R-universe search: exports:format

Showing 7 of total 7 results (show query)

mrcieu

TwoSampleMR:Two Sample MR Functions and Interface to MRC Integrative Epidemiology Unit OpenGWAS Database

A package for performing Mendelian randomization using GWAS summary data. It uses the IEU OpenGWAS database <https://gwas.mrcieu.ac.uk/> to automatically obtain data, and a wide range of methods to run the analysis.

Maintained by Gibran Hemani. Last updated 16 hours ago.

476 stars 11.27 score 1.7k scripts 1 dependents

ianjonsen

aniMotum:Fit Continuous-Time State-Space and Latent Variable Models for Quality Control of Argos Satellite (and Other) Telemetry Data and for Estimating Changes in Animal Movement

Fits continuous-time random walk, correlated random walk and move persistence state-space models for location estimation and behavioural inference from animal tracking data ('Argos', processed light-level 'geolocation', 'GPS'). Template Model Builder ('TMB') is used for fast random-effects estimation. The 'Argos' data can be: (older) least squares-based locations; (newer) Kalman filter-based locations with error ellipse information; or a mixture of both. The models estimate two sets of location states corresponding to: 1) each observation, which are (usually) irregularly timed; and 2) user-specified time intervals (regular or irregular). A track re-routing function is provided to adjust location estimates for known movement barriers. Track simulation functions are provided. Latent variable models are also provided to estimate move persistence from track data not requiring state-space model filtering.

Maintained by Ian Jonsen. Last updated 11 hours ago.

animal-movement animal-tracking random-effects-model state-space-models tmb cpp

39 stars 7.11 score 59 scripts

elipousson

getdata:Get Easy Access to Tabular and Spatial Data

Download and format spatial and non-spatial data with simple filtering by location.

Maintained by Eli Pousson. Last updated 5 months ago.

rspatial

12 stars 4.46 score 18 scripts 3 dependents

frbcesab

popbayes:Bayesian Model to Estimate Population Trends from Counts Series

Infers the trends of one or several animal populations over time from series of counts. It does so by accounting for count precision (provided or inferred based on expert knowledge, e.g. guesstimates), smoothing the population rate of increase over time, and accounting for the maximum demographic potential of species. Inference is carried out in a Bayesian framework. This work is part of the FRB-CESAB working group AfroBioDrivers <https://www.fondationbiodiversite.fr/en/the-frb-in-action/programs-and-projects/le-cesab/afrobiodrivers/>.

Maintained by Nicolas Casajus. Last updated 1 years ago.

animal bayesian counts population precision temporal-trend jags cpp

1 stars 4.30 score

mrcieu

CheckSumStats:CheckSumStats

CheckSumStats is an R package for checking the accuracy of meta- and summary-data from genome-wide association studies (GWAS) prior to their use in post-GWAS applications. For example, the package provides tools for checking that the reported effect allele and effect allele frequency columns are correct. It also checks for possible issues in the reported effect sizes that might introduce bias into downstream analyses.

Maintained by Philip Haycock. Last updated 2 years ago.

8 stars 3.00 score 25 scripts

cran

GCalcium:A Data Manipulation and Analysis Package for Calcium Indicator Data

Provides shortcuts in extracting useful data points and summarizing waveform data. It is optimized for speed to work efficiently with large data sets so you can get to the analysis phase more quickly. It also utilizes a user-friendly format for use by both beginners and seasoned R users.

Maintained by Andrew Tamalunas. Last updated 6 years ago.

2.70 score

cran

REDI:Robust Exponential Decreasing Index

Implementation of the Robust Exponential Decreasing Index (REDI), proposed in the article by Issa Moussa, Arthur Leroy et al. (2019) <https://bmjopensem.bmj.com/content/bmjosem/5/1/e000573.full.pdf>. The REDI represents a measure of cumulated workload, robust to missing data, providing control of the decreasing influence of workload over time. Various functions are provided to format data, compute REDI, and visualise results in a simple and convenient way.

Maintained by Alexia Grenouillat. Last updated 2 years ago.

1.70 score