Last updated: 2023-02-22
Checks: 6 1
Knit directory: oNKo_automation_dev/
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The aim of this test is to assess how consistent that Varispan arm on Janus G3 under the revised automation workflow for oNKo
ML
Absorbance of tartrazine at 410 on Cytation C10 plate reader
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_oNKo/230220_143052_230220_ML_oNKo_Sanitycheck/oNKo_automation_dev"
# 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
}
2023-02-22
Tartrazine stock at 12.5 ug/ul
The raw data was read into R Studio.
Comments: To save $ and time, I did one round
of dispensing to half of the plate. To get accuracy measure, I will have
to have a standard curve, and do multiple dispensing rounds, using the
delta to estimate accuracy.
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] fs_1.6.1 lubridate_1.9.2 bit64_4.0.5
[4] RColorBrewer_1.1-3 httr_1.4.4 rprojroot_2.0.3
[7] tools_4.2.0 backports_1.4.1 bslib_0.4.2
[10] utf8_1.2.3 R6_2.5.1 DBI_1.1.3
[13] colorspace_2.1-0 withr_2.5.0 tidyselect_1.2.0
[16] processx_3.8.0 bit_4.0.5 compiler_4.2.0
[19] git2r_0.31.0 cli_3.6.0 rvest_1.0.3
[22] formatR_1.14 xml2_1.3.3 labeling_0.4.2
[25] sass_0.4.5 scales_1.2.1 callr_3.7.3
[28] digest_0.6.31 rmarkdown_2.20 pkgconfig_2.0.3
[31] highr_0.10 dbplyr_2.3.0 fastmap_1.1.0
[34] htmlwidgets_1.6.1 rlang_1.0.6 rstudioapi_0.14
[37] farver_2.1.1 jquerylib_0.1.4 generics_0.1.3
[40] jsonlite_1.8.4 crosstalk_1.2.0 vroom_1.6.1
[43] googlesheets4_1.0.1 magrittr_2.0.3 Rcpp_1.0.10
[46] munsell_0.5.0 fansi_1.0.4 lifecycle_1.0.3
[49] stringi_1.7.12 whisker_0.4.1 yaml_2.3.7
[52] snakecase_0.11.0 plyr_1.8.8 grid_4.2.0
[55] parallel_4.2.0 promises_1.2.0.1 crayon_1.5.2
[58] haven_2.5.1 hms_1.1.2 knitr_1.42
[61] ps_1.7.2 pillar_1.8.1 reprex_2.0.2
[64] glue_1.6.2 evaluate_0.20 getPass_0.2-2
[67] modelr_0.1.10 vctrs_0.5.2 tzdb_0.3.0
[70] httpuv_1.6.9 cellranger_1.1.0 gtable_0.3.1
[73] assertthat_0.2.1 cachem_1.0.6 xfun_0.37
[76] janitor_2.2.0 broom_1.0.3 later_1.3.0
[79] googledrive_2.0.0 gargle_1.3.0 timechange_0.2.0
[82] ellipsis_0.3.2