Longitudinal Analysis of Contrasts in Gene Expression Data
We are interested in detecting a departure from the baseline in a longitudinal analysis in the context of multiple organ dysfunction syndrome (MODS). In particular, we are given gene expression reads at two time points for a fixed number of genes and individuals. The individuals can be subdivided in...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Genes |
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| Online Access: | https://www.mdpi.com/2073-4425/14/6/1134 |
| _version_ | 1797594682660749312 |
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| author | Georg Hahn Tanya Novak Jeremy C. Crawford Adrienne G. Randolph Christoph Lange |
| author_facet | Georg Hahn Tanya Novak Jeremy C. Crawford Adrienne G. Randolph Christoph Lange |
| author_sort | Georg Hahn |
| collection | DOAJ |
| description | We are interested in detecting a departure from the baseline in a longitudinal analysis in the context of multiple organ dysfunction syndrome (MODS). In particular, we are given gene expression reads at two time points for a fixed number of genes and individuals. The individuals can be subdivided into two groups, denoted as groups <i>A</i> and <i>B</i>. Using the two time points, we compute a contrast of gene expression reads per individual and gene. The age of each individual is known and it is used to compute, for each gene separately, a linear regression of the gene expression contrasts on the individual’s age. Looking at the intercept of the linear regression to detect a departure from the baseline, we aim to reliably single out those genes for which there is a difference in the intercept among those individuals in group <i>A</i> and not in group <i>B</i>. In this work, we develop testing methodology for this setting based on two hypothesis tests—one under the null and one under an appropriately formulated alternative. We demonstrate the validity of our approach using a dataset created by bootstrapping from a real data application in the context of multiple organ dysfunction syndrome (MODS). |
| first_indexed | 2024-03-11T02:26:43Z |
| format | Article |
| id | doaj.art-c4f29a3ea62743e4932e5c98a59162ea |
| institution | Directory Open Access Journal |
| issn | 2073-4425 |
| language | English |
| last_indexed | 2024-03-11T02:26:43Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Genes |
| spelling | doaj.art-c4f29a3ea62743e4932e5c98a59162ea2023-11-18T10:33:16ZengMDPI AGGenes2073-44252023-05-01146113410.3390/genes14061134Longitudinal Analysis of Contrasts in Gene Expression DataGeorg Hahn0Tanya Novak1Jeremy C. Crawford2Adrienne G. Randolph3Christoph Lange4Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USACritical Care Medicine, Department of Anesthesiology, Boston Children’s Hospital, Boston, MA 02115, USASt. Jude Children’s Research Hospital, Memphis, TN 38105, USACritical Care Medicine, Department of Anesthesiology, Boston Children’s Hospital, Boston, MA 02115, USADepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USAWe are interested in detecting a departure from the baseline in a longitudinal analysis in the context of multiple organ dysfunction syndrome (MODS). In particular, we are given gene expression reads at two time points for a fixed number of genes and individuals. The individuals can be subdivided into two groups, denoted as groups <i>A</i> and <i>B</i>. Using the two time points, we compute a contrast of gene expression reads per individual and gene. The age of each individual is known and it is used to compute, for each gene separately, a linear regression of the gene expression contrasts on the individual’s age. Looking at the intercept of the linear regression to detect a departure from the baseline, we aim to reliably single out those genes for which there is a difference in the intercept among those individuals in group <i>A</i> and not in group <i>B</i>. In this work, we develop testing methodology for this setting based on two hypothesis tests—one under the null and one under an appropriately formulated alternative. We demonstrate the validity of our approach using a dataset created by bootstrapping from a real data application in the context of multiple organ dysfunction syndrome (MODS).https://www.mdpi.com/2073-4425/14/6/1134contrastslongitudinal datagene expressionmultiple organ dysfunction syndrome (MODS) |
| spellingShingle | Georg Hahn Tanya Novak Jeremy C. Crawford Adrienne G. Randolph Christoph Lange Longitudinal Analysis of Contrasts in Gene Expression Data Genes contrasts longitudinal data gene expression multiple organ dysfunction syndrome (MODS) |
| title | Longitudinal Analysis of Contrasts in Gene Expression Data |
| title_full | Longitudinal Analysis of Contrasts in Gene Expression Data |
| title_fullStr | Longitudinal Analysis of Contrasts in Gene Expression Data |
| title_full_unstemmed | Longitudinal Analysis of Contrasts in Gene Expression Data |
| title_short | Longitudinal Analysis of Contrasts in Gene Expression Data |
| title_sort | longitudinal analysis of contrasts in gene expression data |
| topic | contrasts longitudinal data gene expression multiple organ dysfunction syndrome (MODS) |
| url | https://www.mdpi.com/2073-4425/14/6/1134 |
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