Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Broad Institute L1000 Connectivity Map and RNAseq gene expression profiles on tissue samples from the GTEx project

ABSTRACT: The Library of Integrated Cellular Signatures (LINCS) is an NIH program which funds the generation of perturbational profiles across multiple cell and perturbation types, as well as read-outs, at a massive scale. The LINCS Center for Transcriptomics at the Broad Institute uses the L1000 high-throughput gene-expression assay to profile a range of cellular models and perturbations of cellular state. These data relate to using RNA-Seq datasets from the GTEx consortium (http://www.gtexportal.org/) to validate the L1000 assay and to improve the statistical model used in imputing the transcriptome. The Platform is GPL20573: Broad Institute Human L1000 epsilon https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL20573 For questions or assistance with this dataset, please email the CMap support team at: clue@broadinstitute.org

ORGANISM(S): Homo sapiens

PROVIDER: GSE92743 | GEO | 2017/03/03

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

L1000 Connectivity Map perturbational profiles from Broad Institute LINCS Center for Transcriptomics LINCS PHASE *II* (n=354,123; updated March 30, 2017)

Project description:The Library of Integrated Cellular Signatures (LINCS) is an NIH program which funds the generation of perturbational profiles across multiple cell and perturbation types, as well as read-outs, at a massive scale. The LINCS Center for Transcriptomics at the Broad Institute uses the L1000 high-throughput gene-expression assay to build a Connectivity Map which seeks to enable the discovery of functional connections between drugs, genes and diseases through analysis of patterns induced by common gene-expression changes. The platform is GPL20573: Broad Institute Human L1000 epsilon http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL20573 For questions or assistance with this dataset, please email the CMap support team at: clue@broadinstitute.org

2015-07-15 | GSE70138 | GEO

L1000 Connectivity Map perturbational profiles from Broad Institute LINCS Center for Transcriptomics LINCS Pilot PHASE I (n=1,319,138; updated March 03, 2017)

Project description:The Library of Integrated Cellular Signatures (LINCS) is an NIH program which funds the generation of perturbational profiles across multiple cell and perturbation types, as well as read-outs, at a massive scale. The LINCS Center for Transcriptomics at the Broad Institute uses the L1000 high-throughput gene-expression assay to build a Connectivity Map which seeks to enable the discovery of functional connections between drugs, genes and diseases through analysis of patterns induced by common gene-expression changes. These files represent L1000 data generated during the LINCS Pilot Phase (2012-2015), as well as profiles generated for more specific purposes, such as assay development and validation projects or testing custom compounds or non-standard cell lines (not part of the core LINCS cell lines). Note: Related GEO projects include (a) Additional L1000 and RNA-Seq data used to validate the assay and improve the inference model, available at GSE92743 (b) The LINCS “production phase” (also termed Phase II, 2015-2020) which is generating an additional cohort of L1000 data, available at GSE70138. The Platform is GPL20573: Broad Institute Human L1000 epsilon https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL20573 For questions or assistance with this dataset, please email the CMap support team at: clue@broadinstitute.org

2017-03-03 | GSE92742 | GEO

Perturbational proteomic and transcriptional profiles of drug perturbations from Broad Institute LINCS Proteomic Characterization Center for Signaling and Epigenetics and Broad Institute LINCS Center for Transcriptomics (U54HG008097) (n=5,063)

Project description:The Library of Integrated Cellular Signatures (LINCS) is an NIH program which funds the generation of perturbational profiles across multiple cell and perturbation types, as well as read-outs, at a massive scale. The LINCS PCCSE uses two high-throughput liquid chromatography-mass spectrometry (LCMS) assays to study the proteomic changes induced by drug and genetic perturbations. P100 monitors ~100 phosphorylated peptides from cellular proteins that serve as a reduced representation of the phosphoproteome. GCP monitors ~60 modified peptides from histones (e.g., methylated, acetylated, and combinations thereof) encompassing nearly every well-studied post-translational modification on the core nucleosomal histone proteins. Closely complementing these assays is the L1000 high-throughput gene-expression assay. The files available here contain P100, GCP, and L1000 data for 90 small-molecule perturbations in six cell lines (five cancer cell lines and a neurodevelopmental cell model). These data were generated under the auspices of the NIH LINCS Program (www.lincsproject.org). Note: Related GEO projects include a large corpus of additional L1000 data, available at GSE92742. The Platform for the L1000 data is GPL20573: Broad Institute Human L1000 epsilon http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL20573 For questions or assistance with this dataset, please email the Connectivity Map support team at: clue@broadinstitute.org

