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ProteoSign: an end-user online differential proteomics statistical analysis platform

Journal Article · · Nucleic Acids Research
DOI:https://doi.org/10.1093/nar/gkx444· OSTI ID:1625565
 [1];  [2];  [3];  [2];  [4];  [5];  [6];  [2];  [4];  [6];  [2]
  1. Univ. of Crete, Heraklion (Greece). Medical School; Univ. of Oxford (United Kingdom). Sir William Dunn School of Pathology; DOE/OSTI
  2. Univ. of Crete, Heraklion (Greece). Medical School
  3. Univ. of Crete, Heraklion (Greece). Medical School; USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)
  4. FORTH, Heraklion (Greece). Inst. of Molecular Biology and Biotechnology
  5. Univ. of Texas Southwestern Medical Center, Dallas, TX (United States). Dept of Bioinformatics
  6. Univ. of Oxford (United Kingdom). Sir William Dunn School of Pathology
+ Show Author Affiliations
Profiling of proteome dynamics is crucial for understanding cellular behavior in response to intrinsic and extrinsic stimuli and maintenance of homeostasis. Over the last 20 years, mass spectrometry (MS) has emerged as the most powerful tool for large-scale identification and characterization of proteins. Bottom-up proteomics, the most common MS-based proteomics approach, has always been challenging in terms of data management, processing, analysis and visualization, with modern instruments capable of producing several gigabytes of data out of a single experiment. Here, we present ProteoSign, a freely available web application, dedicated in allowing users to perform proteomics differential expression/abundance analysis in a userfriendly and self-explanatory way. Although several non-commercial standalone tools have been developed for post-quantification statistical analysis of proteomics data, most of them are not end-user appealing as they often require very stringent installation of programming environments, third-party software packages and sometimes further scripting or computer programming. To avoid this bottleneck, we have developed a user-friendly software platform accessible via a web interface in order to enable proteomics laboratories and core facilities to statistically analyse quantitative proteomics data sets in a resource-efficient manner. ProteoSign is available at http://bioinformatics.med.uoc.gr/ProteoSign and the source code at https://github.com/yorgodillo/ ProteoSign.
Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC); Wellcome Trust
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1625565
Journal Information:
Nucleic Acids Research, Journal Name: Nucleic Acids Research Journal Issue: W1 Vol. 45; ISSN 0305-1048
Publisher:
Oxford University PressCopyright Statement
Country of Publication:
United States
Language:
English

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Protein-Level Statistical Analysis of Quantitative Label-Free Proteomics Data with ProStaR book January 2019
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Combined Short-Term Glucose Starvation and Chemotherapy in 3D Colorectal Cancer Cell Culture Decreases 14-3-3 Family Protein Expression and Phenotypic Response to Therapy journal July 2018
Instant Clue: A Software Suite for Interactive Data Visualization and Analysis journal August 2018
ProteomicsBrowser: MS/proteomics data visualization and investigation journal November 2018
Motor neurons from ALS patients with mutations in C9ORF72 and SOD1 exhibit distinct transcriptional landscapes journal May 2019
An experimentally-derived measure of inter-replicate variation in reference samples: the same-same permutation methodology posted_content May 2021
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