Package: OutSeekR 1.0.0
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_1.0.0.tar.gz
OutSeekR_1.0.0.zip(r-4.5)OutSeekR_1.0.0.zip(r-4.4)OutSeekR_1.0.0.zip(r-4.3)
OutSeekR_1.0.0.tgz(r-4.4-any)OutSeekR_1.0.0.tgz(r-4.3-any)
OutSeekR_1.0.0.tar.gz(r-4.5-noble)OutSeekR_1.0.0.tar.gz(r-4.4-noble)
OutSeekR_1.0.0.tgz(r-4.4-emscripten)OutSeekR_1.0.0.tgz(r-4.3-emscripten)
OutSeekR.pdf |OutSeekR.html✨
OutSeekR/json (API)
NEWS
# Install 'OutSeekR' in R: |
install.packages('OutSeekR', repos = c('https://pboutros.r-universe.dev', 'https://cloud.r-project.org')) |
- 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 2 days agofrom:d264f12af4. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 20 2024 |
R-4.5-win | OK | Nov 20 2024 |
R-4.5-linux | OK | Nov 20 2024 |
R-4.4-win | OK | Nov 20 2024 |
R-4.4-mac | OK | Nov 20 2024 |
R-4.3-win | OK | Nov 20 2024 |
R-4.3-mac | OK | Nov 20 2024 |
Exports:calculate.p.valuescalculate.residualsdetect.outliersidentify.bic.optimal.data.distributionidentify.bic.optimal.residuals.distributionkmeans.fractionoutlier.detection.cosinequantify.outlierssimulate.nulltrim.samplezrange
Dependencies:codetoolsdigestfuturefuture.applygamlssgamlss.datagamlss.distglobalslatticelistenvlsaMASSMatrixnlmeparallellySnowballCsurvivaltruncnorm
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 |
Identify optimal distribution of data | identify.bic.optimal.data.distribution |
Identify optimal distribution of residuals | identify.bic.optimal.residuals.distribution |
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 |