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| Ekspresi Pembezaan RNA-seq Siri Masa× | Analisis eQTL Siri Masa× | |
|---|---|---|
| Bidang | Bioinformatik | Bioinformatik |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 2006–2018 (principal methods established) | 2010s–2019 (concept established earlier; dynamic framework formalized ~2019) |
| Pengasas≠ | Conesa et al. (maSigPro, 2006); extended by Fischer et al. (ImpulseDE2, 2018) and others | Multiple groups; formalized by Strober et al. and others in the context of cellular differentiation (2019) |
| Jenis≠ | Computational genomics pipeline | Genetic mapping method |
| Sumber perintis≠ | Conesa, A., Nueda, M. J., Ferrer, A., & Talon, M. (2006). maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments. Bioinformatics, 22(9), 1096–1102. link ↗ | Fair, B. J., et al. (2020). Gene expression variability in human and chimpanzee populations share common determinants. eLife, 9, e59929. link ↗ |
| Alias | longitudinal RNA-seq DE analysis, temporal transcriptomics, time-course RNA-seq, dynamic DE analysis | dynamic eQTL analysis, longitudinal eQTL mapping, ts-eQTL, temporal eQTL |
| Berkaitan≠ | 6 | 2 |
| Ringkasan≠ | Time-series RNA-seq differential expression analysis identifies genes whose expression levels change systematically across ordered time points — such as during development, disease progression, or response to a treatment. Unlike two-condition DE analysis, it explicitly models the temporal structure of the data, capturing dynamic gene expression trajectories rather than a single snapshot contrast. Tools such as maSigPro, ImpulseDE2, and splineTimeR have been developed specifically for this design. | Time-series eQTL analysis identifies genetic variants (eQTLs) whose effect on gene expression changes over time or across developmental stages. By combining longitudinal RNA-seq data with individual genotypes, the method captures how the same SNP can activate, silence, or reshape gene regulation at different time points — revealing the temporal architecture of the genome's regulatory program in processes such as differentiation, disease progression, and environmental response. |
| ScholarGateSet data ↗ |
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