Showing 200 of total 265 results (show query)
interstellar-consultation-services
covid19dbcand:Selected 'Drugbank' Drugs for COVID-19 Treatment Related Data in R Format
Provides different datasets parsed from 'Drugbank' <https://www.drugbank.ca/covid-19> database using 'dbparser' package. It is a smaller version from 'dbdataset' package. It contains only information about COVID-19 possible treatment.
Maintained by Mohammed Ali. Last updated 11 months ago.
datasetdbparserdrugbankdrugbank-database
203.3 match 3 stars 4.48 score 6 scripts
bioc
PharmacoGx:Analysis of Large-Scale Pharmacogenomic Data
Contains a set of functions to perform large-scale analysis of pharmaco-genomic data. These include the PharmacoSet object for storing the results of pharmacogenomic experiments, as well as a number of functions for computing common summaries of drug-dose response and correlating them with the molecular features in a cancer cell-line.
Maintained by Benjamin Haibe-Kains. Last updated 2 months ago.
geneexpressionpharmacogeneticspharmacogenomicssoftwareclassificationdatasetspharmacogenomicpharmacogxcpp
41.7 match 68 stars 11.39 score 442 scripts 3 dependents
ctn-0094
DOPE:Drug Ontology Parsing Engine
Provides information on drug names (brand, generic and street) for drugs tracked by the DEA. There are functions that will search synonyms and return the drug names and types. The vignettes have extensive information on the work done to create the data for the package.
Maintained by Raymond Balise. Last updated 4 years ago.
54.9 match 21 stars 7.83 score 31 scripts
darwin-eu
DrugExposureDiagnostics:Diagnostics for OMOP Common Data Model Drug Records
Ingredient specific diagnostics for drug exposure records in the Observational Medical Outcomes Partnership (OMOP) common data model.
Maintained by Ger Inberg. Last updated 3 days ago.
59.8 match 4 stars 7.11 score 41 scriptsbioc
Rcpi:Molecular Informatics Toolkit for Compound-Protein Interaction in Drug Discovery
A molecular informatics toolkit with an integration of bioinformatics and chemoinformatics tools for drug discovery.
Maintained by Nan Xiao. Last updated 5 months ago.
softwaredataimportdatarepresentationfeatureextractioncheminformaticsbiomedicalinformaticsproteomicsgosystemsbiologybioconductorbioinformaticsdrug-discoveryfeature-extractionfingerprintmolecular-descriptorsprotein-sequences
39.3 match 37 stars 7.81 score 29 scriptsdarwin-eu
DrugUtilisation:Summarise Patient-Level Drug Utilisation in Data Mapped to the OMOP Common Data Model
Summarise patient-level drug utilisation cohorts using data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. New users and prevalent users cohorts can be generated and their characteristics, indication and drug use summarised.
Maintained by Martí Català. Last updated 2 months ago.
34.8 match 8.27 score 156 scripts 2 dependents
alanarnholt
BSDA:Basic Statistics and Data Analysis
Data sets for book "Basic Statistics and Data Analysis" by Larry J. Kitchens.
Maintained by Alan T. Arnholt. Last updated 2 years ago.
27.3 match 7 stars 9.11 score 1.3k scripts 6 dependents
msberends
AMR:Antimicrobial Resistance Data Analysis
Functions to simplify and standardise antimicrobial resistance (AMR) data analysis and to work with microbial and antimicrobial properties by using evidence-based methods, as described in <doi:10.18637/jss.v104.i03>.
Maintained by Matthijs S. Berends. Last updated 7 hours ago.
amrantimicrobial-dataepidemiologymicrobiologysoftware
16.1 match 92 stars 11.87 score 182 scripts 6 dependents
mrc-ide
malariasimulation:An individual based model for malaria
Specifies the latest and greatest malaria model.
Maintained by Giovanni Charles. Last updated 27 days ago.
21.3 match 16 stars 8.17 score 146 scriptsbioc
signatureSearch:Environment for Gene Expression Searching Combined with Functional Enrichment Analysis
This package implements algorithms and data structures for performing gene expression signature (GES) searches, and subsequently interpreting the results functionally with specialized enrichment methods.
Maintained by Brendan Gongol. Last updated 5 months ago.
softwaregeneexpressiongokeggnetworkenrichmentsequencingcoveragedifferentialexpressioncpp
23.7 match 17 stars 7.18 score 74 scripts 1 dependents
pharmacologie-caen
vigicaen:'VigiBase' Pharmacovigilance Database Toolbox
Perform the analysis of the World Health Organization (WHO) Pharmacovigilance database 'VigiBase' (Extract Case Level version), <https://who-umc.org/> e.g., load data, perform data management, disproportionality analysis, and descriptive statistics. Intended for pharmacovigilance routine use or studies. This package is NOT supported nor reflect the opinion of the WHO, or the Uppsala Monitoring Centre. Disproportionality methods are described by Norén et al (2013) <doi:10.1177/0962280211403604>.
Maintained by Charles Dolladille. Last updated 3 days ago.
datamanagementpharmacovigilance
26.9 match 1 stars 6.27 score 11 scripts
sterniii3
drugdevelopR:Utility-Based Optimal Phase II/III Drug Development Planning
Plan optimal sample size allocation and go/no-go decision rules for phase II/III drug development programs with time-to-event, binary or normally distributed endpoints when assuming fixed treatment effects or a prior distribution for the treatment effect, using methods from Kirchner et al. (2016) <doi:10.1002/sim.6624> and Preussler (2020). Optimal is in the sense of maximal expected utility, where the utility is a function taking into account the expected cost and benefit of the program. It is possible to extend to more complex settings with bias correction (Preussler S et al. (2020) <doi:10.1186/s12874-020-01093-w>), multiple phase III trials (Preussler et al. (2019) <doi:10.1002/bimj.201700241>), multi-arm trials (Preussler et al. (2019) <doi:10.1080/19466315.2019.1702092>), and multiple endpoints (Kieser et al. (2018) <doi:10.1002/pst.1861>).
Maintained by Lukas D. Sauer. Last updated 2 months ago.
26.0 match 3 stars 6.39 score 15 scripts
hanjunwei-lab
SubtypeDrug:Prioritization of Candidate Cancer Subtype Specific Drugs
A systematic biology tool was developed to prioritize cancer subtype-specific drugs by integrating genetic perturbation, drug action, biological pathway, and cancer subtype. The capabilities of this tool include inferring patient-specific subpathway activity profiles in the context of gene expression profiles with subtype labels, calculating differentially expressed subpathways based on cultured human cells treated with drugs in the 'cMap' (connectivity map) database, prioritizing cancer subtype specific drugs according to drug-disease reverse association score based on subpathway, and visualization of results (Castelo (2013) <doi:10.1186/1471-2105-14-7>; Han et al (2019) <doi:10.1093/bioinformatics/btz894>; Lamb and Justin (2006) <doi:10.1126/science.1132939>). Please cite using <doi:10.1093/bioinformatics/btab011>.
Maintained by Junwei Han. Last updated 1 years ago.
38.4 match 2 stars 4.00 score 3 scriptsbioc
rcellminer:rcellminer: Molecular Profiles, Drug Response, and Chemical Structures for the NCI-60 Cell Lines
The NCI-60 cancer cell line panel has been used over the course of several decades as an anti-cancer drug screen. This panel was developed as part of the Developmental Therapeutics Program (DTP, http://dtp.nci.nih.gov/) of the U.S. National Cancer Institute (NCI). Thousands of compounds have been tested on the NCI-60, which have been extensively characterized by many platforms for gene and protein expression, copy number, mutation, and others (Reinhold, et al., 2012). The purpose of the CellMiner project (http://discover.nci.nih.gov/ cellminer) has been to integrate data from multiple platforms used to analyze the NCI-60 and to provide a powerful suite of tools for exploration of NCI-60 data.
Maintained by Augustin Luna. Last updated 5 months ago.
acghcellbasedassayscopynumbervariationgeneexpressionpharmacogenomicspharmacogeneticsmirnacheminformaticsvisualizationsoftwaresystemsbiology
26.8 match 5.71 score 113 scripts
bernd-mueller
epos:Epilepsy Ontologies' Similarities
Analysis and visualization of similarities between epilepsy ontologies based on text mining results by comparing ranked lists of co-occurring drug terms in the BioASQ corpus. The ranked result lists of neurological drug terms co-occurring with terms from the epilepsy ontologies EpSO, ESSO, EPILONT, EPISEM and FENICS undergo further analysis. The source data to create the ranked lists of drug names is produced using the text mining workflows described in Mueller, Bernd and Hagelstein, Alexandra (2016) <doi:10.4126/FRL01-006408558>, Mueller, Bernd et al. (2017) <doi:10.1007/978-3-319-58694-6_22>, Mueller, Bernd and Rebholz-Schuhmann, Dietrich (2020) <doi:10.1007/978-3-030-43887-6_52>, and Mueller, Bernd et al. (2022) <doi:10.1186/s13326-021-00258-w>.
Maintained by Bernd Mueller. Last updated 1 years ago.
34.5 match 4.03 score 53 scripts
cogdisreslab
drugfindR:Investigate iLINCS for candidate repurposable drugs
This package provides a convenient way to access the LINCS Signatures available in the iLINCS database. These signatures include Consensus Gene Knockdown Signatures, Gene Overexpression signatures and Chemical Perturbagen Signatures. It also provides a way to enter your own transcriptomic signatures and identify concordant and discordant signatures in the LINCS database.
Maintained by Ali Sajid Imami. Last updated 21 days ago.
lincsilincsdrug repurposingdrug discoverytranscriptomicsgene expressiongene knockdowngene overexpressionchemical perturbagendrugfindrbioinformaticsbioinformatics-pipeline
20.9 match 8 stars 6.16 score 145 scriptsctn-0094
public.ctn0094data:De-Identified Data from CTN-0094
These are harmonized datasets produced as part of the Clinical Trials Network (CTN) protocol number 0094. This is a US National Institute of Drug Abuse (NIDA) funded project; to learn more go to <https://ctnlibrary.org/protocol/ctn0094/>. These are datasets which have the data harmonized from CTN-0027 (<https://ctnlibrary.org/protocol/ctn0027/>), CTN-0030 (<https://ctnlibrary.org/protocol/ctn0030/>), and CTN-0051 (<https://ctnlibrary.org/protocol/ctn0051/>).
Maintained by Raymond Balise. Last updated 1 years ago.
26.5 match 4.86 score 24 scripts 1 dependentsbioc
DeepTarget:Deep characterization of cancer drugs
This package predicts a drug’s primary target(s) or secondary target(s) by integrating large-scale genetic and drug screens from the Cancer Dependency Map project run by the Broad Institute. It further investigates whether the drug specifically targets the wild-type or mutated target forms. To show how to use this package in practice, we provided sample data along with step-by-step example.
Maintained by Trinh Nguyen. Last updated 5 months ago.
genetargetgenepredictionpathwaysgeneexpressionrnaseqimmunooncologydifferentialexpressiongenesetenrichmentreportwritingcrispr
24.6 match 4.54 score 1 scripts
detlew
PowerTOST:Power and Sample Size for (Bio)Equivalence Studies
Contains functions to calculate power and sample size for various study designs used in bioequivalence studies. Use known.designs() to see the designs supported. Power and sample size can be obtained based on different methods, amongst them prominently the TOST procedure (two one-sided t-tests). See README and NEWS for further information.
Maintained by Detlew Labes. Last updated 12 months ago.
10.9 match 20 stars 9.61 score 112 scripts 4 dependents
julianfaraway
faraway:Datasets and Functions for Books by Julian Faraway
Books are "Linear Models with R" published 1st Ed. August 2004, 2nd Ed. July 2014, 3rd Ed. February 2025 by CRC press, ISBN 9781439887332, and "Extending the Linear Model with R" published by CRC press in 1st Ed. December 2005 and 2nd Ed. March 2016, ISBN 9781584884248 and "Practical Regression and ANOVA in R" contributed documentation on CRAN (now very dated).
Maintained by Julian Faraway. Last updated 1 months ago.
10.8 match 29 stars 9.43 score 1.7k scripts 1 dependents
egeulgen
PANACEA:Personalized Network-Based Anti-Cancer Therapy Evaluation
Identification of the most appropriate pharmacotherapy for each patient based on genomic alterations is a major challenge in personalized oncology. 'PANACEA' is a collection of personalized anti-cancer drug prioritization approaches utilizing network methods. The methods utilize personalized "driverness" scores from 'driveR' to rank drugs, mapping these onto a protein-protein interaction network. The "distance-based" method scores each drug based on these scores and distances between drugs and genes to rank given drugs. The "RWR" method propagates these scores via a random-walk with restart framework to rank the drugs. The methods are described in detail in Ulgen E, Ozisik O, Sezerman OU. 2023. PANACEA: network-based methods for pharmacotherapy prioritization in personalized oncology. Bioinformatics <doi:10.1093/bioinformatics/btad022>.
