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Automated ChIP-seq analysis platform

Map global binding sites with ChIP-seq and visualize results for histones, transcription factors, or any other protein of interest. The technique involving chromatin immunoprecipitation + sequencing (ChIP-seq) is used for analyzing protein interactions with DNA. Comparing how transcription factors and other chromatin-associated proteins like histone marks interact with DNA in different conditions provides valuable, epigenetic insights into mechanisms of disease, the effect of different treatments, & more. Cleavage Under Targets and Release Using Nuclease (CUT&RUN) is a newer technique for measuring DNA-protein interactions. Scientists working in oncology, immunology, drug discovery & other areas of research can use ChIP-seq or CUT&RUN to compare healthy and disease states to identify differentially binding and altered biological pathways to discover therapeutic targets.

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Analyzing protein-DNA interactions is intuitive with Pluto

Pluto is a cloud-based platform designed and tested by scientists specifically for managing, analyzing, & visualizing life sciences data like ChIPseq and CUT&RUN. With an elegant interface tailored to your lab’s experimental workflows, Pluto allows both wet lab researchers & bioinformaticists a simple and secure way to collaborate on data analysis and visualization.

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Visual data analysis

1. Upload raw data (e.g. FASTQ or BigWig files) or processed, tabular data. 2. Run automated ChIP-seq and CUT&RUN pipelines with customizable parameters. View quality control report and all analysis methods recorded for auditing & end-to-end reproducibility. 3. Ask scientifically relevant questions. 4. Share results securely within your internal team, external vendors & exec stakeholders

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Wet lab biologist friendly

Can a wet lab biologist with no coding experience analyze their own ChIP-seq experiment using Pluto? Yes! Scientists can run bioinformatics analyses like differential binding, peak analysis, motif analysis & more to create interactive plots without any code.

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Why ChIP-seq or CUT&RUN?

Faster time to insight

  • Hours instead of days
  • No need to wait days or weeks in a backlog

Fully leverage all of your data

  • Instant searchability
  • Stop searching cloud storage and hard drives

Bioinformatics pipelines

  • Automated
  • No-Coding Required
  • Eliminate the frustration managing & maintaining pipelines

Resources & Updates

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Learning Series
Stop Wasting Time: Correcting Batch Effects in Multi-Omics Data to Accelerate Discovery

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Learning Series
Buried in bigWigs? Simplify Your Genomic Data Visualization

bigWig files are powerful for signal visualization — but without context and collaboration, they slow discovery. Pluto connects them to your full workflow.

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Learning Series
Comparing bioinformatics platforms: Pluto Bio, Partek Flow, Basepair, and Rosalind

Compare top bioinformatics platforms—Pluto Bio, Partek Flow, Basepair, and Rosalind—to find the best fit for your NGS data analysis needs. Assess supported assays, analyses, visualizations, and collaboration features.

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Learning Series
Unlocking biological insights with multi-omics approaches

Explore how multi-omics integrates diverse datasets like RNA-seq, ATAC-seq, and ChIP-seq to unlock biological insights, accelerate drug discovery, and drive personalized therapies. Learn more about its impact on cancer research and target identification.

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Learning Series
Multi-Omics Target Validation: Building an Effective Drug Discovery Pipeline

Discover how Pluto’s multi-omics pipelines accelerate target validation in drug discovery. Learn how integrated platforms streamline the path from omics data to validated therapeutic targets.

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Learning Series
Alternatives to Rosalind for Bioinformatics and Computational Biology

Discover top alternatives to Rosalind for bioinformatics and computational biology. Explore platforms like Pluto Bio, BaseSpace, GenePattern, and more to find the right solution for your research needs.

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Product Updates
Pluto product update

We’re excited to share a look at some of the latest product updates we’ve been working on, and give you a sneak peek into new features. Here’s the latest: Comments and Notes, Covariates, Export to Microsoft Word and Powerpoint, and more.

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Learning Series
Understanding Key File Formats in High-Throughput Research

Learn about key file formats in high-throughput research, including FASTQ, FASTA, BAM/SAM, BAI, SAM, VCF, GFF/GTF, BED, BedGraph, BigWig, and PDB. Discover how each format is used, what information it contains, and its significance in analyzing ChIP-seq and ATAC-seq data. Understanding these formats is crucial for efficiently handling and analyzing high-throughput data, enabling valuable biological insights and discoveries.

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Learning Series
CUT&RUN 101 for Biologists

Curious about CUT&RUN and when you would use it? Learn more in this Pluto blog post about getting started with CUT&RUN.

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Product Updates
Introducing an even more powerful experience for creating publication-ready plots

Pluto is revolutionizing how R&D teams think about their results and figures.

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Learning Series
Visualizing Genomic Data with IGV Plots: A Powerful Tool for Genomic Research

Discover the power of Integrative Genomics Viewer (IGV) plots - a highly customizable and interactive tool for visualizing and exploring genomic data. Learn how IGV plots can be used in genomic research and the methods for creating data used in these plots. #genomics #bioinformatics.

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Learning Series
Unraveling the Power of ChIP-seq: A Guide to Understanding Protein-DNA Interactions

ChIP-seq, or chromatin immunoprecipitation sequencing, is a powerful tool used to study protein-DNA interactions in the genome.

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Learning Series
Understanding Fraction and Reads in Peaks: A Guide for ChIP-seq and ATAC-seq Analysis

We will explain what these factors are and how they are used to analyze ChIP-seq and ATAC-seq data

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Learning Series
Exploring the Power of ATAC-seq: A Guide to Understanding Chromatin Accessibility

ATAC-seq, or assay for transposase-accessible chromatin sequencing, is a powerful tool used to study the accessibility of the genome.

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