Commit be723e90 authored by Etienne Rifa's avatar Etienne Rifa
Browse files

Merge branch 'master' into bars_update

parents 68f24906 af195182
...@@ -46,9 +46,9 @@ aggregate_fun <- function(data = data, metacoder = NULL, deseq = NULL, mgseq = N ...@@ -46,9 +46,9 @@ aggregate_fun <- function(data = data, metacoder = NULL, deseq = NULL, mgseq = N
if(!dir.exists(output)){ if(!dir.exists(output)){
dir.create(output,recursive=T ) dir.create(output,recursive=T )
} }
flog.info('Done.')
# data.glom <- tax_glom(data, taxrank=rank, h=TRUE) flog.info('Glom Tax.')
data.glom <- tax_glom(data, taxrank=rank)
if(comp == ''){ if(comp == ''){
fun <- paste('combinaisons <- combn(na.omit(unique(sample_data(data)$',column1,')),2)',sep='') fun <- paste('combinaisons <- combn(na.omit(unique(sample_data(data)$',column1,')),2)',sep='')
...@@ -176,7 +176,7 @@ aggregate_fun <- function(data = data, metacoder = NULL, deseq = NULL, mgseq = N ...@@ -176,7 +176,7 @@ aggregate_fun <- function(data = data, metacoder = NULL, deseq = NULL, mgseq = N
names(TABf)[ncol(TABf)] = names(TF)[j] names(TABf)[ncol(TABf)] = names(TF)[j]
} }
TABfbak <- TABf TABfbak0 <- TABf
# add new columns, sumMethods, DeseqLFC, Mean Relative Abundance (TSS) condition 1 & 2 # add new columns, sumMethods, DeseqLFC, Mean Relative Abundance (TSS) condition 1 & 2
row.names(deseqT) = deseqT[,1] row.names(deseqT) = deseqT[,1]
...@@ -192,7 +192,7 @@ aggregate_fun <- function(data = data, metacoder = NULL, deseq = NULL, mgseq = N ...@@ -192,7 +192,7 @@ aggregate_fun <- function(data = data, metacoder = NULL, deseq = NULL, mgseq = N
# clr = function(x){log(x+1) - rowMeans(log(x+1))} # clr = function(x){log(x+1) - rowMeans(log(x+1))}
# otableNORM <- clr(otable) # otableNORM <- clr(otable)
normf = function(x){ x/sum(x) } normf = function(x){ x/sum(x) }
data.norm <- transform_sample_counts(data, normf) data.norm <- transform_sample_counts(data.glom, normf)
otableNORM <- otu_table(data.norm) otableNORM <- otu_table(data.norm)
Gtab <- cbind(as.data.frame(ssample), t(otableNORM)) Gtab <- cbind(as.data.frame(ssample), t(otableNORM))
......
...@@ -11,6 +11,7 @@ ...@@ -11,6 +11,7 @@
#' @param output The output file directory. #' @param output The output file directory.
#' @param tests Whether to compute tests or not (TRUE/FALSE) #' @param tests Whether to compute tests or not (TRUE/FALSE)
#' @param axes Axes to plot (c(1,2)) #' @param axes Axes to plot (c(1,2))
#' @param ellipse Plot ellipse (TRUE)
#' @param verbose Verbose level. (1: quiet, 2: print infos, 3: print infos + debug) #' @param verbose Verbose level. (1: quiet, 2: print infos, 3: print infos + debug)
#' #'
#' @return Return specific plots and tests in list and output them in the output directory. #' @return Return specific plots and tests in list and output them in the output directory.
