In philippmuench/PMtools: Miscellaneous helper functions
compare two humann tables
a <- as.data.frame(read.table("tmp/unrief90_aws_cas_joined_cpm_edited.tsv", header = T, sep = '\t', stringsAsFactors = F))
dim(a)
a_1 <- a[which(a$SRS == "Cas1"),]
a_1_i <- a_1[which(a_1$taxa == "g__Lactobacillus.s__Lactobacillus_iners"),]
a_1_i$SRS <- NULL
a_1_i$taxa <- NULL
e <- as.data.frame(t(a_1_i))
b <- as.data.frame(read.table("data-raw/humann2_table.tsv", header = T, sep = '\t', stringsAsFactors = F))
dim(b)
b_1 <- b[which(b$SRS == "Cas1"),]
b_1_i <- b_1[which(b_1$taxa == "g__Lactobacillus|s__Lactobacillus_iners"),]
b_1_i$SRS <- NULL
b_1_i$taxa <- NULL
d <- as.data.frame(t(b_1_i))
overview of scaling functions
load data and generate ordering
library(PMtools)
# load example datasets
data(humann2_table)
data(hmp1_2_metadata)
data(hmp1_2_metaphlan)
# generate the sample order
custom.order <-
orderHumannBySimilarity(hmp1_2_metaphlan, distance.method = "bray")
# generate the data used for plotting
dat <-
humann2Barplot(
humann2_table,
metadata = hmp1_2_metadata,
feature = "Cas1",
num.bugs = "auto",
order.by = "custom",
custom.order = custom.order
)
linear scaled
humann2_barplot
```{bash, eval=F}
humann2_barplot --input /Users/pmuench/Library/Mobile\ Documents/com\~apple\~CloudDocs/Projekte/HMP_CRISPR/figure5_cas/unrief90_aws_cas_joined_cpm.tsv -f "Cas1" -s similarity metadata -m STArea -e 0.8 -t 10 --scaling none --colormap Spectral --output cas1_no_sclae.png
## PMtools
```r
p1 <-
makeHumann2Barplot(
dat,
NULL,
hide.legend = F,
scale = "none",
space = "fixed"
)
print(p1)
log10 scaled
humann2_barplot
```{bash, eval=F}
humann2_barplot --input /Users/pmuench/Library/Mobile\ Documents/com\~apple\~CloudDocs/Projekte/HMP_CRISPR/figure5_cas/unrief90_aws_cas_joined_cpm.tsv -f "Cas1" -s similarity metadata -m STArea -e 0.8 -t 10 --scaling pseudolog --colormap Spectral --output cas1_pseudolog.png
## PMtools new
based on log10 scaling of aggregated strata and proportional coloring
```r
p <-
makeHumann2Barplot(
dat,
p1$colors,
hide.legend = F,
scale = "proportional-log",
space = "fixed"
)
print(p)
PMtools old
based on asinh(x/2)/log(10)
p <-
makeHumann2Barplot(
dat,
p1$colors,
hide.legend = F,
scale = "pseudolog",
space = "fixed"
)
print(p)
ggplot2 insternal log10 scaling
based onggplot2::scale_y_log10()
p <-
makeHumann2Barplot(
dat,
p1$colors,
hide.legend = F,
scale = "ggplot2-log10",
space = "fixed"
)
print(p)
all Cas genes
cas_plots <- vector('list', 10)
plot.colors <- NULL
for (cas in paste0("Cas", 1:10)) {
cas_plots[[cas]] <- local({
dat <-
humann2Barplot(
humann2_table,
metadata = hmp1_2_metadata,
feature = cas,
num.bugs = "auto",
num.bugs.explained.fraction = 0.35,
order.by = "custom",
custom.order = custom.order
)
p <-
makeHumann2Barplot(
dat,
plot.colors,
hide.legend = F,
scale = "proportional-log",
space = "fixed"
)
plot.colors <<- rbind(plot.colors, p$colors)
write.table(p$colors, file = "log.txt", append = T, sep = "\t", row.names = F,
col.names = F, quote = F)
print(p$gplot)
})
}
png("all_cas_floor.png", width = 600, height = 900)
print(multiplot(plotlist = cas_plots, cols = 2))
dev.off()
pdf("all_cas_floor.pdf", height = 5, width = 7)
print(multiplot(plotlist = cas_plots, cols = 2))
dev.off()
test color fuctionality
#Library(PMtools)
# load example datasets
data(humann2_table)
data(hmp1_2_metadata)
data(hmp1_2_metaphlan)
# generate the sample order
custom.order <-
orderHumannBySimilarity(hmp1_2_metaphlan, distance.method = "bray")
plot.colors <- NULL
# generate the data used for plotting
dat1 <-
humann2Barplot(
humann2_table,
metadata = hmp1_2_metadata,
num.bugs.explained.fraction = 0.35,
feature = "Cas1",
num.bugs = "auto",
order.by = "custom",
