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. 2020 Jan 23;18(1):e3000583. doi: 10.1371/journal.pbio.3000583

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© 2020 Blatti et al

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Fig 5 — (A) Each user-uploaded expression profile (sample) is matched against expression profiles in a predetermined collection (signatures) and match scores for all sample-signature pairs are reported by the pipeline. (B) Signature Analysis and other KnowEnG pipelines can be executed seamlessly on the third-party platform of SB-CGC that hosts a large repository of cancer data and associated tools. The pipelines are published on SB-CGC as a native workflow and the Knowledge Network is transferred “under the hood” from the KnowEnG Cloud when needed by a pipeline. (C) Signature Analysis of 79 ESCC samples, distributed into 3 subgroups, matched against 4 LUSC signatures (subtypes) using Spearman’s Correlation Coefficient. (D) Signature analysis of 551 LUSC samples available on the SB-CGC, matched against 4 LUSC signatures. ESCC, esophageal squamous cell carcinoma; KnowEnG, Knowledge Engine for Genomics; LUSC, lung squamous cell carcinoma; SB-CGC, Seven Bridges Cancer Genomics Cloud.