGP2 IgG1_G1F
LC_IGP3 IgG1_G2F
LC_IGP4 IgG1_G0FN
LC_IGP5 IgG1_G1FN
LC_IGP6 IgG1_G2FN
LC_IGP7 IgG1_G1FS1
LC_IGP8 IgG1_G2FS1
LC_IGP9 IgG1_G1FNS1
LC_IGP10 IgG1_G2FNS1
LC_IGP11 IgG1_G0
LC_IGP12 IgG1_G1
LC_IGP13 IgG1_G2
LC_IGP14 IgG1_G0N
LC_IGP15 IgG1_G1N
LC_IGP16 IgG1_G2N
LC_IGP17 IgG1_G1S1
LC_IGP18 IgG1_G2S1
LC_IGP19 IgG1_G1NS1
LC_IGP20 IgG1_G2NS1
LC_IGP21 IgG1 Fucosylation
LC_IGP22 IgG1 Bisecting_GlcNAc
LC_IGP23 IgG1 Galactosylation
LC_IGP24 IgG1 Sialylation
LC_IGP25 IgG1 SA per Gal
LC_IGP26 IgG1 GS1/(G+GS1)
LC_IGP27 IgG1 GS1/(G0+G+GS1)
LC_IGP28 IgG1 G1S1/(G1+G1S1)
LC_IGP29 IgG1 G2S1/(G2+G2S1)
LC_IGP30 IgG1 BGS1/(BG+BGS1)
LC_IGP31 IgG1 BGS1/(BG0+BG+BGS1)
LC_IGP32 IgG1 BG1S1/(BG1+BG1S1)
LC_IGP33 IgG1 BG2S1/(BG2+BG2S1)
LC_IGP34 IgG1 FGS1/(FG+FGS1)
LC_IGP35 IgG1 FGS1/(F+FG+FGS1)
LC_IGP36 IgG1 FG1S1/(FG1+FG1S1)
LC_IGP37 IgG1 FG2S1/(FG2+FG2S1)
LC_IGP38 IgG1 FBGS1/(FBG+FBGS1)
LC_IGP39 IgG1 FBGS1/(FB+FBG+FBGS1)
LC_IGP40 IgG1 FBG1S1/(FBG1+FBG1S1)
LC_IGP41 IgG1 FBG2S1/(FBG2+FBG2S1)
LC_IGP42 IgG1 BS1/S1
LC_IGP43 IgG1 FBS1/FS1
LC_IGP44 IgG1 BS1/(S1+BS1)
LC_IGP45 IgG1 FBS1/(FS1+FBS1)
LC_IGP46 IgG1_G0Fn
LC_IGP47 IgG1_G1Fn
LC_IGP48 IgG1_G2Fn
LC_IGP49 IgG1_G0FNn
LC_IGP50 IgG1_G1FNn
LC_IGP51 IgG1_G2FNn
LC_IGP52 IgG1_G0n
LC_IGP53 IgG1_G1n
LC_IGP54 IgG1_G2n
LC_IGP55 IgG1_G0Nn
LC_IGP56 IgG1_G1Nn
LC_IGP57 IgG1_G2Nn
LC_IGP58 IgG1G0n
LC_IGP59 IgG1G1n
LC_IGP60 IgG1G2n
LC_IGP61 IgG1 Fn total
LC_IGP62 IgG1 FG0n total/G0n
LC_IGP63 IgG1 FG1n total/G1n
LC_IGP64 IgG1 FG2n total/G2n
LC_IGP65 IgG1 Fn
LC_IGP66 IgG1 FG0n/G0n
LC_IGP67 IgG1 FG1n/G1n
LC_IGP68 IgG1 FG2n/G2n
LC_IGP69 IgG1 FBn
LC_IGP70 IgG1 FBG0n/G0n
LC_IGP71 IgG1 FBG1n/G1n
LC_IGP72 IgG1 FBG2n/G2n
LC_IGP73 IgG1 Bn total
LC_IGP74 IgG1 BG0n total/G0n
LC_IGP75 IgG1 BG1n total/G1n
LC_IGP76 IgG1 BG2n total/G2n
LC_IGP77 IgG1 Bn
LC_IGP78 IgG1 BG0n/G0n
