A transcriptome atlas and interactive analysis platform for autoimmune disease

Shen, Zhuoqiao; Fang, Minghao; Sun, Wujianan; Tang, Meifang; Liu, Nianping; Zhu, Lin; Liu, Qian; Li, Bin; Sun, Ruoming; Shi, Yu; Guo, Chuang; Lin, Jun; Qu, Kun

doi:10.1093/database/baac050

Cited by 4 publications

(1 citation statement)

References 41 publications

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“…GEOexplorer ( 9 ), eVITTA ( 10 ), ImaGEO ( 11 ) and GREIN ( 12 )] and databases [e.g. Autoimmune Diseases Explorer ( 13 ), IAAA ( 14 ) and Expression Atlas ( 15 )] have been developed with data visualization, differential gene identification, pathway enrichment analysis or data comparison functions.…”

Section: Introductionmentioning

confidence: 99%

IBDTransDB: a manually curated transcriptomic database for inflammatory bowel disease

Avram,

Yadav,

Sahasrabudhe

et al. 2024

Database

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Inflammatory Bowel Disease (IBD) therapies are ineffective in at least 40% patients, and transcriptomic datasets have been widely used to reveal the pathogenesis and to identify the novel drug targets for these patients. Although public IBD transcriptomic datasets are available from many web-based tools/databases, due to the unstructured metadata and data description of these public datasets, most of these tools/databases do not allow querying datasets based on multiple keywords (e.g. colon and infliximab). Furthermore, few tools/databases can compare and integrate the datasets from the query results. To fill these gaps, we have developed IBDTransDB (https://abbviegrc.shinyapps.io/ibdtransdb/), a manually curated transcriptomic database for IBD. IBDTransDB includes a manually curated database with 34 transcriptomic datasets (2932 samples, 122 differential comparisons) and a query system supporting 35 keywords from 5 attributes (e.g. tissue and treatment). IBDTransDB also provides three modules for data analyses and integration. IBDExplore allows interactive visualization of differential gene list, pathway enrichment, gene signature and cell deconvolution analyses from a single dataset. IBDCompare supports comparisons of selected genes or pathways from multiple datasets across different conditions. IBDIntegrate performs meta-analysis to prioritize a list of genes/pathways based on user-selected datasets and conditions. Using two case studies related to infliximab treatment, we demonstrated that IBDTransDB provides a unique platform for biologists and clinicians to reveal IBD pathogenesis and identify the novel targets by integrating with other omics data. Database URL: https://abbviegrc.shinyapps.io/ibdtransdb/

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Section: Introductionmentioning

confidence: 99%

IBDTransDB: a manually curated transcriptomic database for inflammatory bowel disease

Avram,

Yadav,

Sahasrabudhe

et al. 2024

Database

View full text Add to dashboard Cite

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Managing autoimmune disorders through personalized epigenetic approaches

Telatin,

Chang

2024

Personalized Epigenetics

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Scope+: An open source generalizable architecture for single-cell atlases at sample and cell levels

Yin

Cao

Chen

et al. 2022

Preprint

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Recent advancements in the use of single-cell technologies in large cohort studies enable the investigation of cellular response and mechanisms associated with disease outcome, including COVID-19. Several efforts have been made using single-cell RNA-sequencing to better understand the immune response to COVID-19 virus infection. Nonetheless, it is often difficult to compare or integrate data from multiple data sets due to challenges in data normalisation, metadata harmonisation, and having a common interface to quickly query and access this vast amount of data. Here we present Covidscope (http://covidsc.d24h.hk/), a well-curated open web resource that currently contains single-cell gene expression data and associated metadata of almost 5 million blood and immune cells extracted from almost 1,000 COVID-19 patients across 20 studies around the world. Our collection contains the integrated data with harmonised metadata and multi-level cell type annotations. By combining NoSQL and optimised index, our Covidscope achieves rapid subsetting of high-dimensional gene expression data based on both data set level, donor-level (e.g., age and sex of patients) and cell-level (e.g., expression of specific gene markers) metadata, enabling multiple efficient downstream single-cell meta-analysis.

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A transcriptome atlas and interactive analysis platform for autoimmune disease

Cited by 4 publications

References 41 publications

IBDTransDB: a manually curated transcriptomic database for inflammatory bowel disease

IBDTransDB: a manually curated transcriptomic database for inflammatory bowel disease

Managing autoimmune disorders through personalized epigenetic approaches

Scope+: An open source generalizable architecture for single-cell atlases at sample and cell levels

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