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\documentclass[11pt, oneside]{article} % use "amsart" instead of "article" for AMSLaTeX format
%\usepackage{geometry} % See geometry.pdf to learn the layout options. There are lots.
%\geometry{letterpaper} % ... or a4paper or a5paper or ...
%\geometry{landscape} % Activate for for rotated page geometry
%\usepackage[parfill]{parskip} % Activate to begin paragraphs with an empty line rather than an indent
%\usepackage{graphicx} % Use pdf, png, jpg, or eps with pdflatex; use eps in DVI mode
% TeX will automatically convert eps --> pdf in pdflatex
%\usepackage{amssymb}
\usepackage[utf8]{inputenc}
%\usepackage[cyr]{aeguill}
%\usepackage[francais]{babel}
%\usepackage{hyperref}
\title{Positive selection on genes interacting with SARS-Cov2, comparison of different analysis}
\author{Marie Cariou}
\date{Janvier 2021} % Activate to display a given date or no date
\begin{document}
\maketitle
\tableofcontents
\newpage
\section{Files manipulations}
\subsection{Read Janet Young's table}
<<>>=
workdir<-"/home/adminmarie/Documents/CIRI_BIBS_projects/2020_05_Etienne_covid/"
tab<-read.delim(paste0(workdir,
"data/COVID_PAMLresults_332hits_plusBatScreens_2020_Apr14.csv"),
fill=T, h=T, dec=",")
dim(tab)
@
\subsection{Read DGINN Young table}
<<>>=
dginnY<-read.delim(paste0(workdir,
"data/summary_primate_young.res"),
fill=T, h=T)
dim(dginnY)
@
\subsection{Joining Young and DGINN Young table}
<<>>=
# correct gene names (MARC1)
val_remp=as.character(unique(dginnY$Gene)[(unique(dginnY$Gene) %in%
tab$Gene.name)==F])
tab$Gene.name<-as.character(tab$Gene.name)
tab$Gene.name[158]<-val_remp
sum(unique(dginnY$Gene) %in% unique(tab$Gene.name))
@
<<>>=
add_col<-function(method="PamlM1M2"){
tmp<-dginnY[dginnY$Method==method,
c("Gene", "Omega", "PosSel", "PValue", "NbSites", "PSS")]
names(tmp)<-c("Gene.name", paste0("Omega_", method),
paste0("PosSel_", method), paste0("PValue_", method),
paste0("NbSites_", method), paste0("PSS_", method))
tab<-merge(tab, tmp, by="Gene.name")
return(tab)
}
tab<-add_col("PamlM1M2")
tab<-add_col("PamlM7M8")
tab<-add_col("BppM1M2")
tab<-add_col("BppM7M8")
# Manip pour la colonne BUSTED
tmp<-dginnY[dginnY$Method=="BUSTED",c("Gene", "Omega", "PosSel", "PValue")]
names(tmp)<-c("Gene.name", "Omega_BUSTED", "PosSel_BUSTED", "PValue_BUSTED")
tab<-merge(tab, tmp, by="Gene.name")
tmp<-dginnY[dginnY$Method=="MEME",c("Gene", "NbSites", "PSS")]
names(tmp)<-c("Gene.name", "NbSites_MEME", "PSS_MEME")
tab<-merge(tab, tmp, by="Gene.name")
@
\subsection{Read DGINN Table}
<<>>=
dginnT<-read.delim(paste0(workdir,
"data/DGINN_202005281649summary_cleaned.csv"),
fill=T, h=T, sep=",")
dim(dginnT)
names(dginnT)
