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| Multi-Omics-Single-Zell-RNA-seq-Analyse× | ChIP-seq Peak Calling× | |
|---|---|---|
| Fachgebiet | Bioinformatik | Bioinformatik |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 2015–2021 (rapid maturation with CITE-seq 2017; Seurat v4 2021) | 2007–2008 |
| Urheber≠ | Pioneered by Rahul Satija (Seurat), Oliver Stegle and John Marioni (MOFA+), and the broader single-cell genomics community | Johnson et al. (ChIP-seq concept, 2007); Zhang et al. (MACS algorithm, 2008) |
| Typ≠ | Integrative computational pipeline | Computational genomics pipeline |
| Wegweisende Quelle≠ | Hao, Y., Hao, S., Andersen-Nissen, E., Mauck, W. M., Zheng, S., Butler, A., Lee, M. J., Wilk, A. J., Darby, C., Zager, M., Hoffman, P., Stoeckius, M., Papalexi, E., Mimitou, E. P., Jain, J., Srivastava, A., Stuart, T., Fleming, L. M., Yeung, B., Rogers, A. J., McElrath, J. M., Blish, C. A., Gottardo, R., Smibert, P., & Satija, R. (2021). Integrated analysis of multimodal single-cell data. Cell, 184(13), 3573–3587.e29. link ↗ | Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., & Liu, X. S. (2008). Model-based analysis of ChIP-seq (MACS). Genome Biology, 9(9), R137. DOI ↗ |
| Aliasnamen | scMulti-omics, single-cell multi-omics, multimodal single-cell analysis, paired single-cell omics | ChIP-seq analysis, peak detection, MACS peak calling, ChIP peak identification |
| Verwandt | 6 | 6 |
| Zusammenfassung≠ | Multi-omics single-cell RNA-seq analysis integrates two or more molecular layers — such as gene expression (scRNA-seq), chromatin accessibility (scATAC-seq), or surface protein abundance (CITE-seq) — measured simultaneously or co-profiled in the same individual cells. By aligning these modalities in a shared low-dimensional space, researchers gain a mechanistically richer picture of cell identity, regulatory state, and phenotype than any single assay can provide. | ChIP-seq peak calling is a computational pipeline that identifies genomic regions where a protein of interest — a transcription factor or histone modification — is enriched, based on sequencing reads from chromatin immunoprecipitation experiments. It converts raw sequencing data into a set of high-confidence binding or modification sites across the genome, enabling downstream analysis of gene regulation, chromatin state, and epigenetic mechanisms. |
| ScholarGateDatensatz ↗ |
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