Maintained by Ege Ulgen. Last updated 2 years ago.
drugnetwork-analysisoncologypersonalized-medicine
21.4 match 10 stars 4.70 score 3 scripts
openintrostat
openintro:Datasets and Supplemental Functions from 'OpenIntro' Textbooks and Labs
Supplemental functions and data for 'OpenIntro' resources, which includes open-source textbooks and resources for introductory statistics (<https://www.openintro.org/>). The package contains datasets used in our open-source textbooks along with custom plotting functions for reproducing book figures. Note that many functions and examples include color transparency; some plotting elements may not show up properly (or at all) when run in some versions of Windows operating system.
Maintained by Mine Çetinkaya-Rundel. Last updated 3 months ago.
7.8 match 240 stars 11.39 score 6.0k scriptsbioc
cogena:co-expressed gene-set enrichment analysis
cogena is a workflow for co-expressed gene-set enrichment analysis. It aims to discovery smaller scale, but highly correlated cellular events that may be of great biological relevance. A novel pipeline for drug discovery and drug repositioning based on the cogena workflow is proposed. Particularly, candidate drugs can be predicted based on the gene expression of disease-related data, or other similar drugs can be identified based on the gene expression of drug-related data. Moreover, the drug mode of action can be disclosed by the associated pathway analysis. In summary, cogena is a flexible workflow for various gene set enrichment analysis for co-expressed genes, with a focus on pathway/GO analysis and drug repositioning.
Maintained by Zhilong Jia. Last updated 5 months ago.
clusteringgenesetenrichmentgeneexpressionvisualizationpathwayskegggomicroarraysequencingsystemsbiologydatarepresentationdataimportbioconductorbioinformatics
11.4 match 12 stars 7.36 score 32 scriptsbioc
gDRcore:Processing functions and interface to process and analyze drug dose-response data
This package contains core functions to process and analyze drug response data. The package provides tools for normalizing, averaging, and calculation of gDR metrics data. All core functions are wrapped into the pipeline function allowing analyzing the data in a straightforward way.
Maintained by Arkadiusz Gladki. Last updated 4 days ago.
11.4 match 2 stars 7.25 score 4 scripts 1 dependents
ngiangre
kidsides:Download, Cache, and Connect to 'KidSIDES'
Caches and then connects to a 'sqlite' database containing half a million pediatric drug safety signals. The database is part of a family of resources catalogued at <https://nsides.io>. The database contains 17 tables where the description table provides a map between the fields the field's details. The database was created by Nicholas Giangreco during his PhD thesis which you can read in Giangreco (2022) <doi:10.7916/d8-5d9b-6738>. The observations are from the Food and Drug Administration's Adverse Event Reporting System. Generalized additive models estimated drug effects across child development stages for the occurrence of an adverse event when exposed to a drug compared to other drugs. Read more at the methods detailed in Giangreco (2022) <doi:10.1016/j.medj.2022.06.001>.
Maintained by Nicholas Giangreco. Last updated 2 years ago.
databasedruggeneralized-additive-modelsinformaticspediatricspharmacovigilancepkgdownsafety
18.6 match 5 stars 4.40 score 5 scriptsbioc
cTRAP:Identification of candidate causal perturbations from differential gene expression data
Compare differential gene expression results with those from known cellular perturbations (such as gene knock-down, overexpression or small molecules) derived from the Connectivity Map. Such analyses allow not only to infer the molecular causes of the observed difference in gene expression but also to identify small molecules that could drive or revert specific transcriptomic alterations.
Maintained by Nuno Saraiva-Agostinho. Last updated 5 months ago.
differentialexpressiongeneexpressionrnaseqtranscriptomicspathwaysimmunooncologygenesetenrichmentbioconductorbioinformaticscmapgene-expressionl1000
15.9 match 5 stars 5.08 score 16 scripts
lightbluetitan
MedDataSets:Comprehensive Medical, Disease, Treatment, and Drug Datasets
Provides an extensive collection of datasets related to medicine, diseases, treatments, drugs, and public health. This package covers topics such as drug effectiveness, vaccine trials, survival rates, infectious disease outbreaks, and medical treatments. The included datasets span various health conditions, including AIDS, cancer, bacterial infections, and COVID-19, along with information on pharmaceuticals and vaccines. These datasets are sourced from the R ecosystem and other R packages, remaining unaltered to ensure data integrity. This package serves as a valuable resource for researchers, analysts, and healthcare professionals interested in conducting medical and public health data analysis in R.
Maintained by Renzo Caceres Rossi. Last updated 5 months ago.
13.7 match 8 stars 5.68 score 60 scripts
graemeleehickey
joineR:Joint Modelling of Repeated Measurements and Time-to-Event Data
Analysis of repeated measurements and time-to-event data via random effects joint models. Fits the joint models proposed by Henderson and colleagues <doi:10.1093/biostatistics/1.4.465> (single event time) and by Williamson and colleagues (2008) <doi:10.1002/sim.3451> (competing risks events time) to a single continuous repeated measure. The time-to-event data is modelled using a (cause-specific) Cox proportional hazards regression model with time-varying covariates. The longitudinal outcome is modelled using a linear mixed effects model. The association is captured by a latent Gaussian process. The model is estimated using am Expectation Maximization algorithm. Some plotting functions and the variogram are also included. This project is funded by the Medical Research Council (Grant numbers G0400615 and MR/M013227/1).
Maintained by Graeme L. Hickey. Last updated 3 months ago.
biostatisticscompeting-riskscoxjoinerlongitudinal-datarepeated-measurementsrepeated-measuresstatisicsstatistical-methodssurvivalsurvival-analysistime-to-event
10.9 match 18 stars 6.87 score 69 scripts
smouksassi
coveffectsplot:Produce Forest Plots to Visualize Covariate Effects
Produce forest plots to visualize covariate effects using either the command line or an interactive 'Shiny' application.
Maintained by Samer Mouksassi. Last updated 1 months ago.
9.3 match 32 stars 7.86 score 40 scripts
huanglabumn
oncoPredict:Drug Response Modeling and Biomarker Discovery
Allows for building drug response models using screening data between bulk RNA-Seq and a drug response metric and two additional tools for biomarker discovery that have been developed by the Huang Laboratory at University of Minnesota. There are 3 main functions within this package. (1) calcPhenotype is used to build drug response models on RNA-Seq data and impute them on any other RNA-Seq dataset given to the model. (2) GLDS is used to calculate the general level of drug sensitivity, which can improve biomarker discovery. (3) IDWAS can take the results from calcPhenotype and link the imputed response back to available genomic (mutation and CNV alterations) to identify biomarkers. Each of these functions comes from a paper from the Huang research laboratory. Below gives the relevant paper for each function. calcPhenotype - Geeleher et al, Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines. GLDS - Geeleher et al, Cancer biomarker discovery is improved by accounting for variability in general levels of drug sensitivity in pre-clinical models. IDWAS - Geeleher et al, Discovering novel pharmacogenomic biomarkers by imputing drug response in cancer patients from large genomics studies.
Maintained by Robert Gruener. Last updated 12 months ago.
svapreprocesscorestringrbiomartgenefilterorg.hs.eg.dbgenomicfeaturestxdb.hsapiens.ucsc.hg19.knowngenetcgabiolinksbiocgenericsgenomicrangesirangess4vectors
10.8 match 18 stars 6.47 score 41 scripts
genie-bpc
genieBPC:Project GENIE BioPharma Collaborative Data Processing Pipeline
The American Association Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) BioPharma Collaborative represents a multi-year, multi-institution effort to build a pan-cancer repository of linked clinico-genomic data. The genomic and clinical data are provided in multiple releases (separate releases for each cancer cohort with updates following data corrections), which are stored on the data sharing platform 'Synapse' <https://www.synapse.org/>. The 'genieBPC' package provides a seamless way to obtain the data corresponding to each release from 'Synapse' and to prepare datasets for analysis.
Maintained by Jessica A. Lavery. Last updated 8 months ago.
9.1 match 9 stars 7.57 score 26 scriptsbioc
faers:R interface for FDA Adverse Event Reporting System
The FDA Adverse Event Reporting System (FAERS) is a database used for the spontaneous reporting of adverse events and medication errors related to human drugs and therapeutic biological products. faers pacakge serves as the interface between the FAERS database and R. Furthermore, faers pacakge offers a standardized approach for performing pharmacovigilance analysis.
Maintained by Yun Peng. Last updated 5 months ago.
softwaredataimportbiomedicalinformaticspharmacogenomicsadverse-eventsdrug-safetyfaersfaers-procedurepharmacovigilancesignal-detection
11.5 match 20 stars 5.95 score 5 scriptsbioc
DepInfeR:Inferring tumor-specific cancer dependencies through integrating ex-vivo drug response assays and drug-protein profiling
DepInfeR integrates two experimentally accessible input data matrices: the drug sensitivity profiles of cancer cell lines or primary tumors ex-vivo (X), and the drug affinities of a set of proteins (Y), to infer a matrix of molecular protein dependencies of the cancers (ß). DepInfeR deconvolutes the protein inhibition effect on the viability phenotype by using regularized multivariate linear regression. It assigns a “dependence coefficient” to each protein and each sample, and therefore could be used to gain a causal and accurate understanding of functional consequences of genomic aberrations in a heterogeneous disease, as well as to guide the choice of pharmacological intervention for a specific cancer type, sub-type, or an individual patient. For more information, please read out preprint on bioRxiv: https://doi.org/10.1101/2022.01.11.475864.
Maintained by Junyan Lu. Last updated 5 months ago.
softwareregressionpharmacogeneticspharmacogenomicsfunctionalgenomics
14.6 match 1 stars 4.36 score 23 scripts
kjhealy
gssrdoc:Document General Social Survey Variable
The General Social Survey (GSS) is a long-running, mostly annual survey of US households. It is administered by the National Opinion Research Center (NORC). This package contains the a tibble with information on the survey variables, together with every variable documented as an R help page. For more information on the GSS see \url{http://gss.norc.org}.
Maintained by Kieran Healy. Last updated 11 months ago.
27.5 match 2.28 score 38 scriptsbioc
multiMiR:Integration of multiple microRNA-target databases with their disease and drug associations
A collection of microRNAs/targets from external resources, including validated microRNA-target databases (miRecords, miRTarBase and TarBase), predicted microRNA-target databases (DIANA-microT, ElMMo, MicroCosm, miRanda, miRDB, PicTar, PITA and TargetScan) and microRNA-disease/drug databases (miR2Disease, Pharmaco-miR VerSe and PhenomiR).
Maintained by Spencer Mahaffey. Last updated 5 months ago.
mirnadatahomo_sapiens_datamus_musculus_datarattus_norvegicus_dataorganismdatamicrorna-sequencesql
7.3 match 20 stars 8.45 score 141 scriptsbioc
gDRutils:A package with helper functions for processing drug response data
This package contains utility functions used throughout the gDR platform to fit data, manipulate data, and convert and validate data structures. This package also has the necessary default constants for gDR platform. Many of the functions are utilized by the gDRcore package.
Maintained by Arkadiusz Gladki. Last updated 4 days ago.
8.3 match 2 stars 7.40 score 3 scripts 3 dependents
blakelanglais
ProAE:PRO-CTCAE Scoring, Analysis, and Graphical Tools
A collection of tools to facilitate standardized analysis and graphical procedures when using the National Cancer Institute’s Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) and other PRO measurements.
Maintained by Blake Langlais. Last updated 5 months ago.
17.1 match 3.48 score 9 scriptsbioc
drugTargetInteractions:Drug-Target Interactions
Provides utilities for identifying drug-target interactions for sets of small molecule or gene/protein identifiers. The required drug-target interaction information is obained from a local SQLite instance of the ChEMBL database. ChEMBL has been chosen for this purpose, because it provides one of the most comprehensive and best annotatated knowledge resources for drug-target information available in the public domain.
Maintained by Thomas Girke. Last updated 5 months ago.
cheminformaticsbiomedicalinformaticspharmacogeneticspharmacogenomicsproteomicsmetabolomics
13.5 match 1 stars 4.34 score 11 scripts
robjhyndman
fpp2:Data for "Forecasting: Principles and Practice" (2nd Edition)
All data sets required for the examples and exercises in the book "Forecasting: principles and practice" (2nd ed, 2018) by Rob J Hyndman and George Athanasopoulos <https://otexts.com/fpp2/>. All packages required to run the examples are also loaded.