# Number of genes in dginn-primate output not present in the original table
dginnT[(dginnT$Gene %in% tab$Gene.name)==F,"Gene"]
# This includes paralogs, recombinations found by DGINN and additionnal genes
# included on purpose
# Number of genes from the original list not present in DGINN output
tab[(tab$Gene.name %in% dginnT$Gene)==F,"Gene.name"]
names(dginnT)<-c("File", "Name", "Gene.name", "GeneSize",
"dginn-primate_NbSpecies", "dginn-primate_omegaM0Bpp",
"dginn-primate_omegaM0codeml", "dginn-primate_BUSTED",
"dginn-primate_BUSTED.p.value", "dginn-primate_MEME.NbSites",
"dginn-primate_MEME.PSS", "dginn-primate_BppM1M2",
"dginn-primate_BppM1M2.p.value", "dginn-primate_BppM1M2.NbSites",
"dginn-primate_BppM1M2.PSS", "dginn-primate_BppM7M8",
"dginn-primate_BppM7M8.p.value", "dginn-primate_BppM7M8.NbSites",
"dginn-primate_BppM7M8.PSS", "dginn-primate_codemlM1M2",
"dginn-primate_codemlM1M2.p.value", "dginn-primate_codemlM1M2.NbSites",
"dginn-primate_codemlM1M2.PSS", "dginn-primate_codemlM7M8",
"dginn-primate_codemlM7M8.p.value", "dginn-primate_codemlM7M8.NbSites",
"dginn-primate_codemlM7M8.PSS")
@
<<eval=FALSE>>=
table(dginnT$`dginn-primate_BUSTED`)
table(dginnT$`dginn-primate_codemlM1M2`)
table(dginnT$`dginn-primate_codemlM7M8`)
table(dginnT$`dginn-primate_BppM1M2`)
table(dginnT$`dginn-primate_BppM7M8`)
table(dginnT$`dginn-primate_BUSTED`=="na",dginnT$`dginn-primate_codemlM1M2`=="na", dginnT$`dginn-primate_codemlM7M8`=="na",
dginnT$`dginn-primate_BppM1M2`=="na", dginnT$`dginn-primate_BppM7M8`=="na" )
@
\subsection{Join Table and DGINN table}
<<>>=
tab<-merge(tab,dginnT, by="Gene.name", all.x=T)
table(tab$`dginn-primate_BUSTED`)
table(tab$`dginn-primate_codemlM1M2`)
table(tab$`dginn-primate_codemlM7M8`)
table(tab$`dginn-primate_BppM1M2`)
table(tab$`dginn-primate_BppM7M8`)
table(tab$`dginn-primate_BUSTED`=="na" | tab$`dginn-primate_codemlM1M2`=="na" | tab$`dginn-primate_codemlM7M8`=="na" |
tab$`dginn-primate_BppM1M2`=="na"| tab$`dginn-primate_BppM7M8`=="na" )
@
\subsection{Add DGINN results on bat dataset}
DGINN results from different analysis.
<<>>=
# original table
dginnbats<-read.delim(paste0(workdir,
"data/DGINN_202005281339summary_cleaned.tab"),
fill=T, h=T)
# rerun on corrected alignment
dginnbatsnew1<-read.delim(paste0(workdir,
"data/DGINN_202011262248_summary.tab"),
fill=T, h=T)
dginnbatsnew2<-read.delim(paste0(workdir,
"data/DGINN_202012192053_summary.tab"),
fill=T, h=T)
# colomne choice, BUSTED and Bppml form first file, codeml from the other one
dginnbatsnew<-dginnbatsnew1
dginnbatsnew$omegaM0codeml<-dginnbatsnew2$omegaM0codeml
dginnbatsnew$codemlM1M2<-dginnbatsnew2$codemlM1M2
dginnbatsnew$codemlM1M2_p.value<-dginnbatsnew2$codemlM1M2_p.value
