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.
- Version1.1.0
- R version≥ 2.10
- LicenseGPL-2
- Needs compilation?No
- Last release03/01/2024
Documentation
Team
Paul C. Boutros
Anders Hugo Frelin
Show author detailsRolesAuthorHelen Zhu
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Last 30 days
This package has been downloaded 155 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 times.
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Last 365 days
This package has been downloaded 1,820 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Jan 22, 2025 with 29 downloads.
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Dependencies
- Imports3 packages
- Suggests5 packages