LC_IGP79 IgG1 BG1n/G1n
LC_IGP80 IgG1 BG2n/G2n
LC_IGP81 IgG1 Fn/Bn
LC_IGP82 IgG1 FBn/Fn
LC_IGP83 IgG1 FBn/Fn total
LC_IGP84 IgG1 FBn/Bn total
LC_IGP85 IgG1 Fn/Bn total
LC_IGP86 IgG1 Bn/Fn total
LC_IGP87 IgG2_G0F
LC_IGP88 IgG2_G1F
LC_IGP89 IgG2_G2F
LC_IGP90 IgG2_G0FN
LC_IGP91 IgG2_G1FN
LC_IGP92 IgG2_G2FN
LC_IGP93 IgG2_G1FS1
LC_IGP94 IgG2_G2FS1
LC_IGP95 IgG2_G1FNS1
LC_IGP96 IgG2_G2FNS1
LC_IGP97 IgG2_G0
LC_IGP98 IgG2_G1
LC_IGP99 IgG2_G2
LC_IGP100 IgG2_G0N
LC_IGP101 IgG2_G1N
LC_IGP102 IgG2_G2N
LC_IGP103 IgG2_G1S1
LC_IGP104 IgG2_G2S1
LC_IGP105 IgG2_G1NS1
LC_IGP106 IgG2_G2NS1
LC_IGP107 IgG2 Fucosylation
LC_IGP108 IgG2 Bisecting GlcNAc
LC_IGP109 IgG2 Galactosylation
LC_IGP110 IgG2 Sialylation
LC_IGP111 IgG2 SA per Gal
LC_IGP112 IgG2 GS1/(G+GS1)
LC_IGP113 IgG2 GS1/(G0+G+GS1)
LC_IGP114 IgG2 G1S1/(G1+G1S1)
LC_IGP115 IgG2 G2S1/(G2+G2S1)
LC_IGP116 IgG2 BGS1/(BG+BGS1)
LC_IGP117 IgG2 BGS1/(BG0+BG+BGS1)
LC_IGP118 IgG2 BG1S1/(BG1+BG1S1)
LC_IGP119 IgG2 BG2S1/(BG2+BG2S1)
LC_IGP120 IgG2 FGS1/(FG+FGS1)
LC_IGP121 IgG2 FGS1/(F+FG+FGS1)
LC_IGP122 IgG2 FG1S1/(FG1+FG1S1)
LC_IGP123 IgG2 FG2S1/(FG2+FG2S1)
LC_IGP124 IgG2 FBGS1/(FBG+FBGS1)
LC_IGP125 IgG2 FBGS1/(FB+FBG+FBGS1)
LC_IGP126 IgG2 FBG1S1/(FBG1+FBG1S1)
LC_IGP127 IgG2 FBG2S1/(FBG2+FBG2S1)
LC_IGP128 IgG2 BS1/S1
LC_IGP129 IgG2 FBS1/FS1
LC_IGP130 IgG2 BS1/(S1+BS1)
LC_IGP131 IgG2 FBS1/(FS1+FBS1)
LC_IGP132 IgG2_G0Fn
LC_IGP133 IgG2_G1Fn
LC_IGP134 IgG2_G2Fn
LC_IGP135 IgG2_G0FNn
LC_IGP136 IgG2_G1FNn
LC_IGP137 IgG2_G2FNn
LC_IGP138 IgG2_G0n
LC_IGP139 IgG2_G1n
LC_IGP140 IgG2_G2n
LC_IGP141 IgG2_G0Nn
LC_IGP142 IgG2_G1Nn
LC_IGP143 IgG2_G2Nn
LC_IGP144 IgG2G0n
LC_IGP145 IgG2G1n
LC_IGP146 IgG2G2n
LC_IGP147 IgG2 Fn total
LC_IGP148 IgG2 FG0n total/G0n
LC_IGP149 IgG2 FG1n total/G1n
LC_IGP150 IgG2 FG2n total/G2n
LC_IGP151 IgG2 Fn
LC_IGP152 IgG2 FG0n/G0n
LC_IGP153 IgG2 FG1n/G1n