Maintained by Rob Hyndman. Last updated 2 years ago.
6.8 match 106 stars 8.57 score 1.8k scripts 1 dependents
openbiox
UCSCXenaShiny:Interactive Analysis of UCSC Xena Data
Provides functions and a Shiny application for downloading, analyzing and visualizing datasets from UCSC Xena (<http://xena.ucsc.edu/>), which is a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others.
Maintained by Shixiang Wang. Last updated 4 months ago.
cancer-datasetshiny-appsucsc-xena
6.7 match 96 stars 8.54 score 35 scriptsbioc
CoreGx:Classes and Functions to Serve as the Basis for Other 'Gx' Packages
A collection of functions and classes which serve as the foundation for our lab's suite of R packages, such as 'PharmacoGx' and 'RadioGx'. This package was created to abstract shared functionality from other lab package releases to increase ease of maintainability and reduce code repetition in current and future 'Gx' suite programs. Major features include a 'CoreSet' class, from which 'RadioSet' and 'PharmacoSet' are derived, along with get and set methods for each respective slot. Additional functions related to fitting and plotting dose response curves, quantifying statistical correlation and calculating area under the curve (AUC) or survival fraction (SF) are included. For more details please see the included documentation, as well as: Smirnov, P., Safikhani, Z., El-Hachem, N., Wang, D., She, A., Olsen, C., Freeman, M., Selby, H., Gendoo, D., Grossman, P., Beck, A., Aerts, H., Lupien, M., Goldenberg, A. (2015) <doi:10.1093/bioinformatics/btv723>. Manem, V., Labie, M., Smirnov, P., Kofia, V., Freeman, M., Koritzinksy, M., Abazeed, M., Haibe-Kains, B., Bratman, S. (2018) <doi:10.1101/449793>.
Maintained by Benjamin Haibe-Kains. Last updated 5 months ago.
softwarepharmacogenomicsclassificationsurvival
8.7 match 6.53 score 63 scripts 6 dependents
kenaho1
asbio:A Collection of Statistical Tools for Biologists
Contains functions from: Aho, K. (2014) Foundational and Applied Statistics for Biologists using R. CRC/Taylor and Francis, Boca Raton, FL, ISBN: 978-1-4398-7338-0.
Maintained by Ken Aho. Last updated 2 months ago.
7.2 match 5 stars 7.32 score 310 scripts 3 dependentsbioc
ToxicoGx:Analysis of Large-Scale Toxico-Genomic Data
Contains a set of functions to perform large-scale analysis of toxicogenomic data, providing a standardized data structure to hold information relevant to annotation, visualization and statistical analysis of toxicogenomic data.
Maintained by Benjamin Haibe-Kains. Last updated 5 months ago.
geneexpressionpharmacogeneticspharmacogenomicssoftware
12.0 match 4.36 score 23 scriptshanjunwei-lab
DTSEA:Drug Target Set Enrichment Analysis
It is a novel tool used to identify the candidate drugs against a particular disease based on the drug target set enrichment analysis. It assumes the most effective drugs are those with a closer affinity in the protein-protein interaction network to the specified disease. (See Gómez-Carballa et al. (2022) <doi: 10.1016/j.envres.2022.112890> and Feng et al. (2022) <doi: 10.7150/ijms.67815> for disease expression profiles; see Wishart et al. (2018) <doi: 10.1093/nar/gkx1037> and Gaulton et al. (2017) <doi: 10.1093/nar/gkw1074> for drug target information; see Kanehisa et al. (2021) <doi: 10.1093/nar/gkaa970> for the details of KEGG database.)
Maintained by Junwei Han. Last updated 2 years ago.
12.1 match 4.32 score 42 scripts
pharmaverse
sdtmchecks:Data Quality Checks for Study Data Tabulation Model (SDTM) Datasets
A series of checks to identify common issues in Study Data Tabulation Model (SDTM) datasets. These checks are intended to be generalizable, actionable, and meaningful for analysis.
Maintained by Will Harris. Last updated 3 months ago.
6.7 match 21 stars 7.66 score 15 scriptsbioc
Xeva:Analysis of patient-derived xenograft (PDX) data
The Xeva package provides efficient and powerful functions for patient-drived xenograft (PDX) based pharmacogenomic data analysis. This package contains a set of functions to perform analysis of patient-derived xenograft data. This package was developed by the BHKLab, for further information please see our documentation.
Maintained by Benjamin Haibe-Kains. Last updated 4 months ago.
geneexpressionpharmacogeneticspharmacogenomicssoftwareclassification
8.0 match 11 stars 6.35 score 17 scripts
rkoenker
quantreg:Quantile Regression
Estimation and inference methods for models for conditional quantile functions: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also now included. See Koenker, R. (2005) Quantile Regression, Cambridge U. Press, <doi:10.1017/CBO9780511754098> and Koenker, R. et al. (2017) Handbook of Quantile Regression, CRC Press, <doi:10.1201/9781315120256>.
Maintained by Roger Koenker. Last updated 6 days ago.
3.6 match 18 stars 13.93 score 2.6k scripts 1.5k dependentsbioc
maftools:Summarize, Analyze and Visualize MAF Files
Analyze and visualize Mutation Annotation Format (MAF) files from large scale sequencing studies. This package provides various functions to perform most commonly used analyses in cancer genomics and to create feature rich customizable visualzations with minimal effort.
Maintained by Anand Mayakonda. Last updated 5 months ago.
datarepresentationdnaseqvisualizationdrivermutationvariantannotationfeatureextractionclassificationsomaticmutationsequencingfunctionalgenomicssurvivalbioinformaticscancer-genome-atlascancer-genomicsgenomicsmaf-filestcgacurlbzip2xz-utilszlib
3.3 match 459 stars 14.63 score 948 scripts 18 dependents
ropensci
dbparser:Drugs Databases Parser
This tool is for parsing public drug databases such as 'DrugBank' XML database <https://go.drugbank.com/>. The parsed data are then returned in a proper 'R' object called 'dvobject'.
Maintained by Mohammed Ali. Last updated 8 months ago.
5.7 match 59 stars 8.47 score 210 scriptsbioc
gDRimport:Package for handling the import of dose-response data
The package is a part of the gDR suite. It helps to prepare raw drug response data for downstream processing. It mainly contains helper functions for importing/loading/validating dose-response data provided in different file formats.
Maintained by Arkadiusz Gladki. Last updated 25 days ago.
softwareinfrastructuredataimport
6.3 match 2 stars 7.16 score 5 scripts 1 dependents
centerforstatistics-ugent
xnet:Two-Step Kernel Ridge Regression for Network Predictions
Fit a two-step kernel ridge regression model for predicting edges in networks, and carry out cross-validation using shortcuts for swift and accurate performance assessment (Stock et al, 2018 <doi:10.1093/bib/bby095> ).
Maintained by Joris Meys. Last updated 4 years ago.
8.5 match 11 stars 5.30 score 12 scriptshanjunwei-lab
DrugSim2DR:Predict Drug Functional Similarity to Drug Repurposing
A systematic biology tool was developed to repurpose drugs via a drug-drug functional similarity network. 'DrugSim2DR' first predict drug-drug functional similarity in the context of specific disease, and then using the similarity constructed a weighted drug similarity network. Finally, it used a network propagation algorithm on the network to identify drugs with significant target abnormalities as candidate drugs.
Maintained by Junwei Han. Last updated 2 years ago.
11.2 match 2 stars 4.00 score 2 scripts
bxc147
Epi:Statistical Analysis in Epidemiology
Functions for demographic and epidemiological analysis in the Lexis diagram, i.e. register and cohort follow-up data. In particular representation, manipulation, rate estimation and simulation for multistate data - the Lexis suite of functions, which includes interfaces to 'mstate', 'etm' and 'cmprsk' packages. Contains functions for Age-Period-Cohort and Lee-Carter modeling and a function for interval censored data and some useful functions for tabulation and plotting, as well as a number of epidemiological data sets.
Maintained by Bendix Carstensen. Last updated 2 months ago.
4.5 match 4 stars 9.65 score 708 scripts 11 dependents
mrcieu
MRInstruments:Data sources for genetic instruments to be used in MR
Datasets of eQTLs, GWAS catalogs, etc.
Maintained by Gibran Hemani. Last updated 5 years ago.
8.0 match 44 stars 5.15 score 212 scripts
r-forge
carData:Companion to Applied Regression Data Sets
Datasets to Accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage (2019).
Maintained by John Fox. Last updated 5 months ago.
3.3 match 12.41 score 944 scripts 919 dependents
cran
MASS:Support Functions and Datasets for Venables and Ripley's MASS
Functions and datasets to support Venables and Ripley, "Modern Applied Statistics with S" (4th edition, 2002).
Maintained by Brian Ripley. Last updated 16 days ago.
3.8 match 19 stars 10.53 score 11k dependentslightbluetitan
timeSeriesDataSets:Time Series Data Sets
Provides a diverse collection of time series datasets spanning various fields such as economics, finance, energy, healthcare, and more. Designed to support time series analysis in R by offering datasets from multiple disciplines, making it a valuable resource for researchers and analysts.
Maintained by Renzo Caceres Rossi. Last updated 6 months ago.
6.8 match 10 stars 5.71 score 103 scripts
insightsengineering
chevron:Standard TLGs for Clinical Trials Reporting
Provide standard tables, listings, and graphs (TLGs) libraries used in clinical trials. This package implements a structure to reformat the data with 'dunlin', create reporting tables using 'rtables' and 'tern' with standardized input arguments to enable quick generation of standard outputs. In addition, it also provides comprehensive data checks and script generation functionality.
Maintained by Joe Zhu. Last updated 24 days ago.
clinical-trialsgraphslistingsnestreportingtables
4.7 match 12 stars 8.24 score 12 scripts
statmanrobin
Stat2Data:Datasets for Stat2
Datasets for the textbook Stat2: Modeling with Regression and ANOVA (second edition). The package also includes data for the first edition, Stat2: Building Models for a World of Data and a few functions for plotting diagnostics.
Maintained by Robin Lock. Last updated 6 years ago.
7.8 match 5 stars 4.94 score 544 scripts
rafromb
SynergyLMM:Statistical Framework for in Vivo Drug Combination Studies
A framework for evaluating drug combination effects in preclinical in vivo studies. 'SynergyLMM' provides functions to analyze longitudinal tumor growth experiments using linear mixed-effects models, perform time-dependent analyses of synergy and antagonism, evaluate model diagnostics and performance, and assess both post-hoc and a priori statistical power. The calculation of drug combination synergy follows the statistical framework provided by Demidenko and Miller (2019, <doi:10.1371/journal.pone.0224137>). The implementation and analysis of linear mixed-effect models is based on the methods described by Pinheiro and Bates (2000, <doi:10.1007/b98882>), and Gałecki and Burzykowski (2013, <doi:10.1007/978-1-4614-3900-4>).
Maintained by Rafael Romero-Becerra. Last updated 1 months ago.
7.0 match 2 stars 5.32 score
gasparrini
dlnm:Distributed Lag Non-Linear Models
Collection of functions for distributed lag linear and non-linear models.
Maintained by Antonio Gasparrini. Last updated 3 years ago.
3.5 match 77 stars 10.30 score 392 scripts 6 dependents
merck
r2rtf:Easily Create Production-Ready Rich Text Format (RTF) Tables and Figures
Create production-ready Rich Text Format (RTF) tables and figures with flexible format.
Maintained by Benjamin Wang. Last updated 6 days ago.
3.3 match 78 stars 10.82 score 171 scripts 10 dependents
levenc
posologyr:Individual Dose Optimization using Population Pharmacokinetics
Personalize drug regimens using individual pharmacokinetic (PK) and pharmacokinetic-pharmacodynamic (PK-PD) profiles. By combining therapeutic drug monitoring (TDM) data with a population model, 'posologyr' offers accurate posterior estimates and helps compute optimal individualized dosing regimens. The empirical Bayes estimates are computed following the method described by Kang et al. (2012) <doi:10.4196/kjpp.2012.16.2.97>.
Maintained by Cyril Leven. Last updated 6 days ago.
bayesianmodel-informed-precision-dosingpharmacokineticsprecision-medicinetherapeutic-drug-monitoring
7.4 match 12 stars 4.68 score 9 scripts
dmphillippo
multinma:Bayesian Network Meta-Analysis of Individual and Aggregate Data
Network meta-analysis and network meta-regression models for aggregate data, individual patient data, and mixtures of both individual and aggregate data using multilevel network meta-regression as described by Phillippo et al. (2020) <doi:10.1111/rssa.12579>. Models are estimated in a Bayesian framework using 'Stan'.
