Literature DB >> 34039258

PTMViz: a tool for analyzing and visualizing histone post translational modification data.

Kevin Chappell1, Stefan Graw1,2, Charity L Washam1,2, Aaron J Storey1, Chris Bolden3, Eric C Peterson3, Stephanie D Byrum4,5.   

Abstract

BACKGROUND: Histone post-translational modifications (PTMs) play an important role in our system by regulating the structure of chromatin and therefore contribute to the regulation of gene and protein expression. Irregularities in histone PTMs can lead to a variety of different diseases including various forms of cancer. Histone modifications are analyzed using high resolution mass spectrometry, which generate large amounts of data that requires sophisticated bioinformatics tools for analysis and visualization. PTMViz is designed for downstream differential abundance analysis and visualization of both protein and/or histone modifications.
RESULTS: PTMViz provides users with data tables and visualization plots of significantly differentiated proteins and histone PTMs between two sample groups. All the data is packaged into interactive data tables and graphs using the Shiny platform to help the user explore the results in a fast and efficient manner to assess if changes in the system are due to protein abundance changes or epigenetic changes. In the example data provided, we identified several proteins differentially regulated in the dopaminergic pathway between mice treated with methamphetamine compared to a saline control. We also identified histone post-translational modifications including histone H3K9me, H3K27me3, H4K16ac, and that were regulated due to drug exposure.
CONCLUSIONS: Histone modifications play an integral role in the regulation of gene expression. PTMViz provides an interactive platform for analyzing proteins and histone post-translational modifications from mass spectrometry data in order to quickly identify differentially expressed proteins and PTMs.

Entities:  

Keywords:  Differential abundance; Histone post-translational modifications; Proteomics; Shiny

Year:  2021        PMID: 34039258     DOI: 10.1186/s12859-021-04166-9

Source DB:  PubMed          Journal:  BMC Bioinformatics        ISSN: 1471-2105            Impact factor:   3.169


  3 in total

1.  Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics.

Authors:  Kendra J Adams; Brian Pratt; Neelanjan Bose; Laura G Dubois; Lisa St John-Williams; Kevin M Perrott; Karina Ky; Pankaj Kapahi; Vagisha Sharma; Michael J MacCoss; M Arthur Moseley; Carol A Colton; Brendan X MacLean; Birgit Schilling; J Will Thompson
Journal:  J Proteome Res       Date:  2020-03-26       Impact factor: 4.466

2.  WERAM: a database of writers, erasers and readers of histone acetylation and methylation in eukaryotes.

Authors:  Yang Xu; Shuang Zhang; Shaofeng Lin; Yaping Guo; Wankun Deng; Ying Zhang; Yu Xue
Journal:  Nucleic Acids Res       Date:  2016-10-26       Impact factor: 16.971

3.  proteiNorm - A User-Friendly Tool for Normalization and Analysis of TMT and Label-Free Protein Quantification.

Authors:  Stefan Graw; Jillian Tang; Maroof K Zafar; Alicia K Byrd; Chris Bolden; Eric C Peterson; Stephanie D Byrum
Journal:  ACS Omega       Date:  2020-09-30
  3 in total

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