models: Example double exponential decay modeling results

In reedssorenson/RNAdecay: Maximum Likelihood Decay Modeling of RNA Degradation Data

Example double exponential decay modeling results

Description

Example results from maximum likelihood modeling of double exponential RNA decay of 118 genes.

Usage

models

Format

a list of data frames, each with 240 rows (1/model) with 22 columns and 240 rows.

geneID

gene identifier

mod

model names as factors

alpha_XXX

decay rate estimate of genotype XXX, in per time (min^-1)

beta_XXX

decay of decay rate estimate of genotype XXX, in per time (min^-1)

sigma2

variance estimate

logLik

maxium log likelihood

nPar

number of parameters in the given model

nStarts

number of parameter starting value sets (of 50) that converged on a maximum likelihood peak

J

number of parameter starting value sets that converged on the highest - within 1e-4 - maximum likelihood of all parameter starting value sets

range.LL

range of maximum likelihoods values reached by algorithm convergence from all parameter starting value sets

nUnique.LL

number of unique maximum likelihoods values reached by algorithm convergence from all parameter starting value sets

C.alpha

sum of all coefficients of variation for each column of alpha estimates

C.beta

sum of all coefficients of variation for each column of beta estimates

C.tot

C.alpha+C.beta

AICc

calculated from the single highest maximum likelihood of all parameter starting value sets

AICc_est

calculated from the log likelihood value computed by using the mean of each parameter from all optimizations that converged on the highest maximum likelihood of all starting parameter value sets

Source

Sorenson et al. (2017) Submitted; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE86361

reedssorenson/RNAdecay documentation built on Oct. 28, 2023, 11:31 a.m.