Generates a timeseries plot showing relative read abundances over time.
amp_timeseries(
data,
time_variable = NULL,
group_by = NULL,
tax_aggregate = "OTU",
tax_add = NULL,
tax_show = 5,
tax_class = NULL,
tax_empty = "best",
split = FALSE,
scales = "free_y",
normalise = TRUE,
plotly = FALSE,
...
)
amp_time_series(
data,
time_variable = NULL,
group_by = NULL,
tax_aggregate = "OTU",
tax_add = NULL,
tax_show = 5,
tax_class = NULL,
tax_empty = "best",
split = FALSE,
scales = "free_y",
normalise = TRUE,
plotly = FALSE,
...
)
(required) Data list as loaded with amp_load
.
(required) The name of the column in the metadata containing the time variables, e.g. "Date"
. Must be directly compatible with as_date
and preferably of the form "yyyy-mm-dd"
or "%Y-%m-%d"
.
Group the samples by a variable in the metadata.
The taxonomic level to aggregate the OTUs. (default: "OTU"
)
Additional taxonomic level(s) to display, e.g. "Phylum"
. (default: "none"
)
The number of taxa to show, or a vector of taxa names. (default: 6
)
Converts a specific phylum to class level instead, e.g. "p__Proteobacteria"
.
How to show OTUs without taxonomic information. One of the following:
"remove"
: Remove OTUs without taxonomic information.
"best"
: (default) Use the best classification possible.
"OTU"
: Display the OTU name.
Split the plot into subplots of each taxa. (default: FALSE
)
If split = TRUE
, should the axis scales of each subplot be fixed (fixed
), free ("free"
), or free in one dimension ("free_x"
or "free_y"
)? (default: "fixed"
)
(logical) Transform the OTU read counts to be in percent per sample. (default: TRUE
)
(logical) Returns an interactive plot instead. (default: FALSE
)
Additional arguments passed to as_date
to make the time_variable compatible with the timeseries plot, fx the format
or tz
arguments, see ?as_date
.
A ggplot2 object.
See ?amp_filter_samples
or the ampvis2 FAQ.
# Load example data
data("AalborgWWTPs")
# Timeseries of the 5 most abundant OTUs based on the "Date" column
amp_timeseries(AalborgWWTPs,
time_variable = "Date",
tax_aggregate = "OTU"
)
#>
#> Attaching package: ‘lubridate’
#> The following objects are masked from ‘package:base’:
#>
#> date, intersect, setdiff, union
#> Warning: Duplicate dates in column Date, displaying the average for each date.
#> Consider grouping dates using the group_by argument or subset the data using amp_filter_samples.
# As the above warning suggests, there are more than one sample per date in the data,
# in this case one from Aalborg East and one from Aalborg West. The average of the
# two samples is then shown per date. In such case it is then recommended to either
# subset the data, or group the samples by setting group_by = "" and split by tax_aggregate
# by setting split = TRUE:
amp_timeseries(AalborgWWTPs,
time_variable = "Date",
group_by = "Plant",
split = TRUE,
scales = "free_y",
tax_show = 9,
tax_aggregate = "Genus",
tax_add = "Phylum"
)