FIT

FIT (Field-Informed Transcriptome) models transcriptomic dynamics in response to fluctuating environmental conditions in field settings to quantify how environmental factors influence organismal gene expression.

Key Features:

• Statistical Modeling: Implements statistical models that describe the relationship between transcriptomic variation and continuous environmental conditions.
• Efficient Parameter Optimization: Employs an efficient parameter optimization procedure that reduces computational cost while maintaining or improving prediction accuracy.
• R Package Implementation: Provides an R package with functions for parameter optimization and transcriptome prediction.

Scientific Applications:

• Ecological research: Predicts transcriptomic responses of organisms in fluctuating field environments to study adaptive responses to environmental variation.
• Agricultural and crop research (rice): Models transcriptomic changes in rice plants under field conditions to investigate responses to environmental stressors relevant to crop improvement and resilience.

Methodology:

Collect transcriptome data from field environments and apply statistical models relating transcriptomic variation to environmental conditions, using efficient parameter optimization implemented as R package functions for parameter optimization and transcriptome prediction.