custom.order = custom.order,
last.plot.colors = plot.colors
)
p1 <-
makeHumann2Barplot(
dat1,
last.plot.colors = plot.colors,
hide.legend = F,
scale = "proportional-log",
space = "fixed"
)
plot.colors <- p1$colors
dat2 <-
humann2Barplot(
humann2_table,
metadata = hmp1_2_metadata,
num.bugs.explained.fraction = 0.35,
feature = "Cas2",
num.bugs = "auto",
order.by = "custom",
custom.order = custom.order,
last.plot.colors = plot.colors
)
p2 <-
makeHumann2Barplot(
dat2,
plot.colors,
hide.legend = F,
scale = "proportional-log",
space = "fixed"
)
dat3 <-
humann2Barplot(
humann2_table,
metadata = hmp1_2_metadata,
feature = "Cas3",
num.bugs = "auto",
order.by = "custom",
custom.order = custom.order,
last.plot.colors = p2$colors
)
p3 <-
makeHumann2Barplot(
dat2,
p1$colors,
hide.legend = F,
scale = "proportional-log",
space = "fixed"
)
all Cas genes
p <- NULL
cas_plots <- vector('list', 10)
#plot.colors <- NULL
for (cas in paste0("Cas", 1:10)) {
cas_plots[[cas]] <- local({
dat <-
humann2Barplot(
humann2_table,
metadata = hmp1_2_metadata,
feature = cas,
num.bugs = "auto",
num.bugs.explained.fraction = 0.35,
order.by = "custom",
custom.order = custom.order,
last.plot.colors = plot.colors
)
p <-
makeHumann2Barplot(
dat,
plot.colors,
hide.legend = F,
scale = "proportional-log",
space = "fixed"
)
plot.colors <<- rbind(plot.colors, p$colors)
write.table(p$colors, file = "log.txt", append = T, sep = "\t", row.names = F,
col.names = F, quote = F)
print(p$gplot)
})
}
png("all_cas_floor_col.png", width = 600, height = 900)
print(multiplot(plotlist = cas_plots, cols = 2))
dev.off()
pdf("all_cas_floor_col4.pdf", height = 6, width = 30)
print(multiplot(plotlist = cas_plots, cols = 2))
dev.off()
set floor fixed to -1
# generate the data used for plotting using STSite
dat <-
humann2Barplot(
humann2_table,
metadata = hmp1_2_metadata,
feature = "Cas4",
num.bugs = "auto",
metadata.factor = 5,
order.by = "custom",
column.stratification.order = c("Subgingival_plaque","Supragingival_plaque","Buccal_mucosa","Saliva","Tongue_dorsum","Throat","Hard_palate","Keratinized_gingiva","Palatine_Tonsils","Stool","Anterior_nares","L_Retroauricular_crease","R_Retroauricular_crease","R_Antecubital_fossa","Mid_vagina","Posterior_fornix","Vaginal_introitus"),
custom.order = custom.order)
p <-
makeHumann2Barplot(
dat,
NULL,
fixed.floor = -1,
fixed.ymax = 4,
hide.legend = F,
scale = "proportional-log",
space = "fixed")
plot(p$gplot)
plot all Cas genes with fixed floor
all Cas genes
p <- NULL
cas_plots <- vector('list', 10)
plot.colors <- NULL
for (cas in paste0("Cas", 1:10)) {
cas_plots[[cas]] <- local({
dat <-
humann2Barplot(
humann2_table,
metadata = hmp1_2_metadata,
feature = cas,
num.bugs = "auto",
metadata.factor = 5,
column.stratification.order = c("Subgingival_plaque","Supragingival_plaque","Buccal_mucosa","Saliva","Tongue_dorsum","Throat","Hard_palate","Keratinized_gingiva","Palatine_Tonsils","Stool","Anterior_nares","L_Retroauricular_crease","R_Retroauricular_crease","R_Antecubital_fossa","Mid_vagina","Posterior_fornix","Vaginal_introitus"),
num.bugs.explained.fraction = 0.35,
order.by = "custom",
custom.order = custom.order,
last.plot.colors = plot.colors
)
p <-
makeHumann2Barplot(
dat,
plot.colors,
hide.legend = F,
fixed.floor = -1,
fixed.ymax = 4,
scale = "proportional-log",
space = "fixed"
)
plot.colors <<- rbind(plot.colors, p$colors)
write.table(p$colors, file = "log.txt", append = T, sep = "\t", row.names = F,
col.names = F, quote = F)
print(p$gplot)
})
}
pdf("all_cas_fixed_floor_fixed_ymax_site2.pdf", height = 6, width = 30)
print(multiplot(plotlist = cas_plots, cols = 2))
dev.off()
philippmuench/PMtools documentation built on Dec. 27, 2019, 8:08 a.m.
