The qsip_sample_data
object holds validated sample metadata.
Usage
qsip_sample_data(
data,
sample_id = "sample_id",
source_mat_id = "source_mat_id",
gradient_position = "gradient_position",
gradient_pos_density = "gradient_pos_density",
gradient_pos_amt = "gradient_pos_amt",
gradient_pos_rel_amt = "",
overwrite = FALSE
)
Arguments
- data
(dataframe) Metadata for samples/fractions
- sample_id
(string) The unique sample ID
- source_mat_id
(string) The unique ID for the biological subject or replicate
- gradient_position
(string) Column name with the fraction position
- gradient_pos_density
(string) Column name with the gradient density
- gradient_pos_amt
(string) Column name with a total amount per fraction, either qPCR copies or DNA
- gradient_pos_rel_amt
(string) Column name with the relative fraction abundance compared to the total
Details
qsip_sample_data()
is not a typical function, but rather a class constructor that
instantiates a new qsip_sample_data
object. The constructor takes a data.frame
as
input and returns a validated qsip_sample_data
object.
In qSIP and MISIP, a "sample" is the post-fractionated material with metadata pertaining to the fractionation process. Sample metadata contains information about the sample and fractionation, such as the sample ID, the source material ID, the gradient position, the density, the amount recovered (e.g. DNA concentration or 16S copies), and the relative abundance of the fraction compared to the total.
Ideally, gradient_pos_amt
should be reported as a mass value of DNA rather than
a concentration. However, if the concentration is reported, the fraction_volume
argument can be used to convert the gradient_pos_amt
concentration to a mass value.
For example, if the gradient_pos_amt
is reported as ng/ul, and the fraction_volume
is reported as 100 ul, then the gradient_pos_amt
will be converted to ng.
Internally, qsip_sample_data
renames the metadata columns to be standardized
to MISIP terminology. A data.frame
with the standardized names can be extracted
back out of the object using the get_dataframe()
method, and the optional original_headers
argument can be set to TRUE
to return the original column names.
There are several validation checks done on the data.frame
:
The
data
argument must contain adata.frame
, including a tibbleThe
sample_id
column must contain unique values per rowThe
gradient_position
must container positive integers, or-1
is allowed to designate the sample as "bulk" or unfractionated
See also
Other "qSIP Objects":
qsip_data()
,
qsip_feature_data()
,
qsip_source_data()