Pluto Knowledge Base
pluto.bio
Analyses
Getting Started
Anatomy of your Lab Space
Your Account
Organization Settings
Manage Access
Experiments
Experiment types in Pluto
Data inputs and outputs
Single cell
Experiment actions and resources
Analyses
Summary
Pathway
Dimensionality reduction
Clinical outcomes
Comparative
Content
Genome
Plots
Integrations
Sharing and Security
Explore
Solutions
Experiment Pipeline Methods
Reference: Analysis Terms & Methods
Software Packages
Sequencing
Statistics
Data Management
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Pluto Knowledge Base
Analyses
Getting Started
Anatomy of your Lab Space
Your Account
Organization Settings
Manage Access
Experiments
Experiment types in Pluto
Data inputs and outputs
Single cell
Experiment actions and resources
Analyses
Summary
Pathway
Dimensionality reduction
Clinical outcomes
Comparative
Content
Genome
Plots
Integrations
Sharing and Security
Explore
Solutions
Experiment Pipeline Methods
Reference: Analysis Terms & Methods
Software Packages
Sequencing
Statistics
Data Management
Analyses
The "Analysis" model in Pluto is a configurable recipe for running a bioinformatics pipeline
Change log: Analyses
Choosing between MACS2 and SEACR for peak calling with DNA Sequencing datasets
Adding comparisons for gene set enrichment analysis
Including covariates in differential analyses
Protein-protein interaction analysis
Summary
Summary Analysis
Summary analysis (CPM-normalized)
Clustering (differential features)
Longitudinal analysis
Pathway
Transcription factor enrichment analysis (TFEA)
Gene set enrichment analysis (GSEA)
Dimensionality reduction
Uniform Manifold Approximation and Projection (UMAP)
t-distributed Stochastic Neighbor Embedding (t-SNE)
Principal components analysis (PCA)
Clinical outcomes
Survival analysis
Comparative
Differential expression analysis
Differential expression analysis for single cell RNA-seq data
Content
Text
Images
Genome
Peak analysis
Coverage Analysis