Experimental noise cutoff boosts inferability of transcriptional networks in large-scale gene-deletion studies
Reliable inference of gene interactions from perturbation experiments remains a challenge. Here, the authors quantify the upper limits of transcriptional network inference from knockout screens, identify the key determinants of accuracy, and introduce an unbiased and scalable inference algorithm.
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2018-01-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-017-02489-x |