...@@ -26,7 +27,7 @@ ...@@ -26,7 +27,7 @@
# Decontam Function # Decontam Function
diversity_beta_light <- function(psobj, rank = "ASV", col = NULL, cov = NULL, dist0 = "bray", ord0 = "MDS", output="./plot_div_beta/", axes = c(1,2), tests = TRUE, verbose = 2) { diversity_beta_light <- function(psobj, rank = "ASV", col = NULL, cov = NULL, dist0 = "bray", ord0 = "MDS", output="./plot_div_beta/", axes = c(1,2), tests = TRUE, verbose = 2, ellipse = TRUE) {
if(verbose == 3){ if(verbose == 3){
invisible(flog.threshold(DEBUG)) invisible(flog.threshold(DEBUG))
...@@ -70,11 +71,32 @@ diversity_beta_light <- function(psobj, rank = "ASV", col = NULL, cov = NULL, di ...@@ -70,11 +71,32 @@ diversity_beta_light <- function(psobj, rank = "ASV", col = NULL, cov = NULL, di
flog.info('Plot ...') flog.info('Plot ...')
resBeta <- list() resBeta <- list()
if(!is.null(cov)){ if(!is.null(cov)){
sdata = sample_data(data_rank)
fun = glue::glue("sdata${cov1[length(cov1)]}_{col} = factor(paste(sdata${cov1[length(cov1)]}, sdata${col}, sep='_'))")
eval(parse(text=fun))
sample_data(data_rank) = sdata
p1 <- plot_samples(data_rank, ordinate(data_rank, ord0, dist0), color = col, shape = cov1[length(cov1)], axes = axes ) + p1 <- plot_samples(data_rank, ordinate(data_rank, ord0, dist0), color = col, shape = cov1[length(cov1)], axes = axes ) +
theme_bw() + ggtitle(glue::glue("{ord0} + {dist0}")) + stat_ellipse() + scale_shape_manual(values = 0:10) theme_bw() + ggtitle(glue::glue("{ord0} + {dist0}")) + scale_shape_manual(values = 0:10)
if(ellipse){p1 <- p1 + stat_ellipse()}
p2 <- plot_samples(data_rank, ordinate(data_rank, ord0, dist0), color = glue::glue("{cov1[length(cov1)]}_{col}"), shape = NULL, axes = axes ) +
theme_bw() + ggtitle(glue::glue("{ord0} + {dist0}")) + scale_shape_manual(values = 0:10)
if(ellipse){p2 <- p2 + stat_ellipse()}
resBeta$plot2 <- p2 + theme(axis.text.x = element_text(angle = 45, hjust=1),
,axis.text=element_text(size=18),
axis.title=element_text(size=16,face="bold"),
strip.text.x = element_text(size = 18,face="bold"),
title=element_text(size=16,face="bold"))
ggsave(glue::glue("{output}/beta_diversity2.eps"), plot=resBeta$plot2, height = 20, width = 30, units="cm", dpi = 500, device="eps")
}else{ }else{
p1 <- plot_samples(data_rank, ordinate(data_rank, ord0, dist0), color = col, axes = axes ) + p1 <- plot_samples(data_rank, ordinate(data_rank, ord0, dist0), color = col, axes = axes ) +
theme_bw() + ggtitle(glue::glue("{ord0} + {dist0}")) + stat_ellipse() theme_bw() + ggtitle(glue::glue("{ord0} + {dist0}"))
if(ellipse){p1 <- p1 + stat_ellipse()}
} }
# plot(p1) # plot(p1)
flog.info('Plot ok...') flog.info('Plot ok...')
...@@ -105,10 +127,9 @@ diversity_beta_light <- function(psobj, rank = "ASV", col = NULL, cov = NULL, di ...@@ -105,10 +127,9 @@ diversity_beta_light <- function(psobj, rank = "ASV", col = NULL, cov = NULL, di
} }
#PairwiseAdonis #PairwiseAdonis
# resBC2 = pairwise.adonis2(as.formula( paste('BC.dist ~ ', col,sep="") ), data = mdata) if(!is.null(cov)){
if(length(col1)>1){ fun = glue::glue("resBC2 <- pairwise.adonis(dist1, mdata${cov1[length(cov1)]}_{col}, p.adjust.m='fdr')" )
fact1 <- apply( mdata[,c(col1)] , 1 , paste , collapse = "-" ) eval(parse(text = fun))
resBC2 <- pairwise.adonis(dist1, fact1, p.adjust.m='fdr')
} else { } else {
resBC2 <- pairwise.adonis(dist1, mdata[,c(col1)], p.adjust.m='fdr') resBC2 <- pairwise.adonis(dist1, mdata[,c(col1)], p.adjust.m='fdr')
} }
......
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