dginnbatsnew$codemlM1M2_NbSites<-dginnbatsnew2$codemlM1M2_NbSites
dginnbatsnew$codemlM1M2_PSS<-dginnbatsnew2$codemlM1M2_PSS
dginnbatsnew$codemlM7M8<-dginnbatsnew2$codemlM7M8
dginnbatsnew$codemlM7M8_p.value<-dginnbatsnew2$codemlM7M8_p.value
dginnbatsnew$codemlM7M8_NbSites<-dginnbatsnew2$codemlM7M8_NbSites
dginnbatsnew$codemlM7M8_PSS<-dginnbatsnew2$codemlM7M8_PSS
####
## RIPK1 is actually a primat results
## 1. Take it and put it at the right place
ripk1<-as.vector(dginnbatsnew[dginnbatsnew$Gene=="RIPK1",])
tab$`dginn-primate_omegaM0Bpp`<-as.numeric(as.character(tab$`dginn-primate_omegaM0Bpp`))
tab$`dginn-primate_BUSTED.p.value`<-as.numeric(as.character(tab$`dginn-primate_BUSTED.p.value`))
tab$`dginn-primate_BppM1M2.p.value`<-as.numeric(as.character(tab$`dginn-primate_BppM1M2.p.value`))
tab$`dginn-primate_BppM7M8.p.value`<-as.numeric(as.character(tab$`dginn-primate_BppM7M8.p.value`))
tab$`dginn-primate_BppM7M8.PSS`<-as.numeric(as.character(tab$`dginn-primate_BppM7M8.PSS`))
tab$`dginn-primate_codemlM1M2.p.value`<-as.numeric(as.character(tab$`dginn-primate_codemlM1M2.p.value`))
tab$`dginn-primate_codemlM1M2.PSS`<-as.numeric(as.character(tab$`dginn-primate_codemlM1M2.PSS`))
tab$`dginn-primate_codemlM7M8.p.value`<-as.numeric(as.character(tab$`dginn-primate_codemlM7M8.p.value`))
tab$`dginn-primate_codemlM7M8.PSS`<-as.numeric(as.character(tab$`dginn-primate_codemlM7M8.PSS`))
tab[tab$Gene.name=="RIPK1","GeneSize"]<-ripk1$GeneSize
tab[tab$Gene.name=="RIPK1","dginn-primate_NbSpecies"]<-ripk1$NbSpecies
tab[tab$Gene.name=="RIPK1","dginn-primate_omegaM0Bpp"]<-ripk1$omegaM0Bpp
tab[tab$Gene.name=="RIPK1","dginn-primate_omegaM0codeml"]<-ripk1$omegaM0codeml
tab[tab$Gene.name=="RIPK1","dginn-primate_BUSTED"]<-ripk1$BUSTED
tab[tab$Gene.name=="RIPK1","dginn-primate_BUSTED.p.value"]<-ripk1$BUSTED_p.value
tab[tab$Gene.name=="RIPK1","dginn-primate_MEME.NbSites"]<-ripk1$MEME_NbSites
tab[tab$Gene.name=="RIPK1","dginn-primate_MEME.PSS"]<-as.numeric(as.character(ripk1$MEME_PSS))
tab[tab$Gene.name=="RIPK1","dginn-primate_BppM1M2"]<-ripk1$BppM1M2
tab[tab$Gene.name=="RIPK1","dginn-primate_BppM1M2.p.value"]<-ripk1$BppM1M2_p.value
tab[tab$Gene.name=="RIPK1","dginn-primate_BppM1M2.NbSites"]<-ripk1$BppM1M2_NbSites
tab[tab$Gene.name=="RIPK1","dginn-primate_BppM1M2.PSS"]<-ripk1$BppM1M2_PSS
tab[tab$Gene.name=="RIPK1","dginn-primate_BppM7M8"]<-ripk1$BppM7M8
tab[tab$Gene.name=="RIPK1","dginn-primate_BppM7M8.p.value"]<-ripk1$BppM7M8_p.value
tab[tab$Gene.name=="RIPK1","dginn-primate_BppM7M8.NbSites"]<-ripk1$BppM7M8_NbSites
tab[tab$Gene.name=="RIPK1","dginn-primate_BppM7M8.PSS"]<-ripk1$BppM7M8_PSS
tab[tab$Gene.name=="RIPK1","dginn-primate_codemlM1M2"]<-ripk1$codemlM1M2
