scTML: A Database for Single-Cell Mutation Landscapes in Cancer
Author Information
Author(s): Li Haochen, Ma Tianxing, Zhao Zetong, Chen Yixin, Xi Xi, Zhao Xiaofei, Zhou Xiaoxiang, Gao Yibo, Wei Lei, Zhang Xuegong
Primary Institution: Tsinghua University
Hypothesis
There is a lack of a single-cell-level database containing comprehensive mutation information in all types of cancer.
Conclusion
The scTML database provides a critical resource for exploring single-cell mutation landscapes and their associations with phenotypes across various cancers.
Supporting Evidence
- scTML includes 636,251 SNVs and insertions/deletions, 98,632 gene fusions, 5,784 alternative splicing events, and 4,866 CNVs.
- The database allows users to explore mutation-phenotype associations at the single-cell level.
- Users can analyze single-cell-level mutation-phenotype relationships and detect cell subclusters of interest.
Takeaway
Scientists created a new database that helps us understand how different mutations in cancer cells work together and affect the cells' behavior.
Methodology
The study involved collecting and analyzing single-cell transcriptomic data from 74 datasets, detecting various mutation types, and establishing a comprehensive database.
Limitations
The database currently lacks some high-quality datasets without publicly available raw sequencing data.
Digital Object Identifier (DOI)
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