Last updated: 2022-09-08

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Rmd 838181c Mark Li 2022-09-08 workflowr::wflow_publish("analysis/Pintool_dev_220901.Rmd")

Aim

The aim of this test is to assess how consistent that 384 pintool on Janus G3 in 100nl delivery after improved the plate heights and dipping numbers

Researcher

ML

Readout

Absorbance of tartrazine at 410 on Cytation 5 plate reader

Required R packages

data.table, DT, platetools, reshape2, tidyverse, patchwork

# 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_Mac-Seq/Pintool_dev/220908_test"
# set the file prefix

prefix <- "ML_Mac-Seq_Pintool_dev"

Screen details

Screen date (yyyy-mm-dd)

2022-09-08

Tartrazine concentration

Tartrazine stock at 12.5 ug/ul Source plate made @ tartrazine 10 ug/ul with 1X PBS

Standard curve

Standard curve of tartrazine absorbance (Abs) was constructed by triplicate serial dilution

Plate layout



Known technical issues

Plate reader Abs signal saturation occurs between 0.08 to 0.16 ug/ul tartrazine.

First transfers were done with height 5mm above well bottom, and latter changed to 4mm. Dipping numbers changed to 5 times.

Washing station this time is much better off Visible edge effect on the source plate (it has been on the desk for 7 days)

Data cleaning

Formatting and Preprocessing

The raw data was read into R Studio.

Data processing

Pintool Delivery Quality

Pintool Consistency Heatmaps


Comments: I would like to look at the standard curve plate, and target plate after each transfer

Abs Raw values


Abs Z score per plate


Abs Delta over each previous transfer

[1] "The loop has ended !"


Consistency Check by Outlier Detection


Comments: I want to have an overview of pins that are significantly correlated (positively and negatively) using the delta of Abs values after each pintool transfer. Ideally, all the pins working in perfect harmony should all the strongly positively correlated in the abs delta.

Pintool Accuracy

Standard Curve


Comments: Now that I know the consistency is not ideal, I want to know just how accurate the pintool is in delivery the labelled 100nl volume. In theory, a 100nl of my stock 10ug/ul tartrazine trasnferred into 50ul PBS should give a final 0.02 ug/ul (i.e. 1ug dye increament). Using the standard curve constructed, I can get a portion of it where Abs readings and dye concentrations approximated a linear relationship (unfortunately the next dye concentration 0.16 ug/ul had an Abs value beyond detection limit). In this roughly linear section, tartrazine concentration covered is ranging 0.002 ug/ul to 0.08 ug/ul, covering the final concentration for at least 4 transfers in this test. I can use this to estimate the dye (hence real volume) transferred by each pin at each transfer, see how far off is that compared to 100nl



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

Coefficients:
(Intercept)          Abs  
  -0.003111     0.037737


Comments: Roughly using a linear approximation: Concentration = (0.038xAbs - 0.003) ug/ul.The volume change by trasnferring a couple rounds of 100nl into 50ul well is less than 1%. So we can have the relationship of Volume = (0.19xAbs - 0.015)x1000 nl

Convert Abs Delta to Volume



 

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_0.5.3   here_1.0.1        patchwork_1.1.2   forcats_0.5.2    
 [5] stringr_1.4.1     dplyr_1.0.10      purrr_0.3.4       readr_2.1.2      
 [9] tidyr_1.2.0       tibble_3.1.8      ggplot2_3.3.6     tidyverse_1.3.2  
[13] readxl_1.4.1      reshape2_1.4.4    platetools_0.1.5  DT_0.24          
[17] data.table_1.14.2 workflowr_1.7.0  

loaded via a namespace (and not attached):
 [1] nlme_3.1-159        fs_1.5.2            lubridate_1.8.0    
 [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_0.4.0         utf8_1.2.2          R6_2.5.1           
[13] DBI_1.1.3           colorspace_2.0-3    withr_2.5.0        
[16] tidyselect_1.1.2    processx_3.7.0      bit_4.0.4          
[19] compiler_4.2.0      git2r_0.30.1        cli_3.3.0          
[22] rvest_1.0.3         formatR_1.12        xml2_1.3.3         
[25] labeling_0.4.2      sass_0.4.2          scales_1.2.1       
[28] callr_3.7.2         digest_0.6.29       rmarkdown_2.16     
[31] pkgconfig_2.0.3     highr_0.9           dbplyr_2.2.1       
[34] fastmap_1.1.0       htmlwidgets_1.5.4   rlang_1.0.5        
[37] rstudioapi_0.14     farver_2.1.1        jquerylib_0.1.4    
[40] generics_0.1.3      jsonlite_1.8.0      crosstalk_1.2.0    
[43] vroom_1.5.7         googlesheets4_1.0.1 magrittr_2.0.3     
[46] Rcpp_1.0.9          munsell_0.5.0       fansi_1.0.3        
[49] lifecycle_1.0.1     stringi_1.7.8       whisker_0.4        
[52] yaml_2.3.5          plyr_1.8.7          grid_4.2.0         
[55] parallel_4.2.0      promises_1.2.0.1    crayon_1.5.1       
[58] lattice_0.20-45     splines_4.2.0       haven_2.5.1        
[61] hms_1.1.2           knitr_1.40          ps_1.7.1           
[64] pillar_1.8.1        reprex_2.0.2        glue_1.6.2         
[67] evaluate_0.16       getPass_0.2-2       modelr_0.1.9       
[70] vctrs_0.4.1         tzdb_0.3.0          httpuv_1.6.5       
[73] cellranger_1.1.0    gtable_0.3.1        assertthat_0.2.1   
[76] cachem_1.0.6        xfun_0.32           mime_0.12          
[79] broom_1.0.1         later_1.3.0         googledrive_2.0.0  
[82] gargle_1.2.0        corrplot_0.92       ellipsis_0.3.2