scholarly journals psichomics: graphical application for