A unified web platform for network-based analyses of genomic data

Li, T.; Kim, A.; Mercer, J.; Rosenbluh, J.; Horn, H.; Greenfeld, L.; An, D.; Zimmer, A.; Liberzon, A.; Bistline, J.; Natoli, T.; Li, Y.; Tsherniak, A.; Narayan, R.; Subramanian, A.; Liefeld, T.; Wong, B.; Thompson, D.; Calvo, S.; Carr, S.; Boehm, J.; Jaffe, J.; Mesirov, J.; Hacohen, N.; Regev, A.; Lage, K.

doi:10.1101/196303

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bioRxiv · 10.1101/196303

A unified web platform for network-based analyses of genomic data

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Abstract

Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to quantitatively compare the signal-to-noise ratio of different networks, the biology they describe, and to identify the optimal network to interpret a particular genetic dataset. Via GeNets users can train a machine-learning model (Quack) to make such comparisons; and they can execute, store, and share analyses of genetic and RNA sequencing datasets.

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Li, T., Kim, A., Mercer, J., Rosenbluh, J., Horn, H., Greenfeld, L., An, D., Zimmer, A., Liberzon, A., Bistline, J., Natoli, T., Li, Y., Tsherniak, A., Narayan, R., Subramanian, A., Liefeld, T., Wong, B., Thompson, D., Calvo, S., Carr, S., Boehm, J., Jaffe, J., Mesirov, J., Hacohen, N., Regev, A., Lage, K.. 2017-10-02. A unified web platform for network-based analyses of genomic data. https://doi.org/10.1101/196303

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