get_conc_bca | R Documentation |
Get protein's concentration from a dilution series measured with the
bicinchoninic acid (BCA) assay. Takes two input data sets, the BCA assay data
and the A562 baseline data. The A562 baseline data is necessary for proteins
that might naturally absorb in this range. Script normalises BCA assay data
for A562 baseline, then to blank values of BCA. Data from the bovine serum
albumin (BSA) standards (identified by protein column containing the word
"BSA"), are used to construct a standard curve of concentration in ng/ul vs
normalised A562 values, which is used to predict FP concentrations at each
dilution. The FP's concentration vs dilution values are then used to predict
the FP concentration at each dilution in one of two ways. Where option is set
to fit
, a linear model is fitted between FP concentration and dilution, and
the fitted values are exported. Where option is set to highest
, FP
concentrations are taken only from the highest concentration/dilution
specified and exported.
get_conc_bca(
microbca_data_csv,
a562_baseline_csv = NULL,
calibr,
buffer,
protein_seq,
option = "highest",
outfolder = "."
)
microbca_data_csv |
path of the CSV file of your BCA data. |
a562_baseline_csv |
path of the CSV file of your A562 baseline data. Optional. If data is missing, use NULL. If NULL is specified, the value of 0 is assigned as baseline for all wells. Default is NULL. |
calibr |
string specifying the value of the 'calibrant' column to assess
with this function. Function subsets the data by the value specified here.
This works by taking all the rows with specified string in the calibrant
column and discarding all other rows (which means that the blanks relevant
to the specified calibrant need to be specified as calibrant = |
buffer |
string specifying the value of the 'media' column to assess with this function. Function subsets the data by the value specified here. |
protein_seq |
character string of protein sequence using 1-letter code. Required for MW calculation. |
option |
string specifying how to choose the predicted concentration to
use. Default is "highest", in which the mean predicted concentration of the
highest dilution (i.e. neat) is used, and is multiplied by the dilution to
determine the concentration of the other dilutions. The alternative, "fit",
fits a |
outfolder |
path to the folder where output files should be saved. Defaults to the current working directory. |
## Not run:
bca_concs <- get_conc_bca(
microbca_data_csv = "bca_data_parsed.csv", a562_baseline_csv = "a562_data_parsed.csv",
calibr = "mCherry", buffer = "T5N15_pi", protein_seq = protein_seq, option = "highest",
outfolder = "protquant_microbca/mCherry_T5N15pi"
)
## End(Not run)
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