🫁 LOSTdb

LOSTdb: a manually curated multi-omics database for lung cancer research

LOSTdb comprises 295 multi-omics datasets, including bulk RNA-seq, genomic, proteomic, methylation, and scRNA-seq data, with over 10,000 manually curated metadata entries. Each omics sample was annotated with both literature-based classical subtypes and NMF-derived meta-program (MP) subtypes. It offers 14 visualization and analysis methods, along with 5 tool modules.

Features

• Multi-Omics Data Integration: Explore genomic, transcriptomic(Bulk, Single-cell), proteomic, and epigenomic data
• Sample: Sample types (LUAD, LUSC, and SCLC); sample sources (clinical samples, mouse models, and cell lines)
• Interactive Visualizations: Dynamic charts and tables for data exploration
• Molecular subtype annotations: Literature-based classical subtypes and NMF-derived meta-program (MP) subtypes
• Tools Analysis: Integrated analysis, Metadata analysis, Gene-Metadata analysis, Target and drug analysis

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This repository contains partial code and tables relating to LOSTdb.

Scripts:

• RNA.R: Script containing RNA-seq analysis functions
• Proteomics.R: Script containing proteomics analysis functions
• 🧬Mutation.R: Script containing genomics analysis functions
• Methylation.R: Script containing methylation analysis functions
• scRNA.R: Script containing scRNA-seq analysis functions
• 🏥Sigclin.R: Script for significance analysis between clinical/meta data.
• 🎯Target.R: Script for target scoring.

📝Tables:

• Dataset catalog of LOSTdb.csv: Dataset information in LOSTdb.
• subtypes.xlsx: Detailed information of molecular subtypes, including classical subtypes and multi-omics meta-program (MP) subtypes.
• Metadata in LOSTdb.csv: Manually curated clinical data and meta data.

Questions or feedback:

For questions, bug reports, or suggestions, please open an issue or join the discussion on our Google Group.

Citation

LOSTdb: a manually curated multi-omics database for lung cancer research