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compare two humann tables
a <- as.data.frame(read.table("tmp/unrief90_aws_cas_joined_cpm_edited.tsv", header = T, sep = '\t', stringsAsFactors = F)) dim(a) a_1 <- a[which(a$SRS == "Cas1"),] a_1_i <- a_1[which(a_1$taxa == "g__Lactobacillus.s__Lactobacillus_iners"),] a_1_i$SRS <- NULL a_1_i$taxa <- NULL e <- as.data.frame(t(a_1_i)) b <- as.data.frame(read.table("data-raw/humann2_table.tsv", header = T, sep = '\t', stringsAsFactors = F)) dim(b) b_1 <- b[which(b$SRS == "Cas1"),] b_1_i <- b_1[which(b_1$taxa == "g__Lactobacillus|s__Lactobacillus_iners"),] b_1_i$SRS <- NULL b_1_i$taxa <- NULL d <- as.data.frame(t(b_1_i))
overview of scaling functions
load data and generate ordering
library(PMtools) # load example datasets data(humann2_table) data(hmp1_2_metadata) data(hmp1_2_metaphlan) # generate the sample order custom.order <- orderHumannBySimilarity(hmp1_2_metaphlan, distance.method = "bray") # generate the data used for plotting dat <- humann2Barplot( humann2_table, metadata = hmp1_2_metadata, feature = "Cas1", num.bugs = "auto", order.by = "custom", custom.order = custom.order )
linear scaled
humann2_barplot
```{bash, eval=F} humann2_barplot --input /Users/pmuench/Library/Mobile\ Documents/com\~apple\~CloudDocs/Projekte/HMP_CRISPR/figure5_cas/unrief90_aws_cas_joined_cpm.tsv -f "Cas1" -s similarity metadata -m STArea -e 0.8 -t 10 --scaling none --colormap Spectral --output cas1_no_sclae.png
 ## PMtools ```r p1 <- makeHumann2Barplot( dat, NULL, hide.legend = F, scale = "none", space = "fixed" ) print(p1)
log10 scaled
humann2_barplot
```{bash, eval=F} humann2_barplot --input /Users/pmuench/Library/Mobile\ Documents/com\~apple\~CloudDocs/Projekte/HMP_CRISPR/figure5_cas/unrief90_aws_cas_joined_cpm.tsv -f "Cas1" -s similarity metadata -m STArea -e 0.8 -t 10 --scaling pseudolog --colormap Spectral --output cas1_pseudolog.png
 ## PMtools new based on log10 scaling of aggregated strata and proportional coloring ```r p <- makeHumann2Barplot( dat, p1$colors, hide.legend = F, scale = "proportional-log", space = "fixed" ) print(p)
PMtools old
based on asinh(x/2)/log(10)
p <- makeHumann2Barplot( dat, p1$colors, hide.legend = F, scale = "pseudolog", space = "fixed" ) print(p)
ggplot2 insternal log10 scaling
based onggplot2::scale_y_log10()
p <- makeHumann2Barplot( dat, p1$colors, hide.legend = F, scale = "ggplot2-log10", space = "fixed" ) print(p)
all Cas genes
cas_plots <- vector('list', 10) plot.colors <- NULL for (cas in paste0("Cas", 1:10)) { cas_plots[[cas]] <- local({ dat <- humann2Barplot( humann2_table, metadata = hmp1_2_metadata, feature = cas, num.bugs = "auto", num.bugs.explained.fraction = 0.35, order.by = "custom", custom.order = custom.order ) p <- makeHumann2Barplot( dat, plot.colors, hide.legend = F, scale = "proportional-log", space = "fixed" ) plot.colors <<- rbind(plot.colors, p$colors) write.table(p$colors, file = "log.txt", append = T, sep = "\t", row.names = F, col.names = F, quote = F) print(p$gplot) }) } png("all_cas_floor.png", width = 600, height = 900) print(multiplot(plotlist = cas_plots, cols = 2)) dev.off() pdf("all_cas_floor.pdf", height = 5, width = 7) print(multiplot(plotlist = cas_plots, cols = 2)) dev.off()
test color fuctionality
