ArticleBMC bioinformatics2022
lmerSeq: an R package for analyzing transformed RNA-Seq data with linear mixed effects models.
Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Acute nutritional ketosis during early recovery from aerobic exercise does not affect skeletal muscle transcriptomic response in humans.European journal of applied physiology · 2026Trial
- One-Week Elderberry Juice Intervention Promotes Metabolic Flexibility in the Transcriptome of Overweight Adults During a Meal Challenge.Nutrients · 2025Trial
- scMEDAL: interpretable single-cell transcriptomics analysis with batch effect visualization via deep mixed-effects autoencoder.Nature communications · 2026Article
- Scale reliant mixed effects models enhance microbiome data analysis.Microbiome · 2026Article
- DiDyNet: a robust framework for differential dynamic network inference from longitudinal multi-omics data.Bioinformatics advances · 2026Article
- Environmental RNA-Based Metatranscriptomics as a Novel Biomonitoring Tool: A Case Study of Glyphosate-Based Herbicide Effects on Freshwater Eukaryotic Communities.Molecular ecology · 2025Article
- Simulating paired and longitudinal single-cell RNA sequencing data with rescueSim.Bioinformatics (Oxford, England) · 2025Article
- Article
- Meta-Analysis of Gene Expression in Bulk-Processed Post-Mortem Spinal Cord from ALS Patients and Normal Controls.NeuroSci · 2025Article
- Antennal RNAseq reveals odorant receptors with sex-biased expression in the common eastern firefly, Photinus pyralis.BMC genomics · 2025Article
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- Atopic Dermatitis Complicated by Recurrent Eczema Herpeticum Is Characterized by Multiple, Concurrent Epidermal Inflammatory Endotypes.JID innovations : skin science from molecules to population health · 2024Article
- Defining trophoblast injury patterns in the transcriptomes of dysfunctional placentas.Placenta · 2023Article
- Human neural stem cells restore spatial memory in a transgenic Alzheimer's disease mouse model by an immunomodulating mechanism.Frontiers in aging neuroscience · 2023Article
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Authors and funding
3 authors.
Funding
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Abstract
backgroundStudies that utilize RNA Sequencing (RNA-Seq) in conjunction with designs that introduce dependence between observations (e.g. longitudinal sampling) require specialized analysis tools to accommodate this additional complexity. This R package contains a set of utilities to fit linear mixed effects models to transformed RNA-Seq counts that properly account for this dependence when performing statistical analyses.
resultsIn a simulation study comparing lmerSeq and two existing methodologies that also work with transformed RNA-Seq counts, we found that lmerSeq was comprehensively better in terms of nominal error rate control and statistical power.
conclusionsExisting R packages for analyzing transformed RNA-Seq data with linear mixed models are limited in the variance structures they allow and/or the transformation methods they support. The lmerSeq package offers more flexibility in both of these areas and gave substantially better results in our simulations.
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