sim_counts: sim_counts - simulated count data
In TeamMacLean/atacr: Analysing Capture Seq Count Data
Description
Usage
Format
Details
Description
The data ‘sim_counts' is a simulated data set with computer generated window counts for three replicates of each of two conditions in experiments with 500 bait and non-bait windows. We’ll set each experiment to have 10 % of windows differentially accessible at a difference of approximately 2 fold.
The data ‘sim_counts' is a simulated data set with computer generated window counts for three replicates of each of two conditions in experiments with 500 bait and non-bait windows. We’ll set each experiment to have 10 % of windows differentially accessible at a difference of approximately 2 fold.
Usage
1
2
3
Format
A SummarizedExperiment object
Details
Counts in bait windows for "control" samples will be modelled as C \sim NB(μ = 30, size = 10μ).
Counts in bait windows for "treatment" samples will be modelled as C \cdot unif(0.8,1.2).
Differentially accessible bait windows will be modelled as C_{1..50} \cdot \mathcal{N}( μ=2,σ = μ/2)
Counts in bait windows for "control" samples will be modelled as C \sim NB(μ = 30, size = 10μ).
Counts in bait windows for "treatment" samples will be modelled as C \cdot unif(0.8,1.2).
Differentially accessible bait windows will be modelled as C_{1..50} \cdot \mathcal{N}( μ=2,σ = μ/2)
TeamMacLean/atacr documentation built on May 9, 2019, 4:24 p.m.
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Description Usage Format Details
Description
The data ‘sim_counts' is a simulated data set with computer generated window counts for three replicates of each of two conditions in experiments with 500 bait and non-bait windows. We’ll set each experiment to have 10 % of windows differentially accessible at a difference of approximately 2 fold.
The data ‘sim_counts' is a simulated data set with computer generated window counts for three replicates of each of two conditions in experiments with 500 bait and non-bait windows. We’ll set each experiment to have 10 % of windows differentially accessible at a difference of approximately 2 fold.
Usage
1 2 3 |
Format
A SummarizedExperiment object
Details
Counts in bait windows for "control" samples will be modelled as C \sim NB(μ = 30, size = 10μ).
Counts in bait windows for "treatment" samples will be modelled as C \cdot unif(0.8,1.2).
Differentially accessible bait windows will be modelled as C_{1..50} \cdot \mathcal{N}( μ=2,σ = μ/2)
Counts in bait windows for "control" samples will be modelled as C \sim NB(μ = 30, size = 10μ).
Counts in bait windows for "treatment" samples will be modelled as C \cdot unif(0.8,1.2).
Differentially accessible bait windows will be modelled as C_{1..50} \cdot \mathcal{N}( μ=2,σ = μ/2)
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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