Maintained by David M. Phillippo. Last updated 2 days ago.
3.6 match 35 stars 9.11 score 163 scripts
selbosh
doseminer:Extract Drug Dosages from Free-Text Prescriptions
Utilities for converting unstructured electronic prescribing instructions into structured medication data. Extracts drug dose, units, daily dosing frequency and intervals from English-language prescriptions. Based on Karystianis et al. (2015) <doi:10.1186/s12911-016-0255-x>.
Maintained by David Selby. Last updated 2 years ago.
6.1 match 4 stars 5.12 score 11 scripts 1 dependents
ahgroup
DSAIRM:Dynamical Systems Approach to Immune Response Modeling
Simulation models (apps) of various within-host immune response scenarios. The purpose of the package is to help individuals learn about within-host infection and immune response modeling from a dynamical systems perspective. All apps include explanations of the underlying models and instructions on what to do with the models.
Maintained by Andreas Handel. Last updated 8 months ago.
5.0 match 34 stars 6.19 score 23 scriptsgraemeleehickey
joineRML:Joint Modelling of Multivariate Longitudinal Data and Time-to-Event Outcomes
Fits the joint model proposed by Henderson and colleagues (2000) <doi:10.1093/biostatistics/1.4.465>, but extended to the case of multiple continuous longitudinal measures. The time-to-event data is modelled using a Cox proportional hazards regression model with time-varying covariates. The multiple longitudinal outcomes are modelled using a multivariate version of the Laird and Ware linear mixed model. The association is captured by a multivariate latent Gaussian process. The model is estimated using a Monte Carlo Expectation Maximization algorithm. This project was funded by the Medical Research Council (Grant number MR/M013227/1).
Maintained by Graeme L. Hickey. Last updated 1 months ago.
armadillobiostatisticsclinical-trialscoxdynamicjoint-modelslongitudinal-datamultivariate-analysismultivariate-datamultivariate-longitudinal-datapredictionrcppregression-modelsstatisticssurvivalopenblascppopenmp
3.4 match 30 stars 8.93 score 146 scripts 1 dependents
yboulag
cTOST:Finite Sample Correction of the Two One-Sided Tests in the Univariate Framework
A system containing easy-to-use tools to compute the bioequivalence assessment in the univariate framework using the methods proposed in Boulaguiem et al. (2023) <doi:10.1101/2023.03.11.532179>.
Maintained by Younes Boulaguiem. Last updated 1 months ago.
bioequivalenceequivalencehighly-variable-drugsstatistics
6.7 match 4.48 score 4 scriptsdarwin-eu
CodelistGenerator:Identify Relevant Clinical Codes and Evaluate Their Use
Generate a candidate code list for the Observational Medical Outcomes Partnership (OMOP) common data model based on string matching. For a given search strategy, a candidate code list will be returned.
Maintained by Edward Burn. Last updated 25 days ago.
3.0 match 13 stars 9.87 score 165 scripts 4 dependents
dongwenluo
predictmeans:Predicted Means for Linear and Semiparametric Models
Providing functions to diagnose and make inferences from various linear models, such as those obtained from 'aov', 'lm', 'glm', 'gls', 'lme', 'lmer', 'glmmTMB' and 'semireg'. Inferences include predicted means and standard errors, contrasts, multiple comparisons, permutation tests, adjusted R-square and graphs.
Maintained by Dongwen Luo. Last updated 11 months ago.
4.5 match 2 stars 6.26 score 152 scripts 2 dependents
nickch-k
causaldata:Example Data Sets for Causal Inference Textbooks
Example data sets to run the example problems from causal inference textbooks. Currently, contains data sets for Huntington-Klein, Nick (2021) "The Effect" <https://theeffectbook.net>, first and second edition, Cunningham, Scott (2021, ISBN-13: 978-0-300-25168-5) "Causal Inference: The Mixtape", and Hernán, Miguel and James Robins (2020) "Causal Inference: What If" <https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/>.
Maintained by Nick Huntington-Klein. Last updated 4 months ago.
3.4 match 136 stars 7.43 score 144 scripts 1 dependents
benkeser
nlpred:Estimators of Non-Linear Cross-Validated Risks Optimized for Small Samples
Methods for obtaining improved estimates of non-linear cross-validated risks are obtained using targeted minimum loss-based estimation, estimating equations, and one-step estimation (Benkeser, Petersen, van der Laan (2019), <doi:10.1080/01621459.2019.1668794>). Cross-validated area under the receiver operating characteristics curve (LeDell, Petersen, van der Laan (2015), <doi:10.1214/15-EJS1035>) and other metrics are included.
Maintained by David Benkeser. Last updated 3 years ago.
auccross-validationestimating-equationsmachine-learningtmle
6.0 match 3 stars 4.18 score 6 scripts
mattcefalu
twang:Toolkit for Weighting and Analysis of Nonequivalent Groups
Provides functions for propensity score estimating and weighting, nonresponse weighting, and diagnosis of the weights.
Maintained by Matthew Cefalu. Last updated 3 years ago.
3.6 match 6 stars 6.83 score 169 scripts 10 dependents
belayb
drugprepr:Prepare Electronic Prescription Record Data to Estimate Drug Exposure
Prepare prescription data (such as from the Clinical Practice Research Datalink) into an analysis-ready format, with start and stop dates for each patient's prescriptions. Based on Pye et al (2018) <doi:10.1002/pds.4440>.
Maintained by David Selby. Last updated 3 years ago.
6.4 match 1 stars 3.70 score 3 scripts
weberse2
OncoBayes2:Bayesian Logistic Regression for Oncology Dose-Escalation Trials
Bayesian logistic regression model with optional EXchangeability-NonEXchangeability parameter modelling for flexible borrowing from historical or concurrent data-sources. The safety model can guide dose-escalation decisions for adaptive oncology Phase I dose-escalation trials which involve an arbitrary number of drugs. Please refer to Neuenschwander et al. (2008) <doi:10.1002/sim.3230> and Neuenschwander et al. (2016) <doi:10.1080/19466315.2016.1174149> for details on the methodology.
Maintained by Sebastian Weber. Last updated 15 days ago.
10.9 match 2.18 score 15 scripts
mohmedsoudy
DFD:Extract Drugs from Differential Expression Data
Extract Drugs from Differential Expression Data using the Connectivity Map (CMAP) Approach and Library of Integrated Network-Based Cellular Signatures (LINCS) Database.
Maintained by Mohamed Soudy. Last updated 1 years ago.
8.7 match 1 stars 2.70 score 1 scripts
stats-uoa
s20x:Functions for University of Auckland Course STATS 201/208 Data Analysis
A set of functions used in teaching STATS 201/208 Data Analysis at the University of Auckland. The functions are designed to make parts of R more accessible to a large undergraduate population who are mostly not statistics majors.
Maintained by James Curran. Last updated 2 years ago.
3.6 match 3 stars 6.40 score 211 scripts 3 dependents
markheckmann
OpenRepGrid:Tools to Analyze Repertory Grid Data
Analyze repertory grids, a qualitative-quantitative data collection technique devised by George A. Kelly in the 1950s. Today, grids are used across various domains ranging from clinical psychology to marketing. The package contains functions to quantitatively analyze and visualize repertory grid data (e.g. 'Fransella', 'Bell', & 'Bannister', 2004, ISBN: 978-0-470-09080-0). The package is part of the The package is part of the <https://openrepgrid.org/> project.
Maintained by Mark Heckmann. Last updated 14 days ago.
3.3 match 19 stars 6.69 score 156 scripts
mathewchamberlain
SignacX:Cell Type Identification and Discovery from Single Cell Gene Expression Data
An implementation of neural networks trained with flow-sorted gene expression data to classify cellular phenotypes in single cell RNA-sequencing data. See Chamberlain M et al. (2021) <doi:10.1101/2021.02.01.429207> for more details.
Maintained by Mathew Chamberlain. Last updated 2 years ago.
cellular-phenotypesseuratsingle-cell-rna-seq
3.4 match 24 stars 6.46 score 34 scriptsbioc
DeepPINCS:Protein Interactions and Networks with Compounds based on Sequences using Deep Learning
The identification of novel compound-protein interaction (CPI) is important in drug discovery. Revealing unknown compound-protein interactions is useful to design a new drug for a target protein by screening candidate compounds. The accurate CPI prediction assists in effective drug discovery process. To identify potential CPI effectively, prediction methods based on machine learning and deep learning have been developed. Data for sequences are provided as discrete symbolic data. In the data, compounds are represented as SMILES (simplified molecular-input line-entry system) strings and proteins are sequences in which the characters are amino acids. The outcome is defined as a variable that indicates how strong two molecules interact with each other or whether there is an interaction between them. In this package, a deep-learning based model that takes only sequence information of both compounds and proteins as input and the outcome as output is used to predict CPI. The model is implemented by using compound and protein encoders with useful features. The CPI model also supports other modeling tasks, including protein-protein interaction (PPI), chemical-chemical interaction (CCI), or single compounds and proteins. Although the model is designed for proteins, DNA and RNA can be used if they are represented as sequences.
Maintained by Dongmin Jung. Last updated 5 months ago.
softwarenetworkgraphandnetworkneuralnetworkopenjdk
4.5 match 4.78 score 4 scripts 2 dependents
sthomas522
hmclearn:Fit Statistical Models Using Hamiltonian Monte Carlo
Provide users with a framework to learn the intricacies of the Hamiltonian Monte Carlo algorithm with hands-on experience by tuning and fitting their own models. All of the code is written in R. Theoretical references are listed below:. Neal, Radford (2011) "Handbook of Markov Chain Monte Carlo" ISBN: 978-1420079418, Betancourt, Michael (2017) "A Conceptual Introduction to Hamiltonian Monte Carlo" <arXiv:1701.02434>, Thomas, S., Tu, W. (2020) "Learning Hamiltonian Monte Carlo in R" <arXiv:2006.16194>, Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013) "Bayesian Data Analysis" ISBN: 978-1439840955, Agresti, Alan (2015) "Foundations of Linear and Generalized Linear Models ISBN: 978-1118730034, Pinheiro, J., Bates, D. (2006) "Mixed-effects Models in S and S-Plus" ISBN: 978-1441903174.
Maintained by Samuel Thomas. Last updated 4 years ago.
3.8 match 11 stars 5.64 score 16 scripts
bips-hb
expard:Drug EXPosures and ADRs
An R package for fitting complex drug exposure and adverse drug reaction (ADR) relationships
Maintained by Louis Dijkstra. Last updated 1 months ago.
11.6 match 1 stars 1.81 score 13 scriptshanjunwei-lab
DRviaSPCN:Drug Repurposing in Cancer via a Subpathway Crosstalk Network
A systematic biology tool was developed to repurpose drugs via a subpathway crosstalk network. The operation modes include 1) calculating centrality scores of SPs in the context of gene expression data to reflect the influence of SP crosstalk, 2) evaluating drug-disease reverse association based on disease- and drug-induced SPs weighted by the SP crosstalk, 3) identifying cancer candidate drugs through perturbation analysis. There are also several functions used to visualize the results.
Maintained by Junwei Han. Last updated 2 months ago.
10.4 match 2.00 score 5 scripts
yuanlonghu
immcp:Poly-Pharmacology Toolkit for Traditional Chinese Medicine Research
Toolkit for Poly-pharmacology Research of Traditional Chinese Medicine. Based on the biological descriptors and drug-disease interaction networks, it can analyze the potential poly-pharmacological mechanisms of Traditional Chinese Medicine and be used for drug-repositioning in Traditional Chinese Medicine.
Maintained by Yuanlong Hu. Last updated 2 years ago.
network-pharmacologypolypharmacologytraditional-chinese-medicine
4.6 match 5 stars 4.40 score 2 scripts
lihualei71
adaptMT:Adaptive P-Value Thresholding for Multiple Hypothesis Testing with Side Information
Implementation of adaptive p-value thresholding (AdaPT), including both a framework that allows the user to specify any algorithm to learn local false discovery rate and a pool of convenient functions that implement specific algorithms. See Lei, Lihua and Fithian, William (2016) <arXiv:1609.06035>.
Maintained by Lihua Lei. Last updated 4 years ago.
3.8 match 9 stars 5.33 score 48 scripts
revelle
psychTools:Tools to Accompany the 'psych' Package for Psychological Research
Support functions, data sets, and vignettes for the 'psych' package. Contains several of the biggest data sets for the 'psych' package as well as four vignettes. A few helper functions for file manipulation are included as well. For more information, see the <https://personality-project.org/r/> web page.