LC_IGP154 IgG2 FG2n/G2n
LC_IGP155 IgG2 FBn
LC_IGP156 IgG2 FBG0n/G0n
LC_IGP157 IgG2 FBG1n/G1n
LC_IGP158 IgG2 FBG2n/G2n
LC_IGP159 IgG2 Bn total
LC_IGP160 IgG2 BG0n total/G0n
LC_IGP161 IgG2 BG1n total/G1n
LC_IGP162 IgG2 BG2n total/G2n
LC_IGP163 IgG2 Bn
LC_IGP164 IgG2 BG0n/G0n
LC_IGP165 IgG2 BG1n/G1n
LC_IGP166 IgG2 BG2n/G2n
LC_IGP167 IgG2 Fn/Bn
LC_IGP168 IgG2 FBn/Fn
LC_IGP169 IgG2 FBn/Fn total
LC_IGP170 IgG2 FBn/Bn total
LC_IGP171 IgG2 Fn/Bn total
LC_IGP172 IgG2 Bn/Fn total
LC_IGP173 IgG4_G0F
LC_IGP174 IgG4_G1F
LC_IGP175 IgG4_G2F
LC_IGP176 IgG4_G0FN
LC_IGP177 IgG4_G1FN
LC_IGP178 IgG4_G2FN
LC_IGP179 IgG4_G1FS1
LC_IGP180 IgG4_G2FS1
LC_IGP181 IgG4_G1FNS1
LC_IGP182 IgG4_G2FNS1
LC_IGP183 IgG4 Bisecting GlcNAc
LC_IGP184 IgG4 Galactosylation
LC_IGP185 IgG4 Sialylation
LC_IGP186 IgG4 SA per Gal
LC_IGP187 IgG4 FGS1/(FG+FGS1)
LC_IGP188 IgG4 FGS1/(F+FG+FGS1)
LC_IGP189 IgG4 FG1S1/(FG1+FG1S1)
LC_IGP190 IgG4 FG2S1/(FG2+FG2S1)
LC_IGP191 IgG4 FBGS1/(FBG+FBGS1)
LC_IGP192 IgG4 FBGS1/(FB+FBG+FBGS1)
LC_IGP193 IgG4 FBG1S1/(FBG1+FBG1S1)
LC_IGP194 IgG4 FBG2S1/(FBG2+FBG2S1)
LC_IGP195 IgG4 FBS1/FS1
LC_IGP196 IgG4 FBS1/(FS1+FBS1)
LC_IGP197 IgG4_G0Fn
LC_IGP198 IgG4_G1Fn
LC_IGP199 IgG4_G2Fn
LC_IGP200 IgG4_G0FNn
LC_IGP201 IgG4_G1FNn
LC_IGP202 IgG4_G2FNn
LC_IGP203 IgG4G0n
LC_IGP204 IgG4G1n
LC_IGP205 IgG4G2n"
con <- textConnection(allnames)
allnames <- read.delim(con, sep="\t", header=TRUE, stringsAsFactors=FALSE)
close(con)
cn <- match(orignames, allnames$computer)
hn <- match(orignames, allnames$human)
if(to=="inverse"){
newnames <- ifelse(!is.na(cn),
allnames$human[cn],
allnames$computer[hn])
}
if(to=="computer"){
newnames <- ifelse(!is.na(cn),
allnames$computer[cn],
allnames$computer[hn])
}
if(to=="human"){
newnames <- ifelse(!is.na(hn),
allnames$human[hn],
allnames$human[cn])
}
return(newnames)
