L1000CDS2
Computational Tool
FAIR Metrics
0 evaluations
General Information
DescriptionAn ultra-fast LINCS L1000 Characteristic Direction signature search engine
Homepagehttp://amp.pharm.mssm.edu/L1000CDS2/#/index
Publications
L1000CDS2: LINCS L1000 characteristic direction signatures search engine
Qiaonan Duan; St Patrick Reid; Neil R Clark; Zichen Wang; Nicolas F Fernandez; Andrew D Rouillard; Ben Readhead; Sarah R Tritsch; Rachel Hodos; Marc Hafner; Mario Niepel; Peter K Sorger; Joel T Dudley; Sina Bavari; Rekha G Panchal; Avi Ma’ayan
The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS2. The L1000CDS2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS2, we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource.
Metrics:
Tool Parameters(required parameters are marked in bold, optional parameters in italic)
DirectionDirection of the perturbations identified by the L1000CDS2 search. "Mimic" identifies perturbations with a similar effect, "reverse" identifies perturbations with an opposite effect to the input gene expression signature.
Canned Analyses generated by the tool

Dataset Accession
Tool Name
Organism
Direction
Cell Type
Disease Name
Drug Name
Hs Gene Symbol
Pert Type
Mm Gene Symbol

Small molecules which mimic acute myocardial infarction
The L1000 database was queried in order to identify small molecule perturbations which mim...
Small molecules which reverse acute myocardial infarction
The L1000 database was queried in order to identify small molecule perturbations which rev...
Small molecules which mimic acute myocardial infarction
The L1000 database was queried in order to identify small molecule perturbations which mim...
Small molecules which reverse acute myocardial infarction
The L1000 database was queried in order to identify small molecule perturbations which rev...
Small molecules which mimic Imatinib treatment
The L1000 database was queried in order to identify small molecule perturbations which mim...
Small molecules which reverse Imatinib treatment
The L1000 database was queried in order to identify small molecule perturbations which rev...
Small molecules which mimic Imatinib treatment
The L1000 database was queried in order to identify small molecule perturbations which mim...
Small molecules which reverse Imatinib treatment
The L1000 database was queried in order to identify small molecule perturbations which rev...
Small molecules which mimic Imatinib treatment
The L1000 database was queried in order to identify small molecule perturbations which mim...
Small molecules which reverse Imatinib treatment
The L1000 database was queried in order to identify small molecule perturbations which rev...
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Datasets analyzed by the tool

Keyword
Tool Name

GSE50588
The Functional Consequences of Variation in Transcription Factor Binding
294
GSE6930
Cytosine arabinoside effect on Ewing's sarcoma cell line: time course and dose response
119
GSE7002
Formaldehyde effect on nasal epithelium: dose response and time course
119
GSE47856
Expression data from cultured human ovarian carcinoma cell lines with and without Cisplatin treatment
119
GSE35366
Models of Neuronal Migration Defects: time course
112
GSE490
Pharmacogenomic effect of corticosteroid in skeletal muscle
112
GSE47150
Embryonic primary cortical neuron response to knockdown of multiple autism candidate genes
112
GSE15129
Coenzyme Q10-dependent gene expression in SAMP1 mice tissues
105
GSE60413
Parkinson Phenotype in Aged PINK1-Deficient Mice Is Accompanied by Progressive Mitochondrial Dysfunction in Absence of Neurodegeneration
105
GSE18344
Nrf2-deficient lung response to cigarette smoke: dose response and time course
98
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