Maintained by William Revelle. Last updated 12 months ago.
3.2 match 5.89 score 178 scripts 5 dependents
brechtdv
cystiSim:Agent-Based Model for Taenia_solium Transmission and Control
The cystiSim package provides an agent-based model for Taenia solium transmission and control. cystiSim was developed within the framework of CYSTINET, the European Network on taeniosis/cysticercosis, COST ACTION TD1302.
Maintained by Brecht Devleesschauwer. Last updated 5 years ago.
5.3 match 3.54 score 2 scriptslightbluetitan
crimedatasets:A Comprehensive Collection of Crime-Related Datasets
A comprehensive collection of datasets exclusively focused on crimes, criminal activities, and related topics. This package serves as a valuable resource for researchers, analysts, and students interested in crime analysis, criminology, social and economic studies related to criminal behavior. Datasets span global and local contexts, with a mix of tabular and spatial data.
Maintained by Renzo Caceres Rossi. Last updated 3 months ago.
3.8 match 8 stars 4.90 score 3 scripts
ellessenne
KMunicate:KMunicate-Style Kaplan–Meier Plots
Produce Kaplan–Meier plots in the style recommended following the KMunicate study by Morris et al. (2019) <doi:10.1136/bmjopen-2019-030215>. The KMunicate style consists of Kaplan-Meier curves with confidence intervals to quantify uncertainty and an extended risk table (per treatment arm) depicting the number of study subjects at risk, events, and censored observations over time. The resulting plots are built using 'ggplot2' and can be further customised to a certain extent, including themes, fonts, and colour scales.
Maintained by Alessandro Gasparini. Last updated 10 months ago.
3.8 match 7 stars 4.89 score 11 scripts
disohda
DiscreteDatasets:Example Data Sets for Use with Discrete Statistical Tests
Provides several data sets for use with discrete statistical tests and discrete multiple testing procedures. Some of them are also available as a four-column version, so that each row represents a 2x2 table.
Maintained by Florian Junge. Last updated 2 months ago.
5.1 match 3.56 score 4 scripts 3 dependents
ubclxing
MTPS:Multi-Task Prediction using Stacking Algorithms
Simultaneous multiple outcomes prediction based on revised stacking algorithms, which enables the integration of information from predictions of individual models. An implementation of methodologies proposed in our paper: Li Xing, Mary L Lesperance, Xuekui Zhang. (2019) Bioinformatics, "Simultaneous prediction of multiple outcomes using revised stacking algorithms" <doi:10.1093/bioinformatics/btz531>.
Maintained by Li Xing. Last updated 2 years ago.
5.6 match 3.18 score 8 scripts 1 dependents
c7rishi
pvLRT:Likelihood Ratio Test-Based Approaches to Pharmacovigilance
A suite of likelihood ratio test based methods to use in pharmacovigilance. Contains various testing and post-processing functions.
Maintained by Saptarshi Chakraborty. Last updated 2 years ago.
6.6 match 1 stars 2.70 score 9 scripts
knudson1
glmm:Generalized Linear Mixed Models via Monte Carlo Likelihood Approximation
Approximates the likelihood of a generalized linear mixed model using Monte Carlo likelihood approximation. Then maximizes the likelihood approximation to return maximum likelihood estimates, observed Fisher information, and other model information.
Maintained by Christina Knudson. Last updated 6 months ago.
3.8 match 2 stars 4.64 score 216 scripts
entjos
TreeMineR:Tree-Based Scan Statistics
Implementation of unconditional Bernoulli Scan Statistic developed by Kulldorff et al. (2003) <doi:10.1111/1541-0420.00039> for hierarchical tree structures. Tree-based Scan Statistics are an exploratory method to identify event clusters across the space of a hierarchical tree.
Maintained by Joshua P. Entrop. Last updated 7 months ago.
5.0 match 3.40 score 2 scriptsbioc
ccmap:Combination Connectivity Mapping
Finds drugs and drug combinations that are predicted to reverse or mimic gene expression signatures. These drugs might reverse diseases or mimic healthy lifestyles.
Maintained by Alex Pickering. Last updated 5 months ago.
geneexpressiontranscriptionmicroarraydifferentialexpression
5.7 match 3.00 score 5 scriptsbioc
octad:Open Cancer TherApeutic Discovery (OCTAD)
OCTAD provides a platform for virtually screening compounds targeting precise cancer patient groups. The essential idea is to identify drugs that reverse the gene expression signature of disease by tamping down over-expressed genes and stimulating weakly expressed ones. The package offers deep-learning based reference tissue selection, disease gene expression signature creation, pathway enrichment analysis, drug reversal potency scoring, cancer cell line selection, drug enrichment analysis and in silico hit validation. It currently covers ~20,000 patient tissue samples covering 50 cancer types, and expression profiles for ~12,000 distinct compounds.
Maintained by E. Chekalin. Last updated 5 months ago.
classificationgeneexpressionpharmacogeneticspharmacogenomicssoftwaregenesetenrichment
4.2 match 4.00 score 4 scriptslightbluetitan
educationR:A Comprehensive Collection of Educational Datasets
Provides a comprehensive collection of datasets related to education, covering topics such as student performance, learning methods, test scores, absenteeism, and other educational metrics. This package is designed as a resource for educational researchers, data analysts, and statisticians to explore and analyze data in the field of education.
Maintained by Renzo Caceres Rossi. Last updated 3 months ago.
3.8 match 4 stars 4.30 score 3 scripts
mikejseo
bnma:Bayesian Network Meta-Analysis using 'JAGS'
Network meta-analyses using Bayesian framework following Dias et al. (2013) <DOI:10.1177/0272989X12458724>. Based on the data input, creates prior, model file, and initial values needed to run models in 'rjags'. Able to handle binomial, normal and multinomial arm-level data. Can handle multi-arm trials and includes methods to incorporate covariate and baseline risk effects. Includes standard diagnostics and visualization tools to evaluate the results.
Maintained by Michael Seo. Last updated 1 years ago.
3.5 match 7 stars 4.54 score 7 scripts
sanfordweisberg
alr4:Data to Accompany Applied Linear Regression 4th Edition
Datasets to Accompany S. Weisberg (2014, ISBN: 978-1-118-38608-8), "Applied Linear Regression," 4th edition. Many data files in this package are included in the `alr3` package as well, so only one of them should be used.
Maintained by Sanford Weisberg. Last updated 7 years ago.
4.5 match 1 stars 3.45 score 306 scriptscran
smoothy:Automatic Estimation of the Most Likely Drug Combination using Smooth Algorithm
A flexible moving average algorithm for modeling drug exposure in pharmacoepidemiology studies as presented in the article: Ouchi, D., Giner-Soriano, M., Gómez-Lumbreras, A., Vedia Urgell, C.,Torres, F., & Morros, R. (2022). "Automatic Estimation of the Most Likely Drug Combination in Electronic Health Records Using the Smooth Algorithm : Development and Validation Study." JMIR medical informatics, 10(11), e37976. <doi:10.2196/37976>.
Maintained by Dan Ouchi. Last updated 2 years ago.
7.6 match 2.04 score 11 scripts
kwkim89
SizeEstimation:Estimating the Sizes of Populations at Risk of HIV Infection from Multiple Data Sources Using a Bayesian Hierarchical Model
This function develops an algorithm for presenting a Bayesian hierarchical model for estimating the sizes of local and national drug injected populations in Bangladesh. The model incorporates multiple commonly used data sources including mapping data, surveys, interventions, capture-recapture data, estimates or guesstimates from organizations, and expert opinion.
Maintained by Kyongwon Kim. Last updated 6 years ago.
5.6 match 2.70 score 1 scriptsinsightsengineering
random.cdisc.data:Create Random ADaM Datasets
A set of functions to create random Analysis Data Model (ADaM) datasets and cached dataset. ADaM dataset specifications are described by the Clinical Data Interchange Standards Consortium (CDISC) Analysis Data Model Team.
Maintained by Joe Zhu. Last updated 5 months ago.
1.8 match 33 stars 8.60 score 52 scripts
calvintchi
hierBipartite:Bipartite Graph-Based Hierarchical Clustering
Bipartite graph-based hierarchical clustering performs hierarchical clustering of groups of samples based on association patterns between two sets of variables. It is developed for pharmacogenomic datasets and datasets sharing the same data structure. In the context of pharmacogenomic datasets, the samples are cell lines, and the two sets of variables are typically expression levels and drug sensitivity values. For this method, sparse canonical correlation analysis from Lee, W., Lee, D., Lee, Y. and Pawitan, Y. (2011) <doi:10.2202/1544-6115.1638> is first applied to extract association patterns for each group of samples. Then, a nuclear norm-based dissimilarity measure is used to construct a dissimilarity matrix between groups based on the extracted associations. Finally, hierarchical clustering is applied.
Maintained by Calvin Chi. Last updated 4 years ago.
3.9 match 1 stars 3.70 score 4 scripts
insightrx
clinPK:Clinical Pharmacokinetics Toolkit
Provides equations commonly used in clinical pharmacokinetics and clinical pharmacology, such as equations for dose individualization, compartmental pharmacokinetics, drug exposure, anthropomorphic calculations, clinical chemistry, and conversion of common clinical parameters. Where possible and relevant, it provides multiple published and peer-reviewed equations within the respective R function.
Maintained by Ron Keizer. Last updated 2 months ago.
clinical-researchpharmacokinetics
2.1 match 30 stars 6.72 score 55 scriptscran
emcAdr:Evolutionary Version of the Metropolis-Hastings Algorithm
Provides computational methods for detecting adverse high-order drug interactions from individual case safety reports using statistical techniques, allowing the exploration of higher-order interactions among drug cocktails.
Maintained by Jules Bangard. Last updated 17 days ago.
5.2 match 2.70 scorebioc
pogos:PharmacOGenomics Ontology Support
Provide simple utilities for querying bhklab PharmacoDB, modeling API outputs, and integrating to cell and compound ontologies.
Maintained by VJ Carey. Last updated 2 months ago.
pharmacogenomicspooledscreensimmunooncology
3.3 match 4.30 score 10 scripts
ocheab
FormulR:Comprehensive Tools for Drug Formulation Analysis and Visualization
This presents a comprehensive set of tools for the analysis and visualization of drug formulation data. It includes functions for statistical analysis, regression modeling, hypothesis testing, and comparative analysis to assess the impact of formulation parameters on drug release and other critical attributes. Additionally, the package offers a variety of data visualization functions, such as scatterplots, histograms, and boxplots, to facilitate the interpretation of formulation data. With its focus on usability and efficiency, this package aims to streamline the drug formulation process and aid researchers in making informed decisions during formulation design and optimization.
Maintained by Oche Ambrose George. Last updated 12 months ago.
7.0 match 2.00 score
nanne-aben
TANDEM:A Two-Stage Approach to Maximize Interpretability of Drug Response Models Based on Multiple Molecular Data Types
A two-stage regression method that can be used when various input data types are correlated, for example gene expression and methylation in drug response prediction. In the first stage it uses the upstream features (such as methylation) to predict the response variable (such as drug response), and in the second stage it uses the downstream features (such as gene expression) to predict the residuals of the first stage. In our manuscript (Aben et al., 2016, <doi:10.1093/bioinformatics/btw449>), we show that using TANDEM prevents the model from being dominated by gene expression and that the features selected by TANDEM are more interpretable.
Maintained by Nanne Aben. Last updated 5 years ago.
3.5 match 2 stars 4.00 score 9 scripts
friendly
twoway:Analysis of Two-Way Tables
Carries out analyses of two-way tables with one observation per cell, together with graphical displays for an additive fit and a diagnostic plot for removable 'non-additivity' via a power transformation of the response. It implements Tukey's Exploratory Data Analysis (1973) <ISBN: 978-0201076165> methods, including a 1-degree-of-freedom test for row*column 'non-additivity', linear in the row and column effects.
Maintained by Michael Friendly. Last updated 5 months ago.
anovaresidualstransformationstukey
3.5 match 4 stars 3.94 score 22 scriptscran
drc:Analysis of Dose-Response Curves
Analysis of dose-response data is made available through a suite of flexible and versatile model fitting and after-fitting functions.
Maintained by Christian Ritz. Last updated 9 years ago.
1.6 match 8 stars 8.39 score 1.4k scripts 28 dependents
sullivan0147
midas2:An Information Borrowing Drug-Combination Bayesian Platform Design(MIDAS-2)
An Information borrowing drug-combination Bayesian platform design with subgroup exploration and hierarchical constrain.
