Nothing
OmicsQC: Nominating Quality Control Outliers in Genomic Profiling Studies
A method that analyzes quality control metrics from multi-sample genomic sequencing studies and nominates poor quality samples for exclusion. Per sample quality control data are transformed into z-scores and aggregated. The distribution of aggregated z-scores are modelled using parametric distributions. The parameters of the optimal model, selected either by goodness-of-fit statistics or user-designation, are used for outlier nomination. Two implementations of the Cosine Similarity Outlier Detection algorithm are provided with flexible parameters for dataset customization.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Anders Hugo Frelin [aut], Helen Zhu [aut], Paul C. Boutros [aut, cre] (<https://orcid.org/0000-0003-0553-7520>) |
| Maintainer | Paul C. Boutros <PBoutros@mednet.ucla.edu> |
| License | GPL-2 |
| Version | 1.1.0 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the OmicsQC package in your browser
Any scripts or data that you put into this service are public.
