slinky

slinky facilitates access to and processing of the NIH LINCS L1000 dataset by identifying samples and their corresponding controls and encapsulating expression data and metadata as SummarizedExperiment objects for transcriptional analyses.

Key Features:

• BioConductor integration: Encapsulates L1000 data as SummarizedExperiment objects within the BioConductor framework to permit use of BioConductor-based analysis tools.
• Sample and control identification: Automates the identification of samples of interest along with their corresponding control samples from the L1000 dataset.
• Data retrieval and loading: Automates retrieval and loading of expression data and associated metadata from the L1000 corpus.
• Handling decentralized L1000 resources: Streamlines navigation and aggregation of extensive and decentralized L1000 data to create analysis-ready datasets.

Scientific Applications:

• Transcriptional response profiling: Analysis of transcriptional responses across biological conditions and perturbations using L1000 expression data.
• Drug discovery and perturbagen studies: Comparison of perturbation-induced expression signatures for drug discovery and mechanism-of-action investigations.
• Gene expression profiling: Generation of curated expression matrices and metadata for gene expression analyses.
• Cellular mechanism exploration: Investigation of cellular mechanisms and system-level responses through LINCS L1000 transcriptional datasets.
• Genomics and systems biology: Support for genomics and systems-biology studies that require large-scale transcriptional datasets and metadata integration.

Methodology:

Encapsulates L1000 data as SummarizedExperiment objects within BioConductor; automates identification of samples and corresponding controls; retrieves and loads expression data and associated metadata.