#Library(PMtools) # load example datasets data(humann2_table) data(hmp1_2_metadata) data(hmp1_2_metaphlan) # generate the sample order custom.order <- orderHumannBySimilarity(hmp1_2_metaphlan, distance.method = "bray") plot.colors <- NULL # generate the data used for plotting dat1 <- humann2Barplot( humann2_table, metadata = hmp1_2_metadata, num.bugs.explained.fraction = 0.35, feature = "Cas1", num.bugs = "auto", order.by = "custom", custom.order = custom.order, last.plot.colors = plot.colors ) p1 <- makeHumann2Barplot( dat1, last.plot.colors = plot.colors, hide.legend = F, scale = "proportional-log", space = "fixed" ) plot.colors <- p1$colors dat2 <- humann2Barplot( humann2_table, metadata = hmp1_2_metadata, num.bugs.explained.fraction = 0.35, feature = "Cas2", num.bugs = "auto", order.by = "custom", custom.order = custom.order, last.plot.colors = plot.colors ) p2 <- makeHumann2Barplot( dat2, plot.colors, hide.legend = F, scale = "proportional-log", space = "fixed" ) dat3 <- humann2Barplot( humann2_table, metadata = hmp1_2_metadata, feature = "Cas3", num.bugs = "auto", order.by = "custom", custom.order = custom.order, last.plot.colors = p2$colors ) p3 <- makeHumann2Barplot( dat2, p1$colors, hide.legend = F, scale = "proportional-log", space = "fixed" )
all Cas genes
p <- NULL cas_plots <- vector('list', 10) #plot.colors <- NULL for (cas in paste0("Cas", 1:10)) { cas_plots[[cas]] <- local({ dat <- humann2Barplot( humann2_table, metadata = hmp1_2_metadata, feature = cas, num.bugs = "auto", num.bugs.explained.fraction = 0.35, order.by = "custom", custom.order = custom.order, last.plot.colors = plot.colors ) p <- makeHumann2Barplot( dat, plot.colors, hide.legend = F, scale = "proportional-log", space = "fixed" ) plot.colors <<- rbind(plot.colors, p$colors) write.table(p$colors, file = "log.txt", append = T, sep = "\t", row.names = F, col.names = F, quote = F) print(p$gplot) }) } png("all_cas_floor_col.png", width = 600, height = 900) print(multiplot(plotlist = cas_plots, cols = 2)) dev.off() pdf("all_cas_floor_col4.pdf", height = 6, width = 30) print(multiplot(plotlist = cas_plots, cols = 2)) dev.off()
set floor fixed to -1
# generate the data used for plotting using STSite dat <- humann2Barplot( humann2_table, metadata = hmp1_2_metadata, feature = "Cas4", num.bugs = "auto", metadata.factor = 5, order.by = "custom", column.stratification.order = c("Subgingival_plaque","Supragingival_plaque","Buccal_mucosa","Saliva","Tongue_dorsum","Throat","Hard_palate","Keratinized_gingiva","Palatine_Tonsils","Stool","Anterior_nares","L_Retroauricular_crease","R_Retroauricular_crease","R_Antecubital_fossa","Mid_vagina","Posterior_fornix","Vaginal_introitus"), custom.order = custom.order) p <- makeHumann2Barplot( dat, NULL, fixed.floor = -1, fixed.ymax = 4, hide.legend = F, scale = "proportional-log", space = "fixed") plot(p$gplot)
plot all Cas genes with fixed floor
all Cas genes
p <- NULL cas_plots <- vector('list', 10) plot.colors <- NULL for (cas in paste0("Cas", 1:10)) { cas_plots[[cas]] <- local({ dat <- humann2Barplot( humann2_table, metadata = hmp1_2_metadata, feature = cas, num.bugs = "auto", metadata.factor = 5, column.stratification.order = c("Subgingival_plaque","Supragingival_plaque","Buccal_mucosa","Saliva","Tongue_dorsum","Throat","Hard_palate","Keratinized_gingiva","Palatine_Tonsils","Stool","Anterior_nares","L_Retroauricular_crease","R_Retroauricular_crease","R_Antecubital_fossa","Mid_vagina","Posterior_fornix","Vaginal_introitus"), num.bugs.explained.fraction = 0.35, order.by = "custom", custom.order = custom.order, last.plot.colors = plot.colors ) p <- makeHumann2Barplot( dat, plot.colors, hide.legend = F, fixed.floor = -1, fixed.ymax = 4, scale = "proportional-log", space = "fixed" ) plot.colors <<- rbind(plot.colors, p$colors) write.table(p$colors, file = "log.txt", append = T, sep = "\t", row.names = F, col.names = F, quote = F) print(p$gplot) }) } pdf("all_cas_fixed_floor_fixed_ymax_site2.pdf", height = 6, width = 30) print(multiplot(plotlist = cas_plots, cols = 2)) dev.off()
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