Related Experiment Video
Updated: Feb 16, 2026

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
Published on: March 5, 2022
PIVOT: platform for interactive analysis and visualization of transcriptomics data
Qin Zhu1, Stephen A Fisher2, Hannah Dueck2
1Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Background:
Many R packages have been developed for transcriptome analysis but their use often requires familiarity with R and integrating results of different packages requires scripts to wrangle the datatypes. Furthermore, exploratory data analyses often generate multiple derived datasets such as data subsets or data transformations, which can be difficult to track.
Results:
Here we present PIVOT, an R-based platform that wraps open source transcriptome analysis packages with a uniform user interface and graphical data management that allows non-programmers to interactively explore transcriptomics data. PIVOT supports more than 40 popular open source packages for transcriptome analysis and provides an extensive set of tools for statistical data manipulations. A graph-based visual interface is used to represent the links between derived datasets, allowing easy tracking of data versions. PIVOT further supports automatic report generation, publication-quality plots, and program/data state saving, such that all analysis can be saved, shared and reproduced.
Conclusions:
PIVOT will allow researchers with broad background to easily access sophisticated transcriptome analysis tools and interactively explore transcriptome datasets.
Related Concept Videos
Pivot Bearings
A pivot bearing is a specialized type of bearing designed to support axial loads on a rotating shaft. The bearing surface, or the pivot, is positioned at the end of a shaft to support the axial thrust. The pivot may...
Analysis of Population Pharmacokinetic Data
Overview of Microsoft Excel as a Data Analysis Tool
Performing a Simple Data Analysis using MS-Excel Function
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
Statistical Software for Data Analysis and Clinical Trials
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...

