CSSPFit-class: An S-4 class containing the model fit information for CSSP...

Description Examples

Description

lambdax

Sequencing depth of the input sample.

lambday

Sequencing depth of the ChIP sample.

e0

The normalization parameter for the ChIP sample.

pi0

The pi_0 parameter of CSSP model, denoting the proportion of bins that are enriched.

mu.chip

The vector of the estimated hyper means for the background model of the ChIP sample.

mu.input

The vector of the estimated hyper means for the input sample.

mean.sig

The vector of the hyper means for each signal component.

size.sig

The vector of the size parameters for each signal component.

a

The size parameter of the input sample model.

b

The size parameter of the background model for the ChIP sample.

p.sig

The vector of the proportions of enrichment as each signal component across all enrichment bins.

prob.zero

The vector of the prior inflated probability at 0.

post.p.sig

The matrix for the posterior probability of each bin being enriched as a signal component conditioning on the event that the bin is enriched. Each column corresponds to one signal component.

post.p.bind

Posterior probability of each bin being enriched.

post.p.zero

Posterior probability of the inflated probability at 0.

post.shape.sig

The matrix for the shape parameters for the posterior gamma distributions of bin level poisson parameters, conditioning on the event that the bins are enriched as each signal component. Each column corresponds to one signal component.

post.scale.sig

The matrix for the scale parameters of the posterior gamma distributions of bin level poisson parameters, conditioning on the event that the bins are enriched as each signal component. Each column corresponds to one signal component.

post.shape.back

The shape parameters for the posterior gamma distributions of bin level poisson parameters, conditioning on each bin being enriched.

post.scale.back

The scale parameters for the posterior gamma distributions of bin level poisson parameters, conditioning on each bin being unenriched.

n

The number of mappable bins that are fitted by the model.

k

The number of signal components.

map.id

The indices for the mappable bins that are fitted by the model.

pvalue

The continuously corrected p-values for a subset of ChIP sample bin counts against the background model.

cum.pval

The cumulative distribution for p-values for a subset of ChIP sample bin counts against the background model.

Examples

1
showClass("CSSPFit")

chandlerzuo/cssp documentation built on May 13, 2019, 3:23 p.m.