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jacek_marzec / packages

Package Name Access Summary Updated
r-coxphf public Implements Firth's penalized maximum likelihood bias reduction method for Cox regression which has been shown to provide a solution in case of monotone likelihood (nonconvergence of likelihood function). The program fits profile penalized likelihood confidence intervals which were proved to outperform Wald confidence intervals. 2023-08-23
r-risksetroc public Compute time-dependent Incident/dynamic accuracy measures (ROC curve, AUC, integrated AUC )from censored survival data under proportional or non-proportional hazard assumption of Heagerty & Zheng (Biometrics, Vol 61 No 1, 2005, PP 92-105). 2023-08-22
r-activedriverwgs public A method for finding an enrichment of cancer simple somatic mutations (SNVs and Indels) in functional elements across the human genome. 'ActiveDriverWGS' detects coding and noncoding driver elements using whole genome sequencing data. The method is part of the following publication: Candidate Cancer Driver Mutations in Distal Regulatory Elements and Long-Range Chromatin Interaction Networks. Molecular Cell (2020) <doi:10.1016/j.molcel.2019.12.027>. 2023-06-16
r-googlesheets public Interact with Google Sheets from R. 2023-06-16
r-h2o public R interface for 'H2O', the scalable open source machine learning platform that offers parallelized implementations of many supervised and unsupervised machine learning algorithms such as Generalized Linear Models, Gradient Boosting Machines (including XGBoost), Random Forests, Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Cox Proportional Hazards, K-Means, PCA, Word2Vec, as well as a fully automatic machine learning algorithm (AutoML). 2023-06-16
r-mailr public Interface to Apache Commons Email to send emails from R. 2023-06-16
r-lares public R library for better/faster analytics, visualization, data mining, and machine learning tasks. With a wide variety of family functions, such as Machine Learning, Data Wrangling, Exploratory, and Scrapper, lares helps the analyst or data scientist to get quick and robust results, without the need of repetitive coding or extensive programming skills. 2023-06-16
r-beepr public The main function of this package is beep(), with the purpose to make it easy to play notification sounds on whatever platform you are on. It is intended to be useful, for example, if you are running a long analysis in the background and want to know when it is ready. 2023-06-16
r-dndscv public This package contains functions for studying selection on coding sequences using a Poisson implementation of dN/dS. A Poisson model of dN/dS facilitates the study of selection beyond traditional codon models, including complex context-dependent mutation effects and selection on nonsense and splice site mutations. This model is best suited for resequencing studies, with very low density of mutations per base pair. The model was initially developed for cancer genome sequencing studies, and specific functions are provided to perform driver gene discovery using the dNdScv method on human cancer genomic data. The first beta version of this package only supports analyses of human data. Future versions of the package will support analyses on any species using a general FASTA input format. 2023-06-16
r-manhattanly public Create interactive Q-Q, manhattan and volcano plots that are usable from the R console, in the 'RStudio' viewer pane, in 'R Markdown' documents, and in 'Shiny' apps. Hover the mouse pointer over a point to show details or drag a rectangle to zoom. A manhattan plot is a popular graphical method for visualizing results from high-dimensional data analysis such as a (epi)genome wide association study (GWAS or EWAS), in which p-values, Z-scores, test statistics are plotted on a scatter plot against their genomic position. Manhattan plots are used for visualizing potential regions of interest in the genome that are associated with a phenotype. Interactive manhattan plots allow the inspection of specific value (e.g. rs number or gene name) by hovering the mouse over a cell, as well as zooming into a region of the genome (e.g. a chromosome) by dragging a rectangle around the relevant area. This work is based on the 'qqman' package by Stephen Turner and the 'plotly.js' engine. It produces similar manhattan and Q-Q plots as the 'manhattan' and 'qq' functions in the 'qqman' package, with the advantage of including extra annotation information and interactive web-based visualizations directly from R. Once uploaded to a 'plotly' account, 'plotly' graphs (and the data behind them) can be viewed and modified in a web browser. 2023-06-16

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