tab[tab$Gene.name=="RIPK1","dginn-primate_codemlM1M2.p.value"]<-ripk1$codemlM1M2_p.value
tab[tab$Gene.name=="RIPK1","dginn-primate_codemlM1M2.NbSites"]<-ripk1$codemlM1M2_NbSites
tab[tab$Gene.name=="RIPK1","dginn-primate_codemlM1M2.PSS"]<-ripk1$codemlM1M2_PSS
tab[tab$Gene.name=="RIPK1","dginn-primate_codemlM7M8"]<-ripk1$codemlM7M8
tab[tab$Gene.name=="RIPK1","dginn-primate_codemlM7M8.p.value"]<-ripk1$codemlM7M8_p.value
tab[tab$Gene.name=="RIPK1","dginn-primate_codemlM7M8.NbSites"]<-ripk1$codemlM7M8_NbSites
tab[tab$Gene.name=="RIPK1","dginn-primate_codemlM7M8.PSS"]<-ripk1$codemlM7M8_PSS
## 2. Remove it
dginnbatsnew<-dginnbatsnew[dginnbatsnew$Gene!="RIPK1",]
## suppress redundant lines
dginnbats<-dginnbats[(dginnbats$Gene %in% dginnbatsnew$Gene)==FALSE,]
names(dginnbatsnew)<-names(dginnbats)
##############"
dginnbatsnew[,4]<-as.numeric(dginnbatsnew[,4])
dginnbats[,6]<-as.numeric(as.character(dginnbats[,6]))
dginnbats[,8]<-as.character(dginnbats[,8])
dginnbats[,12]<-as.character(dginnbats[,12])
dginnbats[,13]<-as.numeric(as.character(dginnbats[,13]))
dginnbats[,16]<-as.character(dginnbats[,16])
dginnbats[,17]<-as.numeric(as.character(dginnbats[,17]))
## replace by new data
dginnbats<-rbind(dginnbats, dginnbatsnew)
names(dginnbats)<-c("File", "bats_Name", "cooper.batsGene", paste0("bats_",
names(dginnbats)[-(1:3)]))
names(dginnbats)
tab<-merge(tab,dginnbats, by="cooper.batsGene", all.x=T)
@
\subsection{Write the new table}
<<>>=
write.table(tab, "covid_comp_complete_old.txt", row.names=FALSE, quote=FALSE, sep="\t")
@
\section{Second Table}
Table containing the DGINN results for both Primates and bats. Conserve all genes.
\subsection{Primates}
<<>>=
dginnT<-read.delim(paste0(workdir,
"data/DGINN_202005281649summary_cleaned.csv"),
fill=T, h=T, sep=",")
dim(dginnT)
names(dginnT)
# Rename the columns to include primate
names(dginnT)<-c("File", "Name", "Gene.name", "GeneSize",
"dginn-primate_NbSpecies", "dginn-primate_omegaM0Bpp",
"dginn-primate_omegaM0codeml", "dginn-primate_BUSTED",
"dginn-primate_BUSTED.p.value", "dginn-primate_MEME.NbSites",
"dginn-primate_MEME.PSS", "dginn-primate_BppM1M2",
"dginn-primate_BppM1M2.p.value", "dginn-primate_BppM1M2.NbSites",
"dginn-primate_BppM1M2.PSS", "dginn-primate_BppM7M8",
"dginn-primate_BppM7M8.p.value", "dginn-primate_BppM7M8.NbSites",
"dginn-primate_BppM7M8.PSS", "dginn-primate_codemlM1M2",
"dginn-primate_codemlM1M2.p.value", "dginn-primate_codemlM1M2.NbSites",
"dginn-primate_codemlM1M2.PSS", "dginn-primate_codemlM7M8",
"dginn-primate_codemlM7M8.p.value", "dginn-primate_codemlM7M8.NbSites",
"dginn-primate_codemlM7M8.PSS")
@
\subsection{Bats}
<<>>=
# original table
dginnbats<-read.delim(paste0(workdir,
"data/DGINN_202005281339summary_cleaned-LE201108.txt"),
