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DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer Datasets
SIMPLE SUMMARY: With the influx of multi-omics profiling, effective integration of these data remains the bottleneck for omics-driven discovery. Thus, we developed DRPPM-EASY, an R Shiny framework for integrative multi-omics analysis of cancer datasets. Our tool enables the exploration of multi-omic...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8869715/ https://www.ncbi.nlm.nih.gov/pubmed/35205126 http://dx.doi.org/10.3390/biology11020260 |
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author | Obermayer, Alyssa Dong, Li Hu, Qianqian Golden, Michael Noble, Jerald D. Rodriguez, Paulo Robinson, Timothy J. Teng, Mingxiang Tan, Aik-Choon Shaw, Timothy I. |
author_facet | Obermayer, Alyssa Dong, Li Hu, Qianqian Golden, Michael Noble, Jerald D. Rodriguez, Paulo Robinson, Timothy J. Teng, Mingxiang Tan, Aik-Choon Shaw, Timothy I. |
author_sort | Obermayer, Alyssa |
collection | PubMed |
description | SIMPLE SUMMARY: With the influx of multi-omics profiling, effective integration of these data remains the bottleneck for omics-driven discovery. Thus, we developed DRPPM-EASY, an R Shiny framework for integrative multi-omics analysis of cancer datasets. Our tool enables the exploration of multi-omics data by providing a simple user interface that minimizes the need for computational experience. Furthermore, the interface can be deployed locally or on a webserver to facilitate scientific collaboration and discovery. ABSTRACT: High-throughput transcriptomic and proteomic analyses are now routinely applied to study cancer biology. However, complex omics integration remains challenging and often time-consuming. Here, we developed DRPPM-EASY, an R Shiny framework for integrative multi-omics analysis. We applied our application to analyze RNA-seq data generated from a USP7 knockdown in T-cell acute lymphoblastic leukemia (T-ALL) cell line, which identified upregulated expression of a TAL1-associated proliferative signature in T-cell acute lymphoblastic leukemia cell lines. Next, we performed proteomic profiling of the USP7 knockdown samples. Through DRPPM-EASY-Integration, we performed a concurrent analysis of the transcriptome and proteome and identified consistent disruption of the protein degradation machinery and spliceosome in samples with USP7 silencing. To further illustrate the utility of the R Shiny framework, we developed DRPPM-EASY-CCLE, a Shiny extension preloaded with the Cancer Cell Line Encyclopedia (CCLE) data. The DRPPM-EASY-CCLE app facilitates the sample querying and phenotype assignment by incorporating meta information, such as genetic mutation, metastasis status, sex, and collection site. As proof of concept, we verified the expression of TP53 associated DNA damage signature in TP53 mutated ovary cancer cells. Altogether, our open-source application provides an easy-to-use framework for omics exploration and discovery. |
format | Online Article Text |
id | pubmed-8869715 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88697152022-02-25 DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer Datasets Obermayer, Alyssa Dong, Li Hu, Qianqian Golden, Michael Noble, Jerald D. Rodriguez, Paulo Robinson, Timothy J. Teng, Mingxiang Tan, Aik-Choon Shaw, Timothy I. Biology (Basel) Technical Note SIMPLE SUMMARY: With the influx of multi-omics profiling, effective integration of these data remains the bottleneck for omics-driven discovery. Thus, we developed DRPPM-EASY, an R Shiny framework for integrative multi-omics analysis of cancer datasets. Our tool enables the exploration of multi-omics data by providing a simple user interface that minimizes the need for computational experience. Furthermore, the interface can be deployed locally or on a webserver to facilitate scientific collaboration and discovery. ABSTRACT: High-throughput transcriptomic and proteomic analyses are now routinely applied to study cancer biology. However, complex omics integration remains challenging and often time-consuming. Here, we developed DRPPM-EASY, an R Shiny framework for integrative multi-omics analysis. We applied our application to analyze RNA-seq data generated from a USP7 knockdown in T-cell acute lymphoblastic leukemia (T-ALL) cell line, which identified upregulated expression of a TAL1-associated proliferative signature in T-cell acute lymphoblastic leukemia cell lines. Next, we performed proteomic profiling of the USP7 knockdown samples. Through DRPPM-EASY-Integration, we performed a concurrent analysis of the transcriptome and proteome and identified consistent disruption of the protein degradation machinery and spliceosome in samples with USP7 silencing. To further illustrate the utility of the R Shiny framework, we developed DRPPM-EASY-CCLE, a Shiny extension preloaded with the Cancer Cell Line Encyclopedia (CCLE) data. The DRPPM-EASY-CCLE app facilitates the sample querying and phenotype assignment by incorporating meta information, such as genetic mutation, metastasis status, sex, and collection site. As proof of concept, we verified the expression of TP53 associated DNA damage signature in TP53 mutated ovary cancer cells. Altogether, our open-source application provides an easy-to-use framework for omics exploration and discovery. MDPI 2022-02-08 /pmc/articles/PMC8869715/ /pubmed/35205126 http://dx.doi.org/10.3390/biology11020260 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Technical Note Obermayer, Alyssa Dong, Li Hu, Qianqian Golden, Michael Noble, Jerald D. Rodriguez, Paulo Robinson, Timothy J. Teng, Mingxiang Tan, Aik-Choon Shaw, Timothy I. DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer Datasets |
title | DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer Datasets |
title_full | DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer Datasets |
title_fullStr | DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer Datasets |
title_full_unstemmed | DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer Datasets |
title_short | DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer Datasets |
title_sort | drppm-easy: a web-based framework for integrative analysis of multi-omics cancer datasets |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8869715/ https://www.ncbi.nlm.nih.gov/pubmed/35205126 http://dx.doi.org/10.3390/biology11020260 |
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