}
# Translate names between computer readable and human readable
# for derived traits of IgG with UPLC
# based on an article from 2014.
#
# Translates names between computer readable and human readable
# for derived traits of IgG with UPLC
#
# @author Ivo Ugrina
# @param orignames vector; type string
# @param to type of translation. If \code{inverse} is used everything will be
# translated. For \code{computer} names will be translated to computer
# readable, and for \code{human} names will be translated to human readable.
# @return Returns a character vector with original and translated names
# @references
# Jennifer E. Huffman et al.
# "Comparative Performance of Four Methods for High-throughput Glycosylation Analysis of Immunoglobulin G in Genetic and Epidemiological Research*"
# \doi{10.1074/mcp.M113.037465}
iudt.translate.2014 <- function(orignames, to="inverse") {
allnames <- "computer human
IGP1 GP1
IGP2 GP2
IGP3 GP4
IGP4 GP5
IGP5 GP6
IGP6 GP7
IGP7 GP8
IGP8 GP9
IGP9 GP10
IGP10 GP11
IGP11 GP12
IGP12 GP13
IGP13 GP14
IGP14 GP15
IGP15 GP16
IGP16 GP17
IGP17 GP18
IGP18 GP19
IGP19 GP20
IGP20 GP21
IGP21 GP22
IGP22 GP23
IGP23 GP24
IGP24 FGS/(FG+FGS)
IGP25 FBGS/(FBG+FBGS)
IGP26 FGS/(F+FG+FGS)
IGP27 FBGS/(FB+FBG+FBGS)
IGP28 FG1S1/(FG1+FG1S1)
IGP29 FG2S1/(FG2+FG2S1+FG2S2)
IGP30 FG2S2/(FG2+FG2S1+FG2S2)
IGP31 FBG2S1/(FBG2+FBG2S1+FBG2S2)
IGP32 FBG2S2/(FBG2+FBG2S1+FBG2S2)
IGP33 FtotalS1/FtotalS2
IGP34 FS1/FS2
IGP35 FBS1/FBS2
IGP36 FBStotal/FStotal
IGP37 FBS1/FS1
IGP38 FBS1/(FS1+FBS1)
IGP39 FBS2/FS2
IGP40 FBS2/(FS2+FBS2)
IGP41 GP1n
IGP42 GP2n
IGP43 GP4n
IGP44 GP5n
IGP45 GP6n
IGP46 GP7n
IGP47 GP8n
IGP48 GP9n
IGP49 GP10n
IGP50 GP11n
IGP51 GP12n
IGP52 GP13n
IGP53 GP14n
IGP54 GP15n
IGP55 G0n
IGP56 G1n
IGP57 G2n
IGP58 Fn total
IGP59 FG0n total/G0n
IGP60 FG1n total/G1n
IGP61 FG2n total/G2n
IGP62 Fn
IGP63 FG0n/G0n
IGP64 FG1n/G1n
IGP65 FG2n/G2n
IGP66 FBn
IGP67 FBG0n/G0n
IGP68 FBG1n/G1n
IGP69 FBG2n/G2n
IGP70 FBn/Fn
IGP71 FBn/Fn total
IGP72 Fn/(Bn+ FBn)
IGP73 Bn/(Fn+ FBn)
IGP74 FBG2n/FG2n
IGP75 FBG2n/(FG2n+ FBG2n)
IGP76 FG2n/(BG2n+ FBG2n)
IGP77 BG2n/(FG2n+ FBG2n)"
con <- textConnection(allnames)
allnames <- read.delim(con, sep="\t", header=TRUE, stringsAsFactors=FALSE)
close(con)
cn <- match(orignames, allnames$computer)
hn <- match(orignames, allnames$human)
if(to=="inverse"){
newnames <- ifelse(!is.na(cn),
allnames$human[cn],
allnames$computer[hn])
}
if(to=="computer"){
newnames <- ifelse(!is.na(cn),
allnames$computer[cn],
allnames$computer[hn])
}
if(to=="human"){
newnames <- ifelse(!is.na(hn),
allnames$human[hn],
allnames$human[cn])
}
return(newnames)
}
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