fill=T, h=T)
# rerun on corrected alignment
dginnbatsnew<-read.delim(paste0(workdir,
"data/DGINN_202011262248_hyphybpp-202012192053_codeml-summary.txt"),
fill=T, h=T)
@
<<>>=
# Add both columns
dginnbatsnew$Lucie.s.comments<-""
dginnbatsnew$Action.taken<-""
# Homogenize column names
dginnbats$BUSTED_p.value<-dginnbats$BUSTED.p.value
dginnbats$MEME_NbSites<-dginnbats$MEME.NbSites
dginnbats$MEME_PSS<-dginnbats$MEME.PSS
dginnbats$BppM1M2_p.value<-dginnbats$BppM1M2.p.value
dginnbats$BppM1M2_NbSites<-dginnbats$BppM1M2.NbSites
dginnbats$BppM1M2_PSS<-dginnbats$BppM1M2.PSS
dginnbats$BppM7M8_p.value<-dginnbats$BppM7M8.p.value
dginnbats$BppM7M8_NbSites<-dginnbats$BppM7M8.NbSites
dginnbats$BppM7M8_PSS<-dginnbats$BppM7M8.PSS
dginnbats$codemlM1M2_p.value<-dginnbats$codemlM1M2.p.value
dginnbats$codemlM1M2_NbSites<-dginnbats$codemlM1M2.NbSites
dginnbats$codemlM1M2_PSS<-dginnbats$codemlM1M2.PSS
dginnbats$codemlM7M8_p.value<-dginnbats$codemlM7M8.p.value
dginnbats$codemlM7M8_NbSites<-dginnbats$codemlM7M8.NbSites
dginnbats$codemlM7M8_PSS<-dginnbats$codemlM7M8.PSS
@
<<>>=
# Order columns in the same order in both tables
dginnbats<-dginnbats[,names(dginnbatsnew)]
names(dginnbatsnew) %in% names(dginnbats)
names(dginnbats)==names(dginnbatsnew)
# Put RIPK aside
ripk1<-dginnbatsnew[dginnbatsnew$Gene=="RIPK1",1:27]
# Add it to primate table
names(ripk1)<-names(dginnT)
ripk1$`dginn-primate_omegaM0Bpp`<-as.factor(ripk1$`dginn-primate_omegaM0Bpp`)
ripk1$`dginn-primate_BUSTED.p.value`<-as.factor(ripk1$`dginn-primate_BUSTED.p.value`)
ripk1$`dginn-primate_BppM1M2.p.value`<-as.factor(ripk1$`dginn-primate_BppM1M2.p.value`)
ripk1$`dginn-primate_BppM7M8.p.value`<-as.factor(ripk1$`dginn-primate_BppM7M8.p.value`)
dginnT<-rbind(dginnT, ripk1)
## Remove it Ripk1 from bats
dginnbatsnew<-dginnbatsnew[dginnbatsnew$Gene!="RIPK1",]
## suppress redundant lines
dginnbats<-dginnbats[(dginnbats$Gene %in% dginnbatsnew$Gene)==FALSE,]
names(dginnbatsnew)<-names(dginnbats)
## replace by new data
dginnbatsnew$omegaM0Bpp<-as.factor(dginnbatsnew$omegaM0Bpp)
dginnbatsnew$BppM1M2_p.value<-as.factor(dginnbatsnew$BppM1M2_p.value)
dginnbatsnew$BppM7M8_p.value<-as.factor(dginnbatsnew$BppM7M8_p.value)
dginnbats<-rbind(dginnbats, dginnbatsnew)
names(dginnbats)<-c("bats_File", "bats_Name", "Gene.name", paste0("bats_",
names(dginnbats)[-(1:3)]))
names(dginnbats)
@
\subsection{Merged table}
<<setup, include=FALSE, cache=FALSE, tidy=TRUE>>=
options(tidy=TRUE, width=70)
@
<<>>=
#tidy.opts = list(width.cutoff = 60)
dim(dginnT)
dginnT$Gene.name
dim(dginnbats)
dginnbats$Gene.name
@
Manual corrections:
TMPRSS2 in bats
<<>>=
dginnbats[dginnbats$Gene.name=="TMPRSS2",]
