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insightsengineering

teal.modules.hermes:RNA-Seq Analysis Modules to Add to a Teal Application

RNA-seq analysis teal modules based on the `hermes` package.

Maintained by Daniel Sabanés Bové. Last updated 1 years ago.

modulesrna-seq-analysisshiny

7 stars 5.54 score 32 scripts

brad-cannell

codebookr:Create Codebooks from Data Frames

Quickly and easily create codebooks (i.e. data dictionaries) directly from a data frame.

Maintained by Brad Cannell. Last updated 1 years ago.

28 stars 4.74 score 39 scripts

aus-doh-safety-and-quality

qiverse.qimatrix:QI Matrix

Defines functions needed to generate Quality Improvement Matrices in R.

Maintained by Healthcare Quality Intelligence Unit (Western Australia Health). Last updated 9 hours ago.

3 stars 3.48 score

ices-tools-prod

icesFO:Functions to support the creation of ICES Fisheries Overviews

Functions to support the creation of ICES Fisheries Overviews.

Maintained by Adriana Villamor. Last updated 10 months ago.

2 stars 3.41 score 260 scripts

haghish

adjROC:Computing Sensitivity at a Fix Value of Specificity and Vice Versa as Well as Bootstrap Metrics for ROC Curves

This software assesses the receiver operating characteristic (ROC) curve at adjusted thresholds, enabling the comparison of sensitivity and specificity across multiple binary classification models. Instead of comparing different models with varied cutoff values in their risk thresholds, all models can be compared at a fixed threshold of sensitivity, a fixed threshold of specificity, or the crossing point between sensitivity and specificity. If a threshold for specificity is given (e.g., specificity = 0.9), sensitivity and its confidence interval are computed, and vice versa. If the threshold for either sensitivity or specificity is not provided, the crossing point between the sensitivity and specificity curves is returned, along with their confidence intervals. For bootstrap procedures, the software evaluates the mean and CI bootstrap values for sensitivity, specificity, and the crossing point between specificity and sensitivity. This allows users to discern whether the performance of a model (based on adjusted sensitivity or adjusted specificity) is significantly different from other models. This software addresses the issue of comparing different classification models with varying predefined cutoff thresholds, which often leads to inconclusive results due to the fluctuating values of both sensitivity and specificity.

Maintained by E. F. Haghish. Last updated 9 months ago.

2.70 score

a2-ai

reportifyr:Reproducible Reporting Made Simple in R

Create reproducible reports with Microsoft Word and R.

Maintained by Jacob Dumbleton. Last updated 1 months ago.

1 stars 2.70 score 10 scripts

izmirlig

pwrFDR:FDR Power

Computing Average and TPX Power under various BHFDR type sequential procedures. All of these procedures involve control of some summary of the distribution of the FDP, e.g. the proportion of discoveries which are false in a given experiment. The most widely known of these, the BH-FDR procedure, controls the FDR which is the mean of the FDP. A lesser known procedure, due to Lehmann and Romano, controls the FDX, or probability that the FDP exceeds a user provided threshold. This is less conservative than FWE control procedures but much more conservative than the BH-FDR proceudre. This package and the references supporting it introduce a new procedure for controlling the FDX which we call the BH-FDX procedure. This procedure iteratively identifies, given alpha and lower threshold delta, an alpha* less than alpha at which BH-FDR guarantees FDX control. This uses asymptotic approximation and is only slightly more conservative than the BH-FDR procedure. Likewise, we can think of the power in multiple testing experiments in terms of a summary of the distribution of the True Positive Proportion (TPP), the portion of tests truly non-null distributed that are called significant. The package will compute power, sample size or any other missing parameter required for power defined as (i) the mean of the TPP (average power) or (ii) the probability that the TPP exceeds a given value, lambda, (TPX power) via asymptotic approximation. All supplied theoretical results are also obtainable via simulation. The suggested approach is to narrow in on a design via the theoretical approaches and then make final adjustments/verify the results by simulation. The theoretical results are described in Izmirlian, G (2020) Statistics and Probability letters, "<doi:10.1016/j.spl.2020.108713>", and an applied paper describing the methodology with a simulation study is in preparation. See citation("pwrFDR").

Maintained by Grant Izmirlian. Last updated 3 months ago.

2.58 score 19 scripts

rmheiberger

microplot:Microplots (Sparklines) in 'LaTeX', 'Word', 'HTML', 'Excel'

The microplot function writes a set of R graphics files to be used as microplots (sparklines) in tables in either 'LaTeX', 'HTML', 'Word', or 'Excel' files. For 'LaTeX', we provide methods for the Hmisc::latex() generic function to construct 'latex' tabular environments which include the graphs. These can be used directly with the operating system 'pdflatex' or 'latex' command, or by using one of 'Sweave', 'knitr', 'rmarkdown', or 'Emacs org-mode' as an intermediary. For 'MS Word', the msWord() function uses the 'flextable' package to construct 'Word' tables which include the graphs. There are several distinct approaches for constructing HTML files. The simplest is to use the msWord() function with argument filetype="html". Alternatively, use either 'Emacs org-mode' or the htmlTable::htmlTable() function to construct an 'HTML' file containing tables which include the graphs. See the documentation for our as.htmlimg() function. For 'Excel' use on 'Windows', the file examples/irisExcel.xls includes 'VBA' code which brings the individual panels into individual cells in the spreadsheet. Examples in the examples and demo subdirectories are shown with 'lattice' graphics, 'ggplot2' graphics, and 'base' graphics. Examples for 'LaTeX' include 'Sweave' (both 'LaTeX'-style and 'Noweb'-style), 'knitr', 'emacs org-mode', and 'rmarkdown' input files and their 'pdf' output files. Examples for 'HTML' include 'org-mode' and 'Rmd' input files and their webarchive 'HTML' output files. In addition, the as.orgtable() function can display a data.frame in an 'org-mode' document. The examples for 'MS Word' (with either filetype="docx" or filetype="html") work with all operating systems. The package does not require the installation of 'LaTeX' or 'MS Word' to be able to write '.tex' or '.docx' files.

Maintained by Richard M. Heiberger. Last updated 3 years ago.

1 stars 2.56 score 36 scripts

tomashovorka

WordR:Rendering Word Documents with R Inline Code

Serves for rendering MS Word documents with R inline code and inserting tables and plots.

Maintained by Tomas Hovorka. Last updated 2 years ago.

1 stars 2.00 score 7 scripts

ices-tools-prod

icesdown:ICES Rmarkdown tools

A collection of rmarkdown and pandoc versions of various ICES templates can be found here.

Maintained by Iago Mosqueira. Last updated 3 years ago.

1.70 score 1 scripts