A function to calculate the CV for the technical lab replicates. The default values are set as per the object names generated by machine
cv_estimation(
dataC,
lab_replicates,
sampleID_var = "sampleID",
antigen_var = "antigen",
replicate_var = "replicate",
mfi_var = "FMedianBG_correct",
cv_cut_off = 20
)A dataset a data frame with feature variables to be used
A numeric value indicating the number of lab replicates
A character string containing the name of the sample identifier variable. Default set to 'sampleID'
A character string containing the name of the features/protein variable. Default to 'antigen'
A character string containing the name of the replicate variable. Default to 'replicate'
A character string containing the name of the variable with MFI value.Assuming background correction is done already. Default to 'FMedianBG_correct'
Optional value indicating the cut off of flagging CV's. Default set at 20.
A data frame where CV's of the replicates have been calculated
Coefficient of Variation
dataC <- readr::read_csv(system.file("extdata",
"dataC.csv", package="protGear"))
#> Rows: 567 Columns: 11
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (3): sampleID, antigen, iden
#> dbl (8): sample_array_ID, FMedian, BGMedian, FMedianBG_correct, Block, Colum...
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## this file has 3 lab replicates and the default names
cv_estimation(dataC ,lab_replicates=3)
#> Warning: The replicates are as expected per sample per antigen
#> # A tibble: 126 × 21
#> # Groups: antigen [6]
#> antigen sampleID sampl…¹ meanX meanX…² meanX…³ meanX…⁴ sdX sdX2_X3 sdX1_X3
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 AMA1 0.0085 11 643. 594. 692 642. 98.5 70 69.3
#> 2 AMA1 0.0255 8 699 700. 672 724. 52.6 74.2 33.9
#> 3 AMA1 0.076 5 633. 588 668. 642. 81.3 35.4 77.1
#> 4 AMA1 0.23 2 1725. 1757 1720 1697 60.5 32.5 84.8
#> 5 AMA1 0.73 19 2504. 2494. 2568. 2450 119. 166. 61.5
#> 6 AMA1 177.78 4 58262 58208 58640. 57938. 709. 994. 383.
#> 7 AMA1 19.75 10 64143. 64204. 64280. 63944 353. 476. 367.
#> 8 AMA1 2.19 16 9243 9294 9031 9404 383. 528. 156.
#> 9 AMA1 533 1 53180. 52860. 53298 53380. 559. 117. 735.
#> 10 AMA1 59.26 7 61601 61870. 61848. 61085 894. 1078. 1111.
#> # … with 116 more rows, 11 more variables: sdX1_X2 <dbl>, CVX <dbl>,
#> # CVX2_X3 <dbl>, CVX1_X3 <dbl>, CVX1_X2 <dbl>, cvCat_all <chr>,
#> # cvSelected_all <dbl>, iden <chr>, `1` <dbl>, `2` <dbl>, `3` <dbl>, and
#> # abbreviated variable names ¹sample_array_ID, ²meanX2_X3, ³meanX1_X3,
#> # ⁴meanX1_X2