Synthetic lethality knowledge base (SLKB) is dedicated to curating CRISPR double knockout experiments (CDKO) aiming to identify synthetic lethal (SL) interactions between two genes. SL identification is highly context dependent, differing across pathways, gene targets, cell lines, and CDKO libraries. SLKB analysis pipeline, additionally distributed as a python package, allows SL score calculation for CDKO studies. Via SLKB, users can analyze their own CDKO data and browse their results.
| SLKB Study Reported Content | |
| # of SL CDKO Studies | 11 (currently counts available for 10) |
| # of sgRNA guides + sequences | 45,430 sgRNAs (1,802 controls) |
| # of sgRNA pair counts | 3,578,017 sgRNA pairs |
| # of unique genes and gene pairs | 6,127 genes/280,483 gene pairs (148,040 unique) |
| # of SL pairs (originally reported) | 16,059 gene pairs |
| # of non-SL pairs (originally reported) | 264,424 gene pairs |
| SLKB Processed Content | |
| # of unique genes and gene pairs (calculated scores) | 6,124 genes/261,958 gene pairs (127,688 unique) |
| # of SL pairs (majority vote) | 13,173 gene pairs |
| # of non-SL pairs (majority vote) | 248,785 gene pairs |
| SL Connectivity Hubs | |
| # of SL hub clusters (containing at least 3 genes through SL interactions) | 865 |
| # of giant SL hub clusters (containing more than 10 genes through SL interactions) | 67 |
| # of mega SL hub clusters (containing more than 20 genes through SL interactions) | 10 |
SLKB offers data browsing and visualization in two ways: (1) study reported SL data, and (2) SLKB calculated SL scores. Both ways allow tabular data browsing. Network visualizations and Venn diagrams are available for study reported and SLKB reported data respectively.
The studies that are currently available in SLKB can be browsed within this page.
(1): Users can filter the available datatable with their own query.
Users can query the contents of SLKB through this page. Users can browse cell lines, studies, and genes. Empty parameters return every possible query.
(1): Users can query multiple genes, separated by semicolon.
(2): Users can query multiple studies' PubMed IDs, separated by semicolon.
(3): Users can query multiple cell lines, separated by semicolon.
(4): Users can limit the query to the aforementioned genes by checking this box.
(5): Users can visualize SL network across Pubmed IDs as annotation. This can be combined with cell line annotation. (Default: only Pubmed ID)
(6): Users can visualize SL network across cell lines as annotation. This can be combined with Pubmed ID annotations.
(7): Users can run the query after filling all parameters. If no parameters are filled, all contents in SLKB are returned.
(8): SLKB contents are displayed in multiple tabs.
(9): All tabs except network tab are tables. Each table can be sorted and filtered based on the columns and contents.
Users can see the impact of each scoring method on the predicted SL pairs. (Default: top 10% pairs from each method)
(1): Users need to choose a study and cell line before proceeding.
(2): Users can set custom score thresholds to each method. Each user entry is tied to its filter button, the updates are made live.
(3): Users can download the Venn diagram contents, where zeros and ones indicate gene prediction by the designated methods.
Users can browse study reported SL scores and contents within this page.
(1): Users can filter the reported results to pairs identified as synthetic lethal.
(2): Users need to choose a study and cell line. Users can query all studies and cell lines.
(3): Users can view the study details to the left side of the panel.
(4): Users can sort the table contents and filter based on their query.
Users can browse study reported SL scores and contents within this page.
(1): Users can filter the reported results to pairs identified as synthetic lethal.
(2): Users need to choose a study and cell line. Users can query all studies and cell lines.
(3): Users can select target genes to filter the yielded network, separated by semicolon.
(4): Users can download the resulting network after it's loaded.
Users may access both the analysis pipeline and web app at the documentation website.
| Data Name | Data Description | Data Download |
| Raw SL Data | Contains original scores for the CDKO studies. | rawSL |
| SLKB Calculated SL Scores | Contains SLKB score calculation for the CDKO studies. | calcSL |
| SLKB Predicted Pairs | Contains the Venn diagram contents of SLKB scoring methods, separated by study and cell line. | predSL |
| SQL Dump Files | Contains the entirety of SLKB database, from counts to scores. | |
| SLKB Pipeline | Full SLKB pipeline (i.e., scoring, database creation, web app) can be accessed at the project link. | |
| SLKB Analysis Pipeline Documentation | Documentation can be accessed at the project link. | |
| SLKB Web App Source | SLKB Web app can be accessed at the GitHub link (or through Zenodo). Results from the pipeline can be inserted for browsing. |
If SLKB, through its pipeline or webapp has helped with your research, please cite us!
Gökbağ, B., Tang, S., Fan, K., Cheng, L., Yu, L., Zhao, Y., & Li, L. (2024). SLKB: synthetic lethality knowledge base. Nucleic Acids Res. 2024 Jan 5;52(D1):D1418-D1428. doi: 10.1093/nar/gkad806. PMID: 37889037; PMCID: PMC10767912.
Bibtex:
@Article{,
author = {Birkan Gökbağ, Shan Tang, Kunjie Fan, Lijun Cheng, Lianbo Yu, Yue Zhao, Lang Li},
title = {SLKB: Synthetic lethality knowledge base},
journal = {Nucleic acids research},
year = {2024},
doi = {10.1093/nar/gkad806}
}