Dataset Information

Dream: powerful differential expression analysis for repeated measures designs.

ABSTRACT:

Summary

Large-scale transcriptome studies with multiple samples per individual are widely used to study disease biology. Yet, current methods for differential expression are inadequate for cross-individual testing for these repeated measures designs. Most problematic, we observe across multiple datasets that current methods can give reproducible false-positive findings that are driven by genetic regulation of gene expression, yet are unrelated to the trait of interest. Here, we introduce a statistical software package, dream, that increases power, controls the false positive rate, enables multiple types of hypothesis tests, and integrates with standard workflows. In 12 analyses in 6 independent datasets, dream yields biological insight not found with existing software while addressing the issue of reproducible false-positive findings.

Availability and implementation

Dream is available within the variancePartition Bioconductor package at http://bioconductor.org/packages/variancePartition.

Contact

gabriel.hoffman@mssm.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Hoffman GE

PROVIDER: S-EPMC8055218 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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Publications

Dream: powerful differential expression analysis for repeated measures designs.

Hoffman Gabriel E GE Roussos Panos P

Bioinformatics (Oxford, England) 20210401 2

<h4>Summary</h4>Large-scale transcriptome studies with multiple samples per individual are widely used to study disease biology. Yet, current methods for differential expression are inadequate for cross-individual testing for these repeated measures designs. Most problematic, we observe across multiple datasets that current methods can give reproducible false-positive findings that are driven by genetic regulation of gene expression, yet are unrelated to the trait of interest. Here, we introduce ...[more]

PMID: 32730587

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Project description:BackgroundThe recently published New Italian version of the Wilkins Rate of Reading Test (standard Italian WRRT) was designed to measure reading speed in repeated-measures designs in research and/or clinical examinations. The test features 15 equivalent 10-line passages made up of unrelated words, adhering to the principles established by the Wilkins Rate of Reading Test in English (original WRRT).AimTo develop a short Italian version of the WRRT (SI-WRRT), and to determine the equivalence across the new, shorter passages of text. The introduction of 5-line passages, instead of the original 10-line ones, aims to enhance the tool's suitability for the elderly or neuropsychological patients by reducing administration time.MethodThe same 15 high-frequency Italian words from the standard Italian WRRT were used to generate 15 5-line passages for the SI-WRRT. Comprehensive eye examination and vision assessment, including the Radner Reading Charts, were performed before the administration of the SI-WRRT. Forty healthy Italian-speaking higher education students read the SI-WRRT passages aloud in random order. Reading speed and accuracy were measured offline from digital recordings of the readings. Equivalence across passages and the effects of practice and fatigue were assessed for reading speed and accuracy, along with test-retest reliability.ResultsNo significant difference in reading speed was found across 14 out of the 15 passages. In addition, no differences were observed in accuracy, and the error rate was very low. Practice and fatigue effects were minimal for reading speed, whereas they were absent for accuracy. Reading speed, the reference metric for the WRRT, showed moderate-to-good test-retest reliability.ConclusionsEquivalence was confirmed across 14 passages of the SI-WRRT. Therefore, the test may be suitable for examining the elderly or neuropsychological patients, as reading time of the 5-line passages is halved with respect to the standard Italian WRRT. However, the 5-line passages still allow the assessment of prolonged reading. Since one passage was not equivalent, we recommend avoiding the use of random rearrangements of words without formally checking their validity.

Dataset Information

Dream: powerful differential expression analysis for repeated measures designs.

Summary

Availability and implementation

Contact

Supplementary information

Publications

Dream: powerful differential expression analysis for repeated measures designs.

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