Introduction | Methodology | Overview | Simulating null data | Parallelization in OutSeekR | Output | Example
Package: OutSeekR 1.1.0
OutSeekR: Statistical Approach to Outlier Detection in RNA-Seq and Related Data
An approach to outlier detection in RNA-seq and related data based on five statistics. 'OutSeekR' implements an outlier test by comparing the distributions of these statistics in observed data with those of simulated null data.
Authors:
OutSeekR_1.1.0.tar.gz
OutSeekR_1.1.0.zip(r-4.7)OutSeekR_1.1.0.zip(r-4.6)OutSeekR_1.1.0.zip(r-4.5)
OutSeekR_1.1.0.tgz(r-4.6-any)OutSeekR_1.1.0.tgz(r-4.5-any)
OutSeekR_1.1.0.tar.gz(r-4.7-any)OutSeekR_1.1.0.tar.gz(r-4.6-any)
OutSeekR_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
OutSeekR/json (API)
| # Install 'OutSeekR' in R: |
| install.packages('OutSeekR', repos = c('https://pboutros.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- example.data.for.calculate.p.values - Example.data.for.calculate.p.values
- outliers - Example data set for outlier testing
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:6a3ccf6356. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 126 | ||
| source / vignettes | OK | 246 | ||
| linux-release-x86_64 | NOTE | 119 | ||
| macos-release-arm64 | NOTE | 76 | ||
| macos-oldrel-arm64 | NOTE | 79 | ||
| windows-devel | NOTE | 70 | ||
| windows-release | NOTE | 104 | ||
| windows-oldrel | NOTE | 74 | ||
| wasm-release | OK | 97 |
Exports:calculate.p.valuescalculate.residualsdetect.outlierskmeans.fractionoutlier.detection.cosinequantify.outlierssimulate.nulltrim.samplezrange
Dependencies:codetoolsdigestfuturefuture.applyglobalslistenvlsamclustparallellySnowballCtruncnorm
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Calculate p-values | calculate.p.values |
| Calculate residuals | calculate.residuals |
| Detect outliers | detect.outliers |
| example.data.for.calculate.p.values | example.data.for.calculate.p.values |
| k-means fraction | kmeans.fraction |
| Cosine similarity | outlier.detection.cosine |
| Example data set for outlier testing | outliers |
| Compute quantities for outlier detection | quantify.outliers |
| Simulate from a null distribution | simulate.null |
| Trim a vector of numbers | trim.sample |
| Range of z-scores | zrange |
