Proportionality: a valid alternative to correlation for relative data.
In the life sciences, many measurement methods yield only the relative abundances of different components in a sample. With such relative-or compositional-data, differential expression needs careful interpretation, and correlation-a statistical workhorse for analyzing pairwise relationships-is an in...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2015-03-01
|
| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1004075 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850125515244961792 |
|---|---|
| author | David Lovell Vera Pawlowsky-Glahn Juan José Egozcue Samuel Marguerat Jürg Bähler |
| author_facet | David Lovell Vera Pawlowsky-Glahn Juan José Egozcue Samuel Marguerat Jürg Bähler |
| author_sort | David Lovell |
| collection | DOAJ |
| description | In the life sciences, many measurement methods yield only the relative abundances of different components in a sample. With such relative-or compositional-data, differential expression needs careful interpretation, and correlation-a statistical workhorse for analyzing pairwise relationships-is an inappropriate measure of association. Using yeast gene expression data we show how correlation can be misleading and present proportionality as a valid alternative for relative data. We show how the strength of proportionality between two variables can be meaningfully and interpretably described by a new statistic ϕ which can be used instead of correlation as the basis of familiar analyses and visualisation methods, including co-expression networks and clustered heatmaps. While the main aim of this study is to present proportionality as a means to analyse relative data, it also raises intriguing questions about the molecular mechanisms underlying the proportional regulation of a range of yeast genes. |
| format | Article |
| id | doaj-art-330a1dbe2de04778a95ecf6f10e49b2a |
| institution | OA Journals |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2015-03-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-330a1dbe2de04778a95ecf6f10e49b2a2025-08-20T02:34:06ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582015-03-01113e100407510.1371/journal.pcbi.1004075Proportionality: a valid alternative to correlation for relative data.David LovellVera Pawlowsky-GlahnJuan José EgozcueSamuel MargueratJürg BählerIn the life sciences, many measurement methods yield only the relative abundances of different components in a sample. With such relative-or compositional-data, differential expression needs careful interpretation, and correlation-a statistical workhorse for analyzing pairwise relationships-is an inappropriate measure of association. Using yeast gene expression data we show how correlation can be misleading and present proportionality as a valid alternative for relative data. We show how the strength of proportionality between two variables can be meaningfully and interpretably described by a new statistic ϕ which can be used instead of correlation as the basis of familiar analyses and visualisation methods, including co-expression networks and clustered heatmaps. While the main aim of this study is to present proportionality as a means to analyse relative data, it also raises intriguing questions about the molecular mechanisms underlying the proportional regulation of a range of yeast genes.https://doi.org/10.1371/journal.pcbi.1004075 |
| spellingShingle | David Lovell Vera Pawlowsky-Glahn Juan José Egozcue Samuel Marguerat Jürg Bähler Proportionality: a valid alternative to correlation for relative data. PLoS Computational Biology |
| title | Proportionality: a valid alternative to correlation for relative data. |
| title_full | Proportionality: a valid alternative to correlation for relative data. |
| title_fullStr | Proportionality: a valid alternative to correlation for relative data. |
| title_full_unstemmed | Proportionality: a valid alternative to correlation for relative data. |
| title_short | Proportionality: a valid alternative to correlation for relative data. |
| title_sort | proportionality a valid alternative to correlation for relative data |
| url | https://doi.org/10.1371/journal.pcbi.1004075 |
| work_keys_str_mv | AT davidlovell proportionalityavalidalternativetocorrelationforrelativedata AT verapawlowskyglahn proportionalityavalidalternativetocorrelationforrelativedata AT juanjoseegozcue proportionalityavalidalternativetocorrelationforrelativedata AT samuelmarguerat proportionalityavalidalternativetocorrelationforrelativedata AT jurgbahler proportionalityavalidalternativetocorrelationforrelativedata |