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FIT (version 0.0.6)

Transcriptomic Dynamics Models in Field Conditions

Description

Provides functionality for constructing statistical models of transcriptomic dynamics in field conditions. It further offers the function to predict expression of a gene given the attributes of samples and meteorological data. Nagano, A. J., Sato, Y., Mihara, M., Antonio, B. A., Motoyama, R., Itoh, H., Naganuma, Y., and Izawa, T. (2012). . Iwayama, K., Aisaka, Y., Kutsuna, N., and Nagano, A. J. (2017). .

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Version

Install

install.packages('FIT')

Version

0.0.6

License

MPL (>= 2) | file LICENSE

Maintainer

Koji Iwayama

Last Published

January 7th, 2019

Functions in FIT (0.0.6)

load.weight

Loads regression weight data.
fit.models

A raw API for fixing linear regression coefficients.
make.recipe

Creates a recipe for training models.
weather.entries

Supported weather factors.
load.weather

Loads weather data.
predict

Predicts gene expressions using pretrained models.
prediction.errors

Computes the prediction errors using the trained models.
make.trivial.weights

Makes trivial weight data
optim

A raw API for optimizing model parameters.
init

A raw API for initializing model parameters.
convert.weight

Converts regression weight data from a dataframe into an object.
convert.expression

converts expression data from a dataframe into an object.
load.attribute

Loads attribute data.
FIT

FIT: a statistical modeling tool for transcriptome dynamics under fluctuating field conditions
load.expression

Loads expression data.
convert.attribute

Converts attribute data from a dataframe into an object.
convert.weather

Converts weather data from a dataframe into an object.
train

Constructs models following a recipe.