Control multiple legends. Control top X axis breaks data file shared on Google drive plot-data_Daily-number-containers-collected-refunded_holidays.csv plot-data_number-to-place-on-top-of-bars.csv plot-title-data_totals.csv plot-title-data_running-totals.csv Plot Daily-number-containers-collected-refunded_holidays_plot-has-problems

Issue Graph color not matched legend color. activity.type='Strength & Stability Workout' is shown in gray, not pink. Using a different color palette doesn't make a difference. Screen Shot 12-02-23 at 11.17 AM tail(activities.2023.11, n=3) # start.date.local moving.time.hour activity.type #23 2023-11-15 2.182778 Ride #24 2023-11-15 1.505278 Strength & Stability Workout #25 2023-11-16 1.158056 Run Issue R files shown as 0 KB. R files reopened as empty in RStudio.

Access SAS Studio on Azure :::warning Problem In Windows10, Start> Photo icon > Change account settings > Access work or school > Connected to GREENLIGHT CLINICAL PTY LTD's Azure AD > Info > Sync. Screen Shot 12-01-23 at 11.58 AM Device sync status is always "The sync is in progress" Screen Shot 11-30-23 at 01.46 PM

Chang's collection of working R code and plots. Visualising time series data Fitness data :::info Data source: activities.csv from Strava bulk download X variable: Activity day of year derived from Activity.Date Y variable: Cumulative riding distance derived from Distance Legend variable: Activity year derived from Activity.Date

Create SAS formats from specfication Excel file :::warning How to use column Codelists[Codelist], Codelists[Code Text] and Codelists[CDISC_Submission_Value] from the spec file C-200-001_sdtm - Copy.xlsx to create a SAS format named $CL_DEMS0101F where the label and start variables take values from the Codelists[CDISC_Submission_Value] and Codelists[Code Text] and the format name is created by modifying the Codelists[Codelist]: ::: :::success

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Different types of clinical research studies Learn About Studies|ClinicalTrials.gov Interim Analysis An interim analysis (IA) is conducted before data collection has been completed. Clinical trials are unusual in that enrollment of subjects is a continual process staggered in time. If a treatment can be proven to be clearly beneficial or harmful compared to the concurrent control, or to be obviously futile, based on a pre-defined analysis of an incomplete data set while the study is on-going, the investigators may stop the study early. Sample size and power If the purpose on an IA is for assessment of the primary endpoint, then it is the responsibility of the Lead Biostatistician or designee to ensure that the type I error is appropriately controlled. For example, p-values and/or decision boundaries could be calculated with a group sequential technique such as O’Brien-Fleming, Lan-De Mets, etc., using validated software such as SAS PROC SEQDESIGN and PROC SEQTEST. The trial must have sufficient power to assess the primary endpoint after taking into account any planned IAs If an IA is for the purpose of assessing the primary endpoint, the statistician who performs any IAs will be unblinded/unmasked early and therefore should not be the statistician who performs the final analysis of the primary endpoint. In addition, any unblinded/unmasked statistician must ensure that unblinded/unmasked results are only communicated to appropriate people.

Resize 1 photo # Bring installed packages to memory library(jpeg) library(dplyr) library(foreach) library(doParallel) # Input and output directories dir.C.drive <-"C:" dir.G.drive <- "G:/My Drive"

R code used to generate outcome demonstrated during knowledge hour presentation at GLC 21-04-2023 Set up directory # Input and output directories dir.C.drive <-"C:" dir.R.packages <- file.path(dir.C.drive,"R","R-4.1.3") dir.main <- file.path(dir.C.drive,"Google-Drive") dir.GLC <- file.path(dir.main,"Greenlight-clinical") dir.GLC.presentation <- file.path(dir.GLC,"Knowledge-hours-presentation") dir.GLC.data <- file.path(dir.GLC.presentation, "data-download")

What is Pinnacle 21? Pinnacle 21, also known as OpenCDISC Validator, provides great compliance checks against CDISC outputs like SDTM, ADaM, SEND and Define.xml.Common Pinnacle 21 Report Issues: Shall we Document or Fix? Pinnacle 21 validation report PINNACLE 21 COMMUNITY VALIDATOR TOOL: Pinnacle 21 Community Validator is the leading industry tool for validating SDTM data sets against CDISC standards (for more information about CDISC standards, please see cdisc.org). After the validator has finished checking the SDTM data sets, findings are made available to the user, typically in Excel format. The findings report consists of four tabs: Datasets Summary, Issue Summary, Details, and Rules. The Datasets Summary tab provides an overview of the contents for each input file and contains summary information about the total number of records, errors, warnings, and notices for each domain. The Issue Summary tab breaks down issues by severity (error, warning, and notice) and by type for each domain. Each issue type is categorized by FDA Publisher ID, which represents the FDA’s published business rules. A description of each rule can be found on the Rules tab. The Details tab includes all issues in an expanded format and is presented on the record level. This tab includes the domain, record number, count, variables, values, rule ID, message, category, and severity for each issue.

