Assays & Analyses

Novel discoveries don't come from running a single assay. Unlock productivity with Pluto's flexible platform, where you can finally analyze all of your biological data in one place.

Don't see the technology you're looking for? Contact us to learn more about other techniques and pipelines available.

Sequencing-based assays

Store large, raw sequencing data files and transform them into biologically-meaningful results in your browser

Bulk RNA sequencing

Measure genome-wide gene expression with RNA-seq to detect individual & pathway-level changes in transcription.

ChIP sequencing

Map global binding sites with ChIP-seq and visualize results for histones, transcription factors, or any other protein of interest.

Single cell RNA sequencing

Leverage scRNA-seq to hone in on cell type-specific gene expression profiles that change under different conditions.

CUT&RUN

Profile chromatin and identify loci with high signal-to-noise with this efficient epigenome method.Learn more with a live demo

PRO-seq

Use this run-on variant to map RNA Polymerase II active sites across the genome with single-base resolution.

CUT&Tag

An emerging immunotethering technology, CUT&Tag detects peaks even with low input & sequencing depth.Learn more

ATAC-seq

Detect the unique chromatin landscape & measure changes in accessibility across different samples.

Other high-throughput assays

Organize -omics and other data to easily search and compare biomarkers across experiments

  • Metabolomics
  • Proteomics
  • Microarray
  • Methyl arrays
  • Looking for something else? Contact Us

Low(er) throughput assays

Make the simplest experiments powerful with interactive, customizable figures and robust statistics

  • qPCR
  • ELISA
  • Cytokine panels
  • Pharmacokinetics, inhibition and toxicity
  • Microscopy imaging
  • Mesoscale discovery assays
  • And more!

Analysis Types

Run fast and flexible bioinformatics analyses with all parameters tracked along the way for end-to-end reproducibility. Examples include:

Summary analysis

Summarize raw or normalized values for targets in different sample groups.

Differential analyses

Compare genome-wide gene expression / binding in two groups for significant changes.

Pathway analyses

Run gene set enrichment (GSEA) & other algorithms for pathway-level biology.

Longitudinal analysis

Analyze data collected across multiple time-points, ages, doses, and more.

Dimensionality reduction

Experiment with principal components (PCA), UMAP, t-SNE algorithms for sample clustering.

Imaging

Highlight representative images with captions & methology alonside their quantification.

Overlap gene lists, run survival analysis, and many more!

Take your analysis to the next level and answer the scientific questions you care about most.

See the analyses in action with a personalized demo

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