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FIT

Transcriptomic Dynamics Models in Field Conditions

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). <doi:10.1016/j.cell.2012.10.048>. Iwayama, K., Aisaka, Y., Kutsuna, N., and Nagano, A. J. (2017). <doi:10.1093/bioinformatics/btx049>.

Functions (18)

FIT

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

convert.attribute

Converts attribute data from a dataframe into an object.

convert.expression

converts expression data from a dataframe into an object.

convert.weather

Converts weather data from a dataframe into an object.

convert.weight

Converts regression weight data from a dataframe into an object.

fit.models

A raw API for fixing linear regression coefficients.

init

A raw API for initializing model parameters.

load.attribute

Loads attribute data.

load.expression

Loads expression data.

load.weather

Loads weather data.

load.weight

Loads regression weight data.

make.recipe

Creates a recipe for training models.

make.trivial.weights

Makes trivial weight data

optim

A raw API for optimizing model parameters.

predict

Predicts gene expressions using pretrained models.

prediction.errors

Computes the prediction errors using the trained models.

train

Constructs models following a recipe.

weather.entries

Supported weather factors.

FIT

Transcriptomic Dynamics Models in Field Conditions

v0.0.6
MPL (>= 2) | file LICENSE
Authors
Koji Iwayama [cre], Yuri Aisaka [aut]
Initial release

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