2017-08-24 | GSE101406 | GEO

The Carcinogenome Project

Project description:We generated a large toxicogenomics resource comprising ∼11,000 expression profiles corresponding to ~500 chemicals, each annotated with carcinogenicity and genotoxicity information, and profiled in HepG2 (human hepatocellular carcinoma cell line) and MCF10A cells at multiple doses and replicates. The Platform is GPL20573: Broad Institute Human L1000 epsilon https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL20573 For questions or assistance with this dataset, please email the CMap support team at: clue@broadinstitute.org

2021-08-28 | GSE178201 | GEO

Homo sapiens

Project description:L1000 Connectivity Map perturbational profiles from Broad Institute LINCS Center for Transcriptomics (NIH U54HL127366)

| PRJNA290347 | ENA

Datasets Used in Evaluation Of RNAi And CRISPR Technologies By Large Scale Gene Expression Profiling In The Connectivity Map

Project description:This GEO Series contains datasets used in the paper "Evaluation Of RNAi And CRISPR Technologies By Large Scale Gene Expression Profiling In The Connectivity Map". The application of RNA interference (RNAi) to mammalian cells has provided the means to perform phenotypic screens to determine the functions of genes. Although RNAi has revolutionized loss of function genetic experiments, it has been difficult to systematically assess the prevalence and consequences of off-target effects. The Connectivity Map (CMAP) represents an unprecedented resource to study the gene expression consequences of expressing short hairpin RNAs (shRNAs). Analysis of signatures for over 13,000 shRNAs applied in 9 cell lines revealed that miRNA-like off-target effects of RNAi are far stronger and more pervasive than generally appreciated. We show that mitigating off-target effects is feasible in these datasets via computational methodologies to produce a Consensus Gene Signature (CGS). In addition, we compared RNAi technology to clustered regularly interspaced short palindromic repeat (CRISPR)-based knockout by analysis of 373 sgRNAs in 6 cells lines, and show that the on-target efficacies are comparable, but CRISPR technology is far less susceptible to systematic off-target effects. These results will help guide the proper use and analysis of loss-of-function reagents for the determination of gene function. Note: Related GEO projects include a large corpus of additional L1000 data, available at GSE92742. The Platform is GPL20573: Broad Institute Human L1000 epsilon https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL20573 For questions or assistance with this dataset, please email the CMap support team at: clue@broadinstitute.org

2017-10-30 | GSE106127 | GEO

A New Approach Methodology (NAM) Based Assessment of Butylated hydroxytoluene (BHT) for Endocrine Disruption (ED) Potential

Project description:We tested the hypothesis that BHT is an endocrine disruptor by using a Next Generation Risk Assessment (NGRA) method. Four different cell lines: A549, HCC1428, HepG2 and MCF7 were treated with BHT and a series of BHT analogs at 5 different concentrations, RNA was isolated from cell extracts and run on the L1000 gene array platform. A toxicogenomics-based assessment was performed by comparing BHT’s unique genomic signature to a large external database containing signatures of other compounds (including many known endocrine disruptors) to identify if any endocrine disruption-related modes of action (MoAs) are prevalent among BHT and other compounds with similar genomic signatures. In addition, we performed a toxicogenomics-based structure activity relationship (SAR) assessment of BHT and a series of structurally similar analogues to understand if endocrine disruption is a relevant MoA for chemicals that are considered suitable analogs to BHT using the P&G read across framework (Wu et al., 2010). The platform is GPL20573: Broad Institute Human L1000 epsilon http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL20573

2022-10-17 | GSE211553 | GEO

Gene expression data of four cancer cell lines (A375, A549, MCF7, and PC3) treated with KR-37524

Project description:KR-37524, known as a Urotensin-II receptor antagonist, has low usability due to its low affinity. For this reason, gene expression information was obtained by treating KR-37524 in four cell cancer cell lines to find a new target. The change in gene expression profile was measured and compared with the LINCS L1000 database and used to find a new target.

2021-07-30 | GSE181088 | GEO

Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis [Tissue_RNA-seq]

Project description:we present a novel path to drug repurposing to identify new immunotherapies for ASCVD. The integration of time of-flight mass cytometry (CyTOF) and RNA-sequencing identified unique inflammatory signatures in peripheral blood mononuclear cells (PBMCs) stimulated with ASCVD plasma. By comparing these inflammatory signatures to large-scale gene expression data from the LINCS L1000 dataset, we identified drugs that could reverse this inflammatory response. In conclusion, a systems immunology-driven drug repurposing with pre- clinical validation strategy can aid the development of new cardiovascular immunotherapies.

2023-04-23 | GSE230216 | GEO

Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis [DRUG_RNA-seq]

2023-04-23 | GSE230215 | GEO