Abstract
Reconstruction of causal gene networks can distinguish regulators from targets and reduce false positives by integrating genetic variations. Its recent developments in speed and accuracy have enabled whole-transcriptome causal network inference on a personal computer. Here, we demonstrate this technique with program Findr on 3000 genes from the Geuvadis dataset. Subsequent analysis reveals major hub genes in the reconstructed network.
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Acknowledgements
Development of Findr was supported by grants from the BBSRC [BB/J004235/1, BB/M020053/1].
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Wang, L., Michoel, T. (2019). Whole-Transcriptome Causal Network Inference with Genomic and Transcriptomic Data. In: Sanguinetti, G., Huynh-Thu, V. (eds) Gene Regulatory Networks. Methods in Molecular Biology, vol 1883. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8882-2_4
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DOI: https://doi.org/10.1007/978-1-4939-8882-2_4
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