webSLE is a lightweight application designed to display clinical and transcriptional data from the Dallas pediatric SLE cohort
webSLE enables the tracking of longitudinal individual clinical profiles. Select a patient and let customizable charts display clinical and laboratory parameters such as SLEDAI, anti-dsDNA antibody titers, complete blood counts, treatment and nephritis class at each visit. Understand the global clinical history of each individual at a single glance.
Linear mixed models were developed to identify the transcriptional correlates of disease activity, SLEDAI component distribution and nephritis classes at the cohort level. Along with the SAS code for each model, webSLE displays the expression profiles and annotated lists of transcripts significantly modulated for each comparison conducted by the models.
We leveraged Weighted Gene Co-expression Network Analysis (WGCNA) to develop an individual longitudinal immunomonitoring pipeline. webSLE displays module/trait correlation matrices, module eigengene profiles and module content per individual.
Visualize changes in blood fingerprints over time with our blood module framework to identify alterations in leukocyte activation and/or frequency and track the status of major immune networks over time.
WebSLE.com is a lightweight web application built in R/Shiny that displays the clinical and transcriptional data from the Dallas Pediatric SLE Cohort. The interface complements the manuscript Longitudinal Blood Transcriptomics Uncovers Immune Networks That Stratify Lupus Patients. It also aims to foster further analysis of this dataset by members of the scientific and biomedical community within the context of their specific research interests. WebSLE.com is organized in 4 sections, including Clinical Data, Mixed Models, WGCNA Runs and Blood Modules, that are accessible from the top navigation bar.
These tutorials will show you how to:
The clinical data section is subdivided into 3 sections:
This section displays the results from the 3 mixed models developed for this study.
Under each tab, the user can select any one of the pairwise estimates conducted. For example, the estimate DA3 vs. DA1 ‐ Up in DA3 returns all transcripts that are differentially expressed between the disease activity groups DA3 and DA1, and specifically overexpressed in DA3.
This section displays the Baylor blood module expression profile for each visit for a chosen patient. The color scale represents the percentage of transcripts from the module that display a normalized fold change of at least 1.5 fold (up in red, down in blue) and a raw data difference of at least 100 as compared to the median of healthy controls. This feature is useful to get a quick overview of the expression dynamics of hematopoietic networks for each individual over time.
The transcript content of each module is displayed under the Annotations tab, in a searchable table.
Click on the following link to download the batch-corrected normalized data for the SLE longitudinal study.
SLE_Longitudinal_972_eset.RData