Maintained by Su Liwen. Last updated 3 years ago.
5.0 match 2.70 score
minoo-asty
CINNA:Deciphering Central Informative Nodes in Network Analysis
Computing, comparing, and demonstrating top informative centrality measures within a network. "CINNA: an R/CRAN package to decipher Central Informative Nodes in Network Analysis" provides a comprehensive overview of the package functionality Ashtiani et al. (2018) <doi:10.1093/bioinformatics/bty819>.
Maintained by Minoo Ashtiani. Last updated 2 years ago.
4.0 match 1 stars 3.29 score 98 scriptsstatmanrobin
Lock5Data:Datasets for "Statistics: UnLocking the Power of Data"
Datasets for the third edition of "Statistics: Unlocking the Power of Data" by Lock^5 Includes version of datasets from earlier editions.
Maintained by Robin Lock. Last updated 4 years ago.
4.5 match 2.90 score 322 scripts
openanalytics
BIGL:Biochemically Intuitive Generalized Loewe Model
Response surface methods for drug synergy analysis. Available methods include generalized and classical Loewe formulations as well as Highest Single Agent methodology. Response surfaces can be plotted in an interactive 3-D plot and formal statistical tests for presence of synergistic effects are available. Implemented methods and tests are described in the article "BIGL: Biochemically Intuitive Generalized Loewe null model for prediction of the expected combined effect compatible with partial agonism and antagonism" by Koen Van der Borght, Annelies Tourny, Rytis Bagdziunas, Olivier Thas, Maxim Nazarov, Heather Turner, Bie Verbist & Hugo Ceulemans (2017) <doi:10.1038/s41598-017-18068-5>.
Maintained by Maxim Nazarov. Last updated 2 years ago.
2.1 match 7 stars 6.02 score 37 scripts
syneoshealth
puzzle:Assembling Data Sets for Non-Linear Mixed Effects Modeling
To Simplify the time consuming and error prone task of assembling complex data sets for non-linear mixed effects modeling. Users are able to select from different absorption processes such as zero and first order, or a combination of both. Furthermore, data sets containing data from several entities, responses, and covariates can be simultaneously assembled.
Maintained by Mario Gonzalez Sales. Last updated 5 years ago.
3.5 match 3 stars 3.65 score 9 scripts
sriharitn
foretell:Projecting Customer Retention Based on Fader and Hardie Probability Models
Project Customer Retention based on Beta Geometric, Beta Discrete Weibull and Latent Class Discrete Weibull Models.This package is based on Fader and Hardie (2007) <doi:10.1002/dir.20074> and Fader and Hardie et al. (2018) <doi:10.1016/j.intmar.2018.01.002>.
Maintained by Srihari Jaganathan. Last updated 2 months ago.
3.4 match 5 stars 3.70 score 2 scripts
prabhanjan-tattar
gpk:100 Data Sets for Statistics Education
Collection of datasets as prepared by Profs. A.P. Gore, S.A. Paranjape, and M.B. Kulkarni of Department of Statistics, Poona University, India. With their permission, first letter of their names forms the name of this package, the package has been built by me and made available for the benefit of R users. This collection requires a rich class of models and can be a very useful building block for a beginner.
Maintained by Prabhanjan Tattar. Last updated 12 years ago.
7.5 match 1.69 score 49 scriptsahgroup
DSAIDE:Dynamical Systems Approach to Infectious Disease Epidemiology (Ecology/Evolution)
Exploration of simulation models (apps) of various infectious disease transmission dynamics scenarios. The purpose of the package is to help individuals learn about infectious disease epidemiology (ecology/evolution) from a dynamical systems perspective. All apps include explanations of the underlying models and instructions on what to do with the models.
Maintained by Andreas Handel. Last updated 1 years ago.
2.0 match 26 stars 6.30 score 22 scripts
ohdsi
omock:Creation of Mock Observational Medical Outcomes Partnership Common Data Model
Creates mock data for testing and package development for the Observational Medical Outcomes Partnership common data model. The package offers functions crafted with pipeline-friendly implementation, enabling users to effortlessly include only the necessary tables for their testing needs.
Maintained by Mike Du. Last updated 1 months ago.
1.7 match 2 stars 7.44 score 45 scripts 1 dependents
hputter
icpack:Survival Analysis of Interval-Censored Data
Survival analysis of interval-censored data with proportional hazards, and an explicit smooth estimate of the baseline log-hazard with P-splines.
Maintained by Hein Putter. Last updated 9 months ago.
4.9 match 2.48 scoremrcieu
epigraphdb:Interface Package for the 'EpiGraphDB' Platform
The interface package to access data from the 'EpiGraphDB' <https://epigraphdb.org> platform. It provides easy access to the 'EpiGraphDB' platform with functions that query the corresponding REST endpoints on the API <https://api.epigraphdb.org> and return the response data in the 'tibble' data frame format.
Maintained by Yi Liu. Last updated 3 years ago.
api-clientbioinformaticsepidemiologygraph-databasemendelian-randomizationphenotypes
2.0 match 27 stars 6.02 score 13 scriptsbioc
DrugVsDisease:Comparison of disease and drug profiles using Gene set Enrichment Analysis
This package generates ranked lists of differential gene expression for either disease or drug profiles. Input data can be downloaded from Array Express or GEO, or from local CEL files. Ranked lists of differential expression and associated p-values are calculated using Limma. Enrichment scores (Subramanian et al. PNAS 2005) are calculated to a reference set of default drug or disease profiles, or a set of custom data supplied by the user. Network visualisation of significant scores are output in Cytoscape format.
Maintained by j. Saez-Rodriguez. Last updated 5 months ago.
microarraygeneexpressionclustering
3.6 match 3.30 score 8 scriptscran
elrm:Exact Logistic Regression via MCMC
Implements a Markov Chain Monte Carlo algorithm to approximate exact conditional inference for logistic regression models. Exact conditional inference is based on the distribution of the sufficient statistics for the parameters of interest given the sufficient statistics for the remaining nuisance parameters. Using model formula notation, users specify a logistic model and model terms of interest for exact inference. See Zamar et al. (2007) <doi:10.18637/jss.v021.i03> for more details.
Maintained by David Zamar. Last updated 3 months ago.
4.5 match 2.56 score 12 scripts 1 dependents
dcnorris
DTAT:Dose Titration Algorithm Tuning
Dose Titration Algorithm Tuning (DTAT) is a methodologic framework allowing dose individualization to be conceived as a continuous learning process that begins in early-phase clinical trials and continues throughout drug development, on into clinical practice. This package includes code that researchers may use to reproduce or extend key results of the DTAT research programme, plus tools for trialists to design and simulate a '3+3/PC' dose-finding study. Please see Norris (2017a) <doi:10.12688/f1000research.10624.3> and Norris (2017c) <doi:10.1101/240846>.
Maintained by David C. Norris. Last updated 10 months ago.
3.9 match 2.90 score 20 scriptscran
Rivivc:In Vitro in Vivo Correlation Linear Level "A"
It is devoted to the IVIVC linear level A with numerical deconvolution method. The latter is working for inequal and incompatible timepoints between impulse and response curves. A numerical convolution method is also available. Application domains include pharamaceutical industry QA/QC and R&D together with academic research.
Maintained by Aleksander Mendyk. Last updated 3 years ago.
11.2 match 1.00 score
gvalentini58
bionetdata:Biological and Chemical Data Networks
Data Package that includes several examples of chemical and biological data networks, i.e. data graph structured.
Maintained by Giorgio Valentini. Last updated 3 years ago.
6.3 match 1.76 score 58 scriptspharmaverse
admiral:ADaM in R Asset Library
A toolbox for programming Clinical Data Interchange Standards Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in R. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team, 2021, <https://www.cdisc.org/standards/foundational/adam>).
Maintained by Ben Straub. Last updated 4 days ago.
cdiscclinical-trialsopen-source
0.8 match 236 stars 13.89 score 486 scripts 4 dependentscran
EWOC.Comb:Escalation with Overdose Control using 2 Drug Combinations
Implements Escalation With Overdose Control trial designs using two drug combinations described by this paper <doi:10.1002/sim.6961>(Tighiouart et al., 2016). It calculates the recommended dose for next cohorts and perform simulations to obtain operating characteristics.
Maintained by Yujie Cui. Last updated 8 months ago.
10.2 match 1.00 score
niuniular
MDDC:Modified Detecting Deviating Cells Algorithm in Pharmacovigilance
Methods for detecting signals related to (adverse event, medical product e.g. drugs, vaccines) pairs, a data generation function for simulating pharmacovigilance datasets, and various utility functions. For more details please see Liu A., Mukhopadhyay R., and Markatou M. <doi:10.48550/arXiv.2410.01168>.
Maintained by Anran Liu. Last updated 5 months ago.
2.2 match 1 stars 4.54 score 4 scripts
ekstroem
isdals:Datasets for Introduction to Statistical Data Analysis for the Life Sciences
Provides datasets for the book "Introduction to Statistical Data Analysis for the Life Sciences, Second edition" by Ekstrøm and Sørensen (2014).
Maintained by Claus Ekstrom. Last updated 2 years ago.
4.0 match 2.51 score 108 scripts 1 dependentscran
sensitivitymv:Sensitivity Analysis in Observational Studies
The package performs a sensitivity analysis in an observational study using an M-statistic, for instance, the mean. The main function in the package is senmv(), but amplify() and truncatedP() are also useful. The method is developed in Rosenbaum Biometrics, 2007, 63, 456-464, <doi:10.1111/j.1541-0420.2006.00717.x>.
Maintained by Paul R. Rosenbaum. Last updated 7 years ago.
3.5 match 2.86 score 60 scripts 4 dependents
mbojan
isnar:Introduction to Social Network Analysis with R
Functions and datasets accompanying the workshop "Introduction to Social Network Analysis with R" on annual INSNA Sunbelt conferences.
Maintained by Michal Bojanowski. Last updated 4 years ago.
3.5 match 8 stars 2.86 score 18 scripts
peterkdunn
GLMsData:Generalized Linear Model Data Sets
Data sets from the book Generalized Linear Models with Examples in R by Dunn and Smyth.
Maintained by Peter K. Dunn. Last updated 3 years ago.
3.8 match 2.61 score 220 scripts
s87jackson
rfars:Download and Analyze Crash Data
Download crash data from the National Highway Traffic Safety Administration and prepare it for research.
Maintained by Steve Jackson. Last updated 12 months ago.
crashfatalitiesofficial-statisticstransportation
1.8 match 10 stars 5.35 score 15 scripts
nlmixr2
nlmixr2lib:A Model Library for 'nlmixr2'
A model library for 'nlmixr2'. The models include (and plan to include) pharmacokinetic, pharmacodynamic, and disease models used in pharmacometrics. Where applicable, references for each model are included in the meta-data for each individual model. The package also includes model composition and modification functions to make model updates easier.
Maintained by Bill Denney. Last updated 2 months ago.
1.5 match 6 stars 6.38 score 9 scriptscran
crosstalkr:Analysis of Graph-Structured Data with a Focus on Protein-Protein Interaction Networks
Provides a general toolkit for drug target identification. We include functionality to reduce large graphs to subgraphs and prioritize nodes. In addition to being optimized for use with generic graphs, we also provides support to analyze protein-protein interactions networks from online repositories. For more details on core method, refer to Weaver et al. (2021) <https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008755>.
Maintained by Davis Weaver. Last updated 10 months ago.
3.5 match 2.70 score
stevencarlislewalker
SASmixed:Data sets from "SAS System for Mixed Models"
Data sets and sample lmer analyses corresponding to the examples in Littell, Milliken, Stroup and Wolfinger (1996), "SAS System for Mixed Models", SAS Institute.
Maintained by Steven Walker. Last updated 11 years ago.
3.5 match 2.68 score 32 scripts
dosorio
retriever:Generate Disease-Specific Response Signatures from the LINCS-L1000 Data
Generates disease-specific drug-response profiles that are independent of time, concentration, and cell-line. Based on the cell lines used as surrogates, the returned profiles represent the unique transcriptional changes induced by a compound in a given disease.
Maintained by Daniel Osorio. Last updated 3 years ago.
4.0 match 2.26 score 12 scriptsbioc
gep2pep:Creation and Analysis of Pathway Expression Profiles (PEPs)
Pathway Expression Profiles (PEPs) are based on the expression of pathways (defined as sets of genes) as opposed to individual genes. This package converts gene expression profiles to PEPs and performs enrichment analysis of both pathways and experimental conditions, such as "drug set enrichment analysis" and "gene2drug" drug discovery analysis respectively.
