normalize() can now normalize by each well (norm_column = "well") as an
alternative to the existing normalization by experimental group (norm_column = "exp_group")
normalize() has two normalization methods.
norm_method = "self": based on the corresponding well or experimental
group row of the measure column in the input normalization CSV.
|exp_group | measure| |:---------|-------:| |Group_1 | 30000| |Group_2 | 30000| |Group_3 | 5000| |Group_4 | 5000|
Given the input normalization data above, normalizing by experimental group
will divide each of those experimental group rows of the seahorse table by the
corresponding measure value of the experimental group in the input CSV.
Similarly, if normalizing by well, each set of well rows is normalized by
the corresponding measure value of the well - the input normalization CSV
must have a column for well instead of exp_group for every well in the
Seahorse data.
based on the minimum of the measure column of the input normalization data
(norm_method = "minimum") (same as before). A normalization
constant is calculated dividing each well or experimental group measure by
the minimum measure.
|exp_group | measure| norm_const| |:---------|-------:|----------:| |Group_1 | 30000| 6 | |Group_2 | 30000| 6 | |Group_3 | 5000| 1 | |Group_4 | 5000| 1 |
If normalizing by experimental group, each row of the seahorse table is divide by the group's normalization constant. Similarly, if normalizing by well, each well row is divided by the well's normalization constant.
Note: the current default is to normalize by experimental group and using
the minimum (norm_column = "exp_group", norm_method = "minimum") to maintain
backwards compatibility, but future releases will normalize by well and using
each corresponding row (norm_column = "well", norm_method = "self").
read_data() throws an error if the "Group" column of the input data is only
one word that cannot be separated with the delimiter provided by the user.get_energetics_summary(), get_rate_summary(), bioscope_plot(),
atp_plot(), and rate_plot().get_energetics() now warns about possible mismatches between the replicates
in the MITO and GLYCO groups instead of stopping as datasets with different
replicate counts can cause a mismatch that may not be erroneous.rate_plot() now has a linewidth parameter to set the width of its
geom_linesSeparating replicates is now supported for getting get_energetics_summary(),
bioscope_plot(), atp_plot() and rate_plot() with sep_reps = TRUE. This will
calculate summary statistics for each replicate within a group instead of
combining them. atp_plot() now uses a linerange plot instead of a crossbar
plot and color to distinguish between replicates instead of experimental
groups. There is no color if there are no replicates or if they are combined.
Note: the current default is to combine replicates (sep_reps = FALSE) to
maintain backwards compatibility, but future releases will separate them by
default. If sep_reps is not explicitly set to FALSE, the functions will
warn the user about this future change in defaults.
get_energetics()read_data() returns the replicate column as a factor instead of numericgeom_line's deprecated size option with linewidth in rate_plotAdd normalize(), a cell count/protein mass normalization function.
read_data now can take a csv file with cell counts or protein mass ($\mu$g)
for each of the experimental groups to normalize the data.
An example csv is provided below for a dataset with 4 experimental groups:
|exp_group | measure| |:---------|-------:| |Group_1 | 30000| |Group_2 | 30000| |Group_3 | 5000| |Group_4 | 5000|
read_data() to
support delimiters other than First release before initial submission for publication.