SBOL: A community standard for communicating designs in synthetic biology

<p>Abstract</p> <p>The Synthetic Biology Open Language (SBOL) is a proposed data standard for exchanging designs within the synthetic biology community. SBOL represents synthetic biology designs in a community-adopted, formalized format for exchange between software tools, research groups, and commercial service providers. The re-use of previously validated designs is critical to the evolution of synthetic biology from a research discipline to an engineering practice. As a community-driven standard, SBOL adapts as synthetic biology evolves, providing specific capabilities for different aspects of the synthetic biology workflow. The SBOL Developers Group has implemented SBOL 1.1 as an XML/RDF serialization and provides software libraries and specification documentation to help developers implement SBOL in their own software. This paper also reports on early successes, including a demonstration of the utility of SBOL for information exchange between three different tools from three academic sites.</p> <p> </p

A workflow of the gene expression analysis.

<p>The gene expression data were analysed to produce a list of fatigue-related features which were used as inputs for a support vector machine classifier of fatigue. 1. Differentially expressed genes were identified between fatigue groups. 2. Linear regression was used to analyse fatigue as a continuous variable. 3. The interferon type I signature was calculated for all the patients and compared to fatigue levels. 4. Gene set enrichment analysis was carried out using the high and low fatigue groups. 5. A support vector machine classifier was created using fatigue-related features as inputs and its performance assessed using receiver-operator characteristic (ROC) curves.</p

The characteristics of the patients.

<p>A heatmap of the clinical scores for the 133 patients included in this study. The values have been scaled between zero (absent) and one (worst). ESSDAI = EULAR Sjögren’s Syndrome Disease Activity Index, SSDDI = Sjögren’s Syndrome Disease Damage Index, ESSPRI = EULAR Sjögren’s Syndrome Patient Reported Index, HAD = Hospital Anxiety and Depression, PROFAD = Profile of Fatigue and Discomfort, VAS = Visual Analogue Scale.</p

Correction for other clinical factors.

<p>Volcano plots for the Fatigue VAS fatigue groups corrected for clinical factors: (A) Age at UKPSSR cohort recruitment. (B) Disease activity measured using the EULAR Sjögren’s Syndrome Disease Activity Index. (C) Disease damage measured using the Sjögren’s Syndrome Disease Damage Index. (D) The EULAR Sjögren’s Syndrome Patient Reported Index dryness sub-domain. (E) The EULAR Sjögren’s Syndrome Patient Reported Index pain sub-domain. (F) Anxiety measured using the Hospital Anxiety and Depression scale. (G) Depression measured using the Hospital Anxiety and Depression scale. (H) Pain and depression (E & G). (I) Pain, depression, dryness and anxiety (D-G). (J) All seven factors (A-G). No significantly differentially expressed genes were identified following any correction.</p

Support vector machine (SVM) classification of fatigue groups.

<p>The receiver operator characteristic curves for the SVM output. Ten curves are shown on each plot. The area under the curve (AUC) is calculated as the mean over the ten curves. (A) All 181 enriched pathway genes as input. (B) The 55 leading edge genes as input.</p

Interferon type I signature and fatigue.

<p>(A) The IFN score ranges for the 133 patients. (B) The Fatigue VAS scores for the IFN-active and IFN-inactive groups. (C) The ESSDAI scores for the IFN-active and IFN-inactive groups.</p