Maintained by Francesco Napolitano. Last updated 5 months ago.
geneexpressiondifferentialexpressiongenesetenrichmentdimensionreductionpathwaysgo
2.0 match 4.48 score 4 scriptsbioc
MetaboSignal:MetaboSignal: a network-based approach to overlay and explore metabolic and signaling KEGG pathways
MetaboSignal is an R package that allows merging, analyzing and customizing metabolic and signaling KEGG pathways. It is a network-based approach designed to explore the topological relationship between genes (signaling- or enzymatic-genes) and metabolites, representing a powerful tool to investigate the genetic landscape and regulatory networks of metabolic phenotypes.
Maintained by Andrea Rodriguez-Martinez. Last updated 5 months ago.
graphandnetworkgenesignalinggenetargetnetworkpathwayskeggreactomesoftware
1.8 match 4.90 score 8 scripts
john-harrold
ubiquity:PKPD, PBPK, and Systems Pharmacology Modeling Tools
Complete work flow for the analysis of pharmacokinetic pharmacodynamic (PKPD), physiologically-based pharmacokinetic (PBPK) and systems pharmacology models including: creation of ordinary differential equation-based models, pooled parameter estimation, individual/population based simulations, rule-based simulations for clinical trial design and modeling assays, deployment with a customizable 'Shiny' app, and non-compartmental analysis. System-specific analysis templates can be generated and each element includes integrated reporting with 'PowerPoint' and 'Word'.
Maintained by John Harrold. Last updated 17 days ago.
1.2 match 13 stars 7.14 score 33 scriptscran
DOS2:Design of Observational Studies, Companion to the Second Edition
Contains data sets, examples and software from the Second Edition of "Design of Observational Studies"; see Rosenbaum, P.R. (2010) <doi:10.1007/978-1-4419-1213-8>.
Maintained by Paul Rosenbaum. Last updated 6 years ago.
3.6 match 2 stars 2.24 score 29 scripts 1 dependents
amirfeizi
otargen:Access Open Target Genetics
Interact seamlessly with Open Target Genetics' GraphQL endpoint to query and retrieve tidy data tables, facilitating the analysis of genetic data. For more information about the Open Target Genetics API (<https://genetics.opentargets.org/api>).
Maintained by Amir Feizi. Last updated 5 months ago.
1.8 match 9 stars 4.43 score 3 scriptsbioc
bioassayR:Cross-target analysis of small molecule bioactivity
bioassayR is a computational tool that enables simultaneous analysis of thousands of bioassay experiments performed over a diverse set of compounds and biological targets. Unique features include support for large-scale cross-target analyses of both public and custom bioassays, generation of high throughput screening fingerprints (HTSFPs), and an optional preloaded database that provides access to a substantial portion of publicly available bioactivity data.
Maintained by Thomas Girke. Last updated 5 months ago.
immunooncologymicrotitreplateassaycellbasedassaysvisualizationinfrastructuredataimportbioinformaticsproteomicsmetabolomics
1.1 match 5 stars 6.70 score 46 scriptsropensci
tidyqpcr:Quantitative PCR Analysis with the Tidyverse
For reproducible quantitative PCR (qPCR) analysis building on packages from the ’tidyverse’, notably ’dplyr’ and ’ggplot2’. It normalizes (by ddCq), summarizes, and plots pre-calculated Cq data, and plots raw amplification and melt curves from Roche Lightcycler (tm) machines. It does NOT (yet) calculate Cq data from amplification curves.
Maintained by Edward Wallace. Last updated 11 months ago.
miqeqpcrqpcr-analysistidyverse
1.3 match 54 stars 5.64 score 20 scripts
kuleuven-ppw-okpiv
C443:See a Forest for the Trees
Get insight into a forest of classification trees, by calculating similarities between the trees, and subsequently clustering them. Each cluster is represented by it's most central cluster member. The package implements the methodology described in Sies & Van Mechelen (2020) <doi:10.1007/s00357-019-09350-4>.
Maintained by Aniek Sies. Last updated 2 years ago.
3.8 match 1 stars 2.00 score 5 scripts
williamqjw
lmreg:Data and Functions Used in Linear Models and Regression with R: An Integrated Approach
Data files and a few functions used in the book 'Linear Models and Regression with R: An Integrated Approach' by Debasis Sengupta and Sreenivas Rao Jammalamadaka (2019).
Maintained by Jinwen Qiu. Last updated 6 years ago.
3.6 match 2.06 score 116 scriptsbioc
TDbasedUFEadv:Advanced package of tensor decomposition based unsupervised feature extraction
This is an advanced version of TDbasedUFE, which is a comprehensive package to perform Tensor decomposition based unsupervised feature extraction. In contrast to TDbasedUFE which can perform simple the feature selection and the multiomics analyses, this package can perform more complicated and advanced features, but they are not so popularly required. Only users who require more specific features can make use of its functionality.
Maintained by Y-h. Taguchi. Last updated 5 months ago.
geneexpressionfeatureextractionmethylationarraysinglecellsoftwarebioconductor-packagebioinformaticstensor-decomposition
1.7 match 4.48 score 4 scripts
johnjsl7
IAcsSPCR:Data and Functions for "An Intro. to Accept. Samp. & SPC/R"
Contains data frames and functions used in the book "An Introduction to Acceptance Sampling and SPC with R". This book is available electronically at <https://bookdown.org/>. A physical copy will be published by CRC Press.
Maintained by John Lawson. Last updated 4 years ago.
7.3 match 1.00 score 7 scriptscran
eba:Elimination-by-Aspects Models
Fitting and testing multi-attribute probabilistic choice models, especially the Bradley-Terry-Luce (BTL) model (Bradley & Terry, 1952 <doi:10.1093/biomet/39.3-4.324>; Luce, 1959), elimination-by-aspects (EBA) models (Tversky, 1972 <doi:10.1037/h0032955>), and preference tree (Pretree) models (Tversky & Sattath, 1979 <doi:10.1037/0033-295X.86.6.542>).
Maintained by Florian Wickelmaier. Last updated 4 years ago.
3.8 match 1.95 score 30 scripts 1 dependentscran
RRTCS:Randomized Response Techniques for Complex Surveys
Point and interval estimation of linear parameters with data obtained from complex surveys (including stratified and clustered samples) when randomization techniques are used. The randomized response technique was developed to obtain estimates that are more valid when studying sensitive topics. Estimators and variances for 14 randomized response methods for qualitative variables and 7 randomized response methods for quantitative variables are also implemented. In addition, some data sets from surveys with these randomization methods are included in the package.
Maintained by Beatriz Cobo Rodríguez. Last updated 4 years ago.
3.6 match 2.00 score
alan-turing-institute
eider:Declarative Feature Extraction from Tabular Data Records
Extract features from tabular data in a declarative fashion, with a focus on processing medical records. Features are specified as JSON and are independently processed before being joined. Input data can be provided as CSV files or as data frames. This setup ensures that data is transformed in a modular and reproducible manner, and allows the same pipeline to be easily applied to new data.
Maintained by Camila Rangel Smith. Last updated 11 months ago.
1.1 match 3 stars 6.26 score 10 scripts
cran
sensitivitymult:Sensitivity Analysis for Observational Studies with Multiple Outcomes
Sensitivity analysis for multiple outcomes in observational studies. For instance, all linear combinations of several outcomes may be explored using Scheffe projections in the comparison() function; see Rosenbaum (2016, Annals of Applied Statistics) <doi:10.1214/16-AOAS942>. Alternatively, attention may focus on a few principal components in the principal() function. The package includes parallel methods for individual outcomes, including tests in the senm() function and confidence intervals in the senmCI() function.
Maintained by Paul R. Rosenbaum. Last updated 8 years ago.
3.5 match 1.95 score 3 dependentscran
fairml:Fair Models in Machine Learning
Fair machine learning regression models which take sensitive attributes into account in model estimation. Currently implementing Komiyama et al. (2018) <http://proceedings.mlr.press/v80/komiyama18a/komiyama18a.pdf>, Zafar et al. (2019) <https://www.jmlr.org/papers/volume20/18-262/18-262.pdf> and my own approach from Scutari, Panero and Proissl (2022) <https://link.springer.com/content/pdf/10.1007/s11222-022-10143-w.pdf> that uses ridge regression to enforce fairness.
Maintained by Marco Scutari. Last updated 2 years ago.
4.5 match 1 stars 1.52 score 1 dependentspharmaverse
admiralonco:Oncology Extension Package for ADaM in 'R' Asset Library
Programming oncology specific Clinical Data Interchange Standards Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in 'R'. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team (2021), <https://www.cdisc.org/standards/foundational/adam>). The package is an extension package of the 'admiral' package.
Maintained by Stefan Bundfuss. Last updated 2 months ago.
0.8 match 32 stars 8.66 score 30 scripts
luisgarcez11
faersquarterlydata:FDA Adverse Event Reporting System Quarterly Data Extracting Tool
An easy framework to read FDA Adverse Event Reporting System XML/ASCII files <https://www.fda.gov/drugs/questions-and-answers-fdas-adverse-event-reporting-system-faers/fda-adverse-event-reporting-system-faers-latest-quarterly-data-files>.
Maintained by Luis Garcez. Last updated 9 months ago.
2.2 match 3.00 score 1 scriptsctn-0094
public.ctn0094extra:Helper Files for the CTN-0094 Relational Database
Engineered features and "helper" functions ancillary to the 'public.ctn0094data' package, extending this package for ease of use (see <https://CRAN.R-project.org/package=public.ctn0094data>). This 'public.ctn0094data' package contains harmonized datasets from some of the National Institute of Drug Abuse's Clinical Trials Network (NIDA's CTN) projects. Specifically, the CTN-0094 project is to harmonize and de-identify clinical trials data from the CTN-0027, CTN-0030, and CTN-51 studies for opioid use disorder. This current version is built from 'public.ctn0094data' v. 1.0.6.
Maintained by Gabriel Odom. Last updated 1 years ago.
1.7 match 3.88 score 15 scripts
konstantinryabov
dmtools:Tools for Clinical Data Management
For checking the dataset from EDC(Electronic Data Capture) in clinical trials. 'dmtools' reshape your dataset in a tidy view and check events. You can reshape the dataset and choose your target to check, for example, the laboratory reference range.
Maintained by Konstantin Ryabov. Last updated 2 years ago.
cdiscclinical-data-managementlaboratory-reference-range-validate
1.5 match 1 stars 4.32 score 14 scripts
zsviolet
PRSPGx:Construct PGx PRS
Construct pharmacogenomics (PGx) polygenic risk score (PRS) with PRS-PGx-Unadj (unadjusted), PRS-PGx-CT (clumping and thresholding), PRS-PGx-L, -GL, -SGL (penalized regression), PRS-PGx-Bayes (Bayesian regression). Package is based on ''Pharmacogenomics Polyenic Risk Score for Drug Response Prediction Using PRS-PGx Methods'' by Zhai, S., Zhang, H., Mehrotra, D.V., and Shen, J., 2021 (submitted).
Maintained by Song Zhai. Last updated 3 years ago.
3.2 match 2.00 score 3 scripts
danielmc1603
twangMediation:Twang Causal Mediation Modeling via Weighting
Provides functions for estimating natural direct and indirect effects for mediation analysis. It uses weighting where the weights are functions of estimates of the probability of exposure or treatment assignment (Hong, G (2010). <https://cepa.stanford.edu/sites/default/files/workshops/GH_JSM%20Proceedings%202010.pdf> Huber, M. (2014). <doi:10.1002/jae.2341>). Estimation of probabilities can use generalized boosting or logistic regression. Additional functions provide diagnostics of the model fit and weights. The vignette provides details and examples.
Maintained by Dan McCaffrey. Last updated 3 years ago.
3.2 match 2.00 scorepharmaverse
admiralophtha:ADaM in R Asset Library - Ophthalmology
Aids the programming of Clinical Data Standards Interchange Consortium (CDISC) compliant Ophthalmology Analysis Data Model (ADaM) datasets in R. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team, 2021, <https://www.cdisc.org/standards/foundational/adam/adamig-v1-3-release-package>).
Maintained by Edoardo Mancini. Last updated 2 months ago.
0.8 match 15 stars 7.94 score 10 scripts
fusarolimichele
pvda:Disproportionality Functions for Pharmacovigilance
Tools for performing disproportionality analysis using the information component, proportional reporting rate and the reporting odds ratio. The anticipated use is passing data to the da() function, which executes the disproportionality analysis. See Norén et al (2011) <doi:10.1177/0962280211403604> and Montastruc et al (2011) <doi:10.1111/j.1365-2125.2011.04037.x> for further details.