# keeping the uncut one
# renaming the other one TMPRSS2_cut
dginnbats$Gene.name<-as.character(dginnbats$Gene.name)
dginnbats[dginnbats$bats_File=="TMPRSS2_bat_select_cut_mafft_prank","Gene.name"]<-"TMPRSS2_cut"
@
RIPK1: ANcestral version kept, suppress it "RIPK1\_sequences\_filtered\_longestORFs\_mafft\_mincov\_prank"
<<>>=
dginnT<-dginnT[dginnT$File!="RIPK1_sequences_filtered_longestORFs_mafft_mincov_prank",]
@
REEP6 eA et B
<<>>=
dginnbats$Gene.name<-as.character(dginnbats$Gene.name)
dginnbats[dginnbats$bats_File=="REEP6_sequences_filtered_longestORFs_D210gp1_prank", "Gene.name"]<-"REEP6_old"
dginnbats[dginnbats$bats_File=="REEP6_LA_bat_select_mafft_prank", "Gene.name"]<-"REEP6"
dginnbats[dginnbats$bats_File=="REEP6_LB_bat_select_mafft_prank", "Gene.name"]<-"REEP6_like"
@
GNG5
<<>>=
dginnT$Gene.name<-as.character(dginnT$Gene.name)
dginnT[dginnT$File=="GNG5_sequences_filtered_longestORFs_D189gp2_prank", "Gene.name"]<-"GNG5_like"
@
<<>>=
dim(dginnbats)
dim(dginnT)
# genes in common
common<-dginnT$Gene.name[dginnT$Gene.name %in% dginnbats$Gene.name]
common
length(dginnT$Gene.name[dginnT$Gene.name %in% dginnbats$Gene.name])
# genes only in primates
onlyprimates<-dginnT$Gene.name[(dginnT$Gene.name %in% dginnbats$Gene.name)==FALSE]
onlyprimates
length(dginnT$Gene.name[(dginnT$Gene.name %in% dginnbats$Gene.name)==FALSE])
# genes only in bats
onlybats<-dginnbats$Gene.name[(dginnbats$Gene.name %in% dginnT$Gene.name)==FALSE]
onlybats
length(dginnbats$Gene.name[(dginnbats$Gene.name %in% dginnT$Gene.name)==FALSE])
@
<<>>=
tab<-merge(dginnT, dginnbats, by="Gene.name", all.x=T, all.y=T)
dim(tab)
# add column "shared"/"only bats"/"only primates"
tab$status<-""
tab$status[tab$Gene.name %in% common]<-"shared"
tab$status[tab$Gene.name %in% onlyprimates]<-"onlyprimates"
tab$status[tab$Gene.name %in% onlybats]<-"onlybats"
table(tab$status)
write.table(tab, "covid_comp_alldginn.txt", sep="\t")
@
\section{Complete data}
Merge the previous tab with J Young's original table. \textbf{Will replace the 1st part of this script}
<<>>=
young<-read.delim(paste0(workdir,
"data/COVID_PAMLresults_332hits_plusBatScreens_2020_Apr14.csv"),
fill=T, h=T, dec=",")
dim(young)
young$PreyGene<-as.character(young$PreyGene)
young$PreyGene[young$PreyGene=="MTARC1"]<-"MARC1"
@
How many genes in the Young table are not in the DGINN table. And who are they?
<<>>=
table(young$PreyGene %in% tab$Gene.name)
young[(young$PreyGene %in% tab$Gene.name)==FALSE, "PreyGene"]
tab[(tab$Gene.name %in% young$PreyGene)==FALSE, "Gene.name"]
@
Merge them and keep only the krogan genes
<<>>=
tablo<-merge(young, tab, by="Gene.name", all.x=TRUE)
write.table(tablo, "covid_comp_complete.txt", row.names=FALSE, quote=TRUE, sep="\t")
@
\end{document}