Butterfly pea Source Gary Shih Cost 0 Date obtained 20210417 Indian guava Botanical name Psidium guajava Source Bunnings stafford Cost 14.98

Extract numbers of varying length from the end of strings # Get file names of pdf or docx files file.names <- list.files( path=dir.assignment.2 ,pattern=".*\\.pdf$|.*\\.docx$" ,full.names=FALSE) # length(file.names) 21 file.names # [1] "agarslawrence_204628_20026409_DMC_Assignment2_4614834-1.docx" # [2] "andrewstimothy_297293_19936198_DMC Assignment 2 0953.docx" # [3] "ashtonisabel_294366_19979255_DMC_2021S2_A2_6589.pdf"

Using the R function in next section to get cut points for continuous predicting variables (predictors), dichotomise the predictors and run univariable cox regression Download a survival data file from QIMR L drive L:/Lab_MarkS/lunC/work/Immunohistochemistry_images/data_output/AP_Exp108.1_PeterMac-lungCancer-CD8-PD1/analysis-results/PeterMac-lung-cancer-cohort-1-DFS-marker-counts.tsv Create a new R script file. Copy the code chunk and modify the path of input, output files or folders Run the source() function to load the R function to the working environment. Modify the file path within the double quotes. Make sure backword slashes \ are replaced by forward slashes / when the path is copied from Windows address bar.

Author: Lun-Hsien Chang Date created: May 2020 Using the R function in next section to annotate all IHC images Download the cell segmentation data file cell-seg-data-merged_CD8.txt from QIMR L drive L:/Lab_MarkS/lunC/work/Immunohistochemistry_images/data_output/AP_Exp108.1_PeterMac-lungCancer-CD8-PD1/analysis-results Download the folder with IHC image files from QIMR L drive L:/Lab_MarkS/lunC/work/Immunohistochemistry_images/data_input/AshR/1. mIHF/Exp 108 210728/CD8 path Create a new R script file. Copy the code chunk below and modify the path of input files and folders. Run the source() function to load the R function to the working environment.

Replace missing values with non-missing values in groups Filling missing value in group have <- data.frame( row.number=c(1:6) ,ID=c("A","A","A","B","B","B") ,v1=c(NA,1,NA, NA, NA, 3) ,v2=c(NA,NA,"Yes",NA,"Yes",NA) ,stringsAsFactors = F)

The aim is to scrape all the tables at Connect Chrome driver, RSelenium Data Analysis and Extraction - RSelenium tutorial Install R packages dir.R.packages <- "C:/Program Files/R/R-4.0.3/library" #install.packages("tidyquant", lib = dir.R.packages)

Chang's collection of working examples in Bash, Shell awk Syntax awk -F "$file_delimiter" -v awk_var1=${shell_var1} -v awk_var2=${shell_var2} 'BEGIN {print "colname1","colname2"} {print $awk_var1,$awk_var2}' $filePath Loop thruough unique combinations (e.g. lower diagonal) of a 10 by 10 matrix using for and awk. # You should know how many iterations will be run, say 10choose2. Get this in R choose(10,2) [1] 45

Our speakers in 2020 November TBA December TBA Upcoming meeting Meeting 18 Time: 1-2pm, Tuesday 24 November 2020, AEST Bancroft Auditorium, Level 6, Bancroft Building, QIMR Berghofer Join from PC, Mac, Linux, iOS or Android via https://qimrberghofer.zoom.us/j/85788177791?pwd=TTVFdGcxYmFNaUtvREZoY1hKbHRjdz09

qsub Submit one job ## Example 1 qsub -l select=1:ncpus=1:mem=8gb -l walltime=10:0:0 ${locTest}/ADHD2017.1.PRS.sh #2675742.hpcpbs02 qstat -u lunC # hpcpbs02: # Req'd Req'd Elap

Tissue segmentation, cell segmentation, cell phenotyping using software InForm version 2.3 Batch Analysis Click on Batch Analysis Check all 'images to export' except for the two TIFF Select JPEG as output image format Check all boxes of 'Tables to export' Click 'Browse' to select export directory Click 'Add Images' to select testing images from a testing folder. In this run, five images from the RBH were used as training images, the other images were used as testing images. Hit 'Run'. This applies the training algorithm to the images selected to segment tissue (into Tumor, Stroma, Glass, others), segment cells (into Nuclei and cytoplasm) and phenotype cells (into tumor cells, immune cells based on the staining of CD8, CD96. Immune cells can be CD8+, CD96+, or double positive). 'Batch progress' appears. This will take a long time.