Maintained by Michele Fusaroli. Last updated 2 months ago.
1.1 match 7 stars 5.24 score 5 scriptspharmaverse
admiralvaccine:Vaccine Extension Package for ADaM in 'R' Asset Library
Programming vaccine specific Clinical Data Interchange Standards Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in 'R'. Flat model is followed as per Center for Biologics Evaluation and Research (CBER) guidelines for creating vaccine specific domains. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team (2021), <https://www.cdisc.org/standards/foundational/adam/adamig-v1-3-release-package>). The package is an extension package of the 'admiral' package.
Maintained by Sukalpo Saha. Last updated 2 months ago.
0.8 match 6 stars 7.44 score 23 scripts
ramonoller
FHtest:Tests for Right and Interval-Censored Survival Data Based on the Fleming-Harrington Class
Functions to compare two or more survival curves with: a) The Fleming-Harrington test for right-censored data based on permutations and on counting processes. b) An extension of the Fleming-Harrington test for interval-censored data based on a permutation distribution and on a score vector distribution.
Maintained by Ramon Oller. Last updated 1 years ago.
3.5 match 1.48 score 7 scripts
razrahman
IntegratedMRF:Integrated Prediction using Uni-Variate and Multivariate Random Forests
An implementation of a framework for drug sensitivity prediction from various genetic characterizations using ensemble approaches. Random Forests or Multivariate Random Forest predictive models can be generated from each genetic characterization that are then combined using a Least Square Regression approach. It also provides options for the use of different error estimation approaches of Leave-one-out, Bootstrap, N-fold cross validation and 0.632+Bootstrap along with generation of prediction confidence interval using Jackknife-after-Bootstrap approach.
Maintained by Raziur Rahman. Last updated 7 years ago.
3.9 match 1.26 score 18 scripts
masedki
MHTrajectoryR:Bayesian Model Selection in Logistic Regression for the Detection of Adverse Drug Reactions
Spontaneous adverse event reports have a high potential for detecting adverse drug reactions. However, due to their dimension, the analysis of such databases requires statistical methods. We propose to use a logistic regression whose sparsity is viewed as a model selection challenge. Since the model space is huge, a Metropolis-Hastings algorithm carries out the model selection by maximizing the BIC criterion.
Maintained by Mohammed Sedki. Last updated 9 years ago.
4.9 match 1.00 score 5 scripts
regisoc
kibior:A Simple Data Management and Sharing Tool
An interface to store, retrieve, search, join and share datasets, based on Elasticsearch (ES) API. As a decentralized, FAIR and collaborative search engine and database effort, it proposes a simple push/pull/search mechanism only based on ES, a tool which can be deployed on nearly any hardware. It is a high-level R-ES binding to ease data usage using 'elastic' package (S. Chamberlain (2020)) <https://docs.ropensci.org/elastic/>, extends joins from 'dplyr' package (H. Wickham et al. (2020)) <https://dplyr.tidyverse.org/> and integrates specific biological format importation with Bioconductor packages such as 'rtracklayer' (M. Lawrence and al. (2009) <doi:10.1093/bioinformatics/btp328>) <http://bioconductor.org/packages/rtracklayer>, 'Biostrings' (H. Pagès and al. (2020) <doi:10.18129/B9.bioc.Biostrings>) <http://bioconductor.org/packages/Biostrings>, and 'Rsamtools' (M. Morgan and al. (2020) <doi:10.18129/B9.bioc.Rsamtools>) <http://bioconductor.org/packages/Rsamtools>, but also a long list of more common ones with 'rio' (C-h. Chan and al. (2018)) <https://cran.r-project.org/package=rio>.
Maintained by Régis Ongaro-Carcy. Last updated 4 years ago.
dataimportdatarepresentationthirdpartyclientdata-sciencedatabasedatasetselasticsearchelasticsearch-clientpush-pullsearchsearch-engine
1.1 match 3 stars 4.48 score 8 scripts
synergisticcauselearning
CoOL:Causes of Outcome Learning
Implementing the computational phase of the Causes of Outcome Learning approach as described in Rieckmann, Dworzynski, Arras, Lapuschkin, Samek, Arah, Rod, Ekstrom. 2022. Causes of outcome learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome. International Journal of Epidemiology <doi:10.1093/ije/dyac078>. The optional 'ggtree' package can be obtained through Bioconductor.
Maintained by Andreas Rieckmann. Last updated 3 years ago.
2.9 match 1.70 score 6 scripts
htx-r
crossnma:Cross-Design & Cross-Format Network Meta-Analysis and Regression
Network meta-analysis and meta-regression (allows including up to three covariates) for individual participant data, aggregate data, and mixtures of both formats using the three-level hierarchical model. Each format can come from randomized controlled trials or non-randomized studies or mixtures of both. Estimates are generated in a Bayesian framework using JAGS. The implemented models are described by Hamza et al. 2023 <DOI:10.1002/jrsm.1619>.
Maintained by Guido Schwarzer. Last updated 4 months ago.
1.1 match 1 stars 4.29 score 13 scriptsbioc
ChemmineR:Cheminformatics Toolkit for R
ChemmineR is a cheminformatics package for analyzing drug-like small molecule data in R. Its latest version contains functions for efficient processing of large numbers of molecules, physicochemical/structural property predictions, structural similarity searching, classification and clustering of compound libraries with a wide spectrum of algorithms. In addition, it offers visualization functions for compound clustering results and chemical structures.
Maintained by Thomas Girke. Last updated 5 months ago.
cheminformaticsbiomedicalinformaticspharmacogeneticspharmacogenomicsmicrotitreplateassaycellbasedassaysvisualizationinfrastructuredataimportclusteringproteomicsmetabolomicscpp
0.5 match 14 stars 9.42 score 253 scripts 12 dependents
bjw34032
oro.pet:Rigorous - Positron Emission Tomography
Image analysis techniques for positron emission tomography (PET) that form part of the Rigorous Analytics bundle.
Maintained by Brandon Whitcher. Last updated 3 years ago.
1.8 match 1 stars 2.70 score 7 scripts
cran
ncappc:NCA Calculations and Population Model Diagnosis
A flexible tool that can perform (i) traditional non-compartmental analysis (NCA) and (ii) Simulation-based posterior predictive checks for population pharmacokinetic (PK) and/or pharmacodynamic (PKPD) models using NCA metrics.
Maintained by Andrew C. Hooker. Last updated 7 years ago.
1.7 match 2.70 score
kathrinmoellenhoff
SimDissolution:Modeling and Assessing Similarity of Drug Dissolutions Profiles
Implementation of a model-based bootstrap approach for testing whether two formulations are similar. The package provides a function for fitting a pharmacokinetic model to time-concentration data and comparing the results for all five candidate models regarding the Residual Sum of Squares (RSS). The candidate set contains a First order, Hixson-Crowell, Higuchi, Weibull and a logistic model. The assessment of similarity implemented in this package is performed regarding the maximum deviation of the profiles. See Moellenhoff et al. (2018) <doi:10.1002/sim.7689> for details.
Maintained by Kathrin Moellenhoff. Last updated 5 years ago.
4.6 match 1.00 scorecran
ZINAR1:Simulates ZINAR(1) Model and Estimates Its Parameters Under Frequentist Approach
Generates Realizations of First-Order Integer Valued Autoregressive Processes with Zero-Inflated Innovations (ZINAR(1)) and Estimates its Parameters as described in Garay et al. (2021) <doi:10.1007/978-3-030-82110-4_2>.
Maintained by João Vitor Ribeiro. Last updated 2 years ago.
4.5 match 1.00 score
michaelwrobbins
microsynth:Synthetic Control Methods with Micro- And Meso-Level Data
A generalization of the 'Synth' package that is designed for data at a more granular level (e.g., micro-level). Provides functions to construct weights (including propensity score-type weights) and run analyses for synthetic control methods with micro- and meso-level data; see Robbins, Saunders, and Kilmer (2017) <doi:10.1080/01621459.2016.1213634> and Robbins and Davenport (2021) <doi:10.18637/jss.v097.i02>.
Maintained by Michael Robbins. Last updated 2 years ago.
1.1 match 1 stars 3.71 score 34 scripts
johnros
chords:Estimation in Respondent Driven Samples
Maximum likelihood estimation in respondent driven samples.
Maintained by Jonathan Rosenblatt. Last updated 8 years ago.
3.8 match 1.08 score 12 scripts
wangben718
metalite.sl:Subject-Level Analysis Using 'metalite'
Analyzes subject-level data in clinical trials using the 'metalite' data structure. The package simplifies the workflow to create production-ready tables, listings, and figures discussed in the subject-level analysis chapters of "R for Clinical Study Reports and Submission" by Zhang et al. (2022) <https://r4csr.org/>.
Maintained by Benjamin Wang. Last updated 3 months ago.
1.1 match 3.48 score 8 scripts
ankonahouston
OralOpioids:Retrieving Oral Opioid Information
Provides details such as Morphine Equivalent Dose (MED), brand name and opioid content which are calculated of all oral opioids authorized for sale by Health Canada and the FDA based on their Drug Identification Number (DIN) or National Drug Code (NDC). MEDs are calculated based on recommendations by Canadian Institute for Health Information (CIHI) and Von Korff et al (2008) and information obtained from Health Canada's Drug Product Database's monthly data dump or FDA Daily database for Canadian and US databases respectively. Please note in no way should output from this package be a substitute for medical advise. All medications should only be consumed on prescription from a licensed healthcare provider.
Maintained by Ankona Banerjee. Last updated 2 months ago.
0.9 match 1 stars 4.18 score 4 scripts
simpar1471
openFDA:'openFDA' API
The 'openFDA' API facilitates access to U.S. Food and Drug Administration (FDA) data on drugs, devices, foodstuffs, tobacco, and more with 'httr2'. This package makes the API easily accessible, returning objects which the user can convert to JSON data and parse. Kass-Hout TA, Xu Z, Mohebbi M et al. (2016) <doi:10.1093/jamia/ocv153>.
Maintained by Simon Parker. Last updated 5 months ago.
0.8 match 4.81 score 128 scripts
harryjalexander
ascentTraining:Ascent Training Datasets
Datasets to be used primarily in conjunction with Ascent training materials but also for the book 'SAMS Teach Yourself R in 24 Hours' (ISBN: 978-0-672-33848-9). Version 1.0-7 is largely for use with the book; however, version 1.1 has a much greater focus on use with training materials, whilst retaining compatibility with the book.
Maintained by Harry Alexander. Last updated 3 years ago.
3.8 match 1.00 score 2 scriptscran
BiSEp:Toolkit to Identify Candidate Synthetic Lethality
Enables the user to infer potential synthetic lethal relationships by analysing relationships between bimodally distributed gene pairs in big gene expression datasets. Enables the user to visualise these candidate synthetic lethal relationships.
Maintained by Mark Wappett. Last updated 11 months ago.
1.6 match 2.30 score
iame-researchcenter
PFIM:Population Fisher Information Matrix
Evaluate or optimize designs for nonlinear mixed effects models using the Fisher Information matrix. Methods used in the package refer to Mentré F, Mallet A, Baccar D (1997) <doi:10.1093/biomet/84.2.429>, Retout S, Comets E, Samson A, Mentré F (2007) <doi:10.1002/sim.2910>, Bazzoli C, Retout S, Mentré F (2009) <doi:10.1002/sim.3573>, Le Nagard H, Chao L, Tenaillon O (2011) <doi:10.1186/1471-2148-11-326>, Combes FP, Retout S, Frey N, Mentré F (2013) <doi:10.1007/s11095-013-1079-3> and Seurat J, Tang Y, Mentré F, Nguyen TT (2021) <doi:10.1016/j.cmpb.2021.106126>.
Maintained by Romain Leroux. Last updated 5 months ago.
1.3 match 2.78 score 9 scriptsctn-0094
CTNote:CTN Outcomes, Treatments, and Endpoints
The Clinical Trials Network (CTN) of the U.S. National Institute of Drug Abuse sponsored the CTN-0094 research team to harmonize data sets from three nationally-representative clinical trials for opioid use disorder (OUD). The CTN-0094 team herein provides a coded collection of trial outcomes and endpoints used in various OUD clinical trials over the past 50 years. These coded outcome functions are used to contrast and cluster different clinical outcome functions based on daily or weekly patient urine screenings. Note that we abbreviate urine drug screen as "UDS" and urine opioid screen as "UOS". For the example data sets (based on clinical trials data harmonized by the CTN-0094 research team), UDS and UOS are largely interchangeable.
Maintained by Gabriel Odom. Last updated 1 years ago.
0.8 match 1 stars 4.78 score 20 scripts