An R package for divergence analysis of omics data.
Given the ever-increasing amount of high-dimensional and complex omics data becoming available, it is increasingly important to discover simple but effective methods of analysis. Divergence analysis transforms each entry of a high-dimensional omics profile into a digitized (binary or ternary) code b...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2021-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0249002 |
| _version_ | 1818741282619523072 |
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| author | Wikum Dinalankara Qian Ke Donald Geman Luigi Marchionni |
| author_facet | Wikum Dinalankara Qian Ke Donald Geman Luigi Marchionni |
| author_sort | Wikum Dinalankara |
| collection | DOAJ |
| description | Given the ever-increasing amount of high-dimensional and complex omics data becoming available, it is increasingly important to discover simple but effective methods of analysis. Divergence analysis transforms each entry of a high-dimensional omics profile into a digitized (binary or ternary) code based on the deviation of the entry from a given baseline population. This is a novel framework that is significantly different from existing omics data analysis methods: it allows digitization of continuous omics data at the univariate or multivariate level, facilitates sample level analysis, and is applicable on many different omics platforms. The divergence package, available on the R platform through the Bioconductor repository collection, provides easy-to-use functions for carrying out this transformation. Here we demonstrate how to use the package with data from the Cancer Genome Atlas. |
| first_indexed | 2024-12-18T01:54:09Z |
| format | Article |
| id | doaj.art-2dd8163315614f769faa8963d5244827 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-18T01:54:09Z |
| publishDate | 2021-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-2dd8163315614f769faa8963d52448272022-12-21T21:24:57ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01164e024900210.1371/journal.pone.0249002An R package for divergence analysis of omics data.Wikum DinalankaraQian KeDonald GemanLuigi MarchionniGiven the ever-increasing amount of high-dimensional and complex omics data becoming available, it is increasingly important to discover simple but effective methods of analysis. Divergence analysis transforms each entry of a high-dimensional omics profile into a digitized (binary or ternary) code based on the deviation of the entry from a given baseline population. This is a novel framework that is significantly different from existing omics data analysis methods: it allows digitization of continuous omics data at the univariate or multivariate level, facilitates sample level analysis, and is applicable on many different omics platforms. The divergence package, available on the R platform through the Bioconductor repository collection, provides easy-to-use functions for carrying out this transformation. Here we demonstrate how to use the package with data from the Cancer Genome Atlas.https://doi.org/10.1371/journal.pone.0249002 |
| spellingShingle | Wikum Dinalankara Qian Ke Donald Geman Luigi Marchionni An R package for divergence analysis of omics data. PLoS ONE |
| title | An R package for divergence analysis of omics data. |
| title_full | An R package for divergence analysis of omics data. |
| title_fullStr | An R package for divergence analysis of omics data. |
| title_full_unstemmed | An R package for divergence analysis of omics data. |
| title_short | An R package for divergence analysis of omics data. |
| title_sort | r package for divergence analysis of omics data |
| url | https://doi.org/10.1371/journal.pone.0249002 |
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