Loading…
MSdb: An integrated expression atlas of human musculoskeletal system
The global prevalence and burden of musculoskeletal (MSK) disorders are immense. Advancements in next-generation sequencing (NGS) have generated vast amounts of data, accelerating the research of pathological mechanisms and the development of therapeutic approaches for MSK disorders. However, scatte...
Saved in:
Published in: | iScience 2023-06, Vol.26 (6), p.106933-106933, Article 106933 |
---|---|
Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | The global prevalence and burden of musculoskeletal (MSK) disorders are immense. Advancements in next-generation sequencing (NGS) have generated vast amounts of data, accelerating the research of pathological mechanisms and the development of therapeutic approaches for MSK disorders. However, scattered datasets across various repositories complicate uniform analysis and comparison. Here, we introduce MSdb, a database for visualization and integrated analysis of next-generation sequencing data from human musculoskeletal system, along with manually curated patient phenotype data. MSdb provides various types of analysis, including sample-level browsing of metadata information, gene/miRNA expression, and single-cell RNA-seq dataset. In addition, MSdb also allows integrated analysis for cross-samples and cross-omics analysis, including customized differentially expressed gene/microRNA analysis, microRNA-gene network, scRNA-seq cross-sample/disease integration, and gene regulatory network analysis. Overall, systematic categorizing, standardized processing, and freely accessible knowledge features MSdb a valuable resource for MSK research community.
[Display omitted]
•A comprehensive database for human musculoskeletal system gene expression data•Systematically sorted metadata facilitate the reuse of public data•Various online analysis functionalities improve the data mining efficiency
Bioinformatics; Biological database; Genomics; Transcriptomics |
---|---|
ISSN: | 2589-0042 2589-0042 |
DOI: | 10.1016/j.isci.2023.106933 |