Last updated: 2023-03-02

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Aim

Following the consistency test, the aim of this test is to assess how Accurate that Varispan arm on Janus G3 under the revised automation workflow for oNKo project

Researcher

ML

Readout

  1. Plate weight increase after dispensing

  2. Absorbance of tartrazine at 410 on Cytation C10 plate reader

Required R packages

# load the required packages
library(data.table)
library(DT)
library(platetools)
library(reshape2)
library(readxl)
library(tidyverse)
library(patchwork)
library(here)
library(htmltools)


# check if here() correctly identified the directory
here::here()
[1] "/home/mli/ML_oNKo/230224_accuracytest/Automation_Accuracy"
# set the file prefix

prefix <- "ML_oNKo_dev"

# def funct
read_excel_allsheets <- function(filename, tibble = FALSE) {
    sheets <- readxl::excel_sheets(filename)
    x <- lapply(sheets, function(X) readxl::read_excel(filename, sheet = X, skip = 24))
    if (!tibble)
        x <- lapply(x, as.data.frame)
    names(x) <- sheets
    x
}

Details

Test date (yyyy-mm-dd)

2023-02-24

Tartrazine concentration and weight test

Tartrazine stock at 12.5 ug/ul

For Absorbance Standard Curve(STD), a working solution of 5ug/ul was made and dispensed into the column 1, then a serial 1 in 2 dilution was carried out til col 23. Another 0.04ug/ul dye solution stock is used for varispan addition into wells.

Be careful of the sensitivity of the assay (e.g abs 0.045 ish). Standard curve of tartrazine absorbance (Abs) was constructed by in triplicates

Delivery Accuracy by Weight Increase

For weight test

1ml of the Dye (0.1ug/ul) weights 1.01 g

Plate 1 (8ul addition) weights 90.54g with 200 wells of PBS (20ul each) Plate 2 (10ul addition) weights 90.42g with 200 wells of PBS (20ul each)

After 1st round of dispensing Plate 1 (8ul addition) weights 92.06g Plate 2 (10ul addition) weights 92.36g

After 2nd round of dispensing Plate 1 (8ul addition) weights 93.60g Plate 2 (10ul addition) weights 94.26g

Dye density est.= 1.01g/1000ul

After 1st round of dispensing

Plate 1 (8ul addition, 200 wells) delta 1.42g ~ Avg 7.03 ul liquid added per well Plate 2 (10ul addition, 200 wells) delta 1.92g ~ Avg 9.55 ul liquid added per well

After 2nd round of dispensing

Plate 1 (8ul addition, 200 wells) delta 1.54 ~ Avg 7.62 ul liquid added per well Plate 2 (10ul addition, 200 wells) deta 1.90g ~ Avg 9.41 ul liquid added per well

Data cleaning for Abs test

The raw data was read into R Studio.

Delivery Accuracy by Abs


Raw Abs values

## Normalised Abs values {.tabset .tabset-fade .tabset-pills}

Note now we see the base line has variations (20ul PBS dispensed into each plate using BioTek)

## Abs and Z score tables for you


### Abs Delta over each previous transfer {.tabset .tabset-fade .tabset-pills} Since the baseline is not really “flat”, lets focus more on the delta of each transfer and each tip

[1] "The loop has ended !"
[1] "The loop has ended !"

Normalised Abs Delta over each previous transfer

Normalised per plate per dispense steo (ie. col 1-13, 14 to 24)

#Use standatd curve to have an Abs to Concentration conversion {.tabset .tabset-fade .tabset-pills}


Call:
lm(formula = Conc ~ Abs, data = Standard.curve)

Coefficients:
(Intercept)          Abs  
    -0.0312       0.4199


Comments: Roughly using a linear approximation: Concentration = (0.4199 xAbs - 0.0312) ug/ul. We each step the expected transfer vol so we can plot the amount of dye trasnferred to expected value.


Check the volume really added



 

Analysed by Mark Li

Victorian Centre for Functional Genomics

 


sessionInfo()
R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS:   /usr/lib64/libblas.so.3.4.2
LAPACK: /usr/lib64/liblapack.so.3.4.2

locale:
 [1] LC_CTYPE=en_AU.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_AU.UTF-8        LC_COLLATE=en_AU.UTF-8    
 [5] LC_MONETARY=en_AU.UTF-8    LC_MESSAGES=en_AU.UTF-8   
 [7] LC_PAPER=en_AU.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] htmltools_0.5.4   here_1.0.1        patchwork_1.1.2   forcats_1.0.0    
 [5] stringr_1.5.0     dplyr_1.1.0       purrr_1.0.1       readr_2.1.4      
 [9] tidyr_1.3.0       tibble_3.1.8      ggplot2_3.4.1     tidyverse_1.3.2  
[13] readxl_1.4.2      reshape2_1.4.4    platetools_0.1.5  DT_0.27          
[17] data.table_1.14.8 workflowr_1.7.0  

loaded via a namespace (and not attached):
 [1] nlme_3.1-162        fs_1.6.1            lubridate_1.9.2    
 [4] bit64_4.0.5         RColorBrewer_1.1-3  httr_1.4.4         
 [7] rprojroot_2.0.3     tools_4.2.0         backports_1.4.1    
[10] bslib_0.4.2         utf8_1.2.3          R6_2.5.1           
[13] mgcv_1.8-41         DBI_1.1.3           colorspace_2.1-0   
[16] withr_2.5.0         tidyselect_1.2.0    processx_3.8.0     
[19] bit_4.0.5           compiler_4.2.0      git2r_0.31.0       
[22] cli_3.6.0           rvest_1.0.3         formatR_1.14       
[25] xml2_1.3.3          labeling_0.4.2      sass_0.4.5         
[28] scales_1.2.1        callr_3.7.3         digest_0.6.31      
[31] rmarkdown_2.20      pkgconfig_2.0.3     highr_0.10         
[34] dbplyr_2.3.0        fastmap_1.1.0       htmlwidgets_1.6.1  
[37] rlang_1.0.6         rstudioapi_0.14     farver_2.1.1       
[40] jquerylib_0.1.4     generics_0.1.3      jsonlite_1.8.4     
[43] crosstalk_1.2.0     vroom_1.6.1         googlesheets4_1.0.1
[46] magrittr_2.0.3      Matrix_1.5-3        Rcpp_1.0.10        
[49] munsell_0.5.0       fansi_1.0.4         lifecycle_1.0.3    
[52] stringi_1.7.12      whisker_0.4.1       yaml_2.3.7         
[55] snakecase_0.11.0    plyr_1.8.8          grid_4.2.0         
[58] parallel_4.2.0      promises_1.2.0.1    crayon_1.5.2       
[61] lattice_0.20-45     splines_4.2.0       haven_2.5.1        
[64] hms_1.1.2           knitr_1.42          ps_1.7.2           
[67] pillar_1.8.1        reprex_2.0.2        glue_1.6.2         
[70] evaluate_0.20       getPass_0.2-2       modelr_0.1.10      
[73] vctrs_0.5.2         tzdb_0.3.0          httpuv_1.6.9       
[76] cellranger_1.1.0    gtable_0.3.1        assertthat_0.2.1   
[79] cachem_1.0.6        xfun_0.37           janitor_2.2.0      
[82] broom_1.0.3         later_1.3.0         googledrive_2.0.0  
[85] gargle_1.3.0        timechange_0.2.0    ellipsis_0.3.2