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L2S2:化学扰动与CRISPR基因敲除的LINCS L1000特征搜索引擎

L2S2: chemical perturbation and CRISPR KO LINCS L1000 signature search engine.

作者信息

Marino Giacomo B, Evangelista John E, Clarke Daniel J B, Ma'ayan Avi

机构信息

Department of Pharmacological Sciences, Department of Artificial Intelligence and Human Health, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States.

出版信息

Nucleic Acids Res. 2025 Jul 7;53(W1):W338-W350. doi: 10.1093/nar/gkaf373.

Abstract

As part of the Library of Integrated Network-Based Cellular Signatures (LINCS) NIH initiative, 248 human cell lines were profiled with the L1000 assay to measure the effect of 33 621 small molecules and 7508 single-gene CRISPR knockouts. From this massive dataset, we computed 1.678 million sets of up- and down-regulated genes. These gene sets are served for search by the LINCS L1000 Signature Search (L2S2) web server application. With L2S2, users can identify small molecules and single gene CRISPR KOs that produce gene expression profiles similar or opposite to their submitted single or up/down gene sets. L2S2 also includes a consensus search feature that ranks perturbations across all cellular contexts, time points, and concentrations. To demonstrate the utility of L2S2, we crossed the L2S2 gene sets with gene sets collected for the RummaGEO resource. The analysis identified clusters of differentially expressed genes that match drug classes, tissues, and diseases, pointing to many opportunities for drug repurposing and drug discovery. Overall, the L2S2 web server application can be used to further the development of personalized therapeutics while expanding our understanding of complex human diseases. The L2S2 web server application is available at https://l2s2.maayanlab.cloud.

摘要

作为美国国立卫生研究院(NIH)综合网络细胞特征库(LINCS)计划的一部分,使用L1000分析方法对248个人类细胞系进行了分析,以测量33621种小分子和7508个单基因CRISPR基因敲除的效果。从这个庞大的数据集中,我们计算出了167.8万组上调和下调基因集。这些基因集可通过LINCS L1000特征搜索(L2S2)网络服务器应用程序进行搜索。使用L2S2,用户可以识别出产生与他们提交的单个或上调/下调基因集相似或相反基因表达谱的小分子和单基因CRISPR基因敲除。L2S2还包括一个共识搜索功能,可对所有细胞环境、时间点和浓度下的扰动进行排名。为了证明L2S2的实用性,我们将L2S2基因集与为RummaGEO资源收集的基因集进行了交叉分析。该分析确定了与药物类别、组织和疾病相匹配的差异表达基因簇,为药物再利用和药物发现提供了许多机会。总体而言,L2S2网络服务器应用程序可用于推动个性化治疗的发展,同时扩展我们对复杂人类疾病的理解。L2S2网络服务器应用程序可在https://l2s2.maayanlab.cloud上获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90cc/12230732/983e887df6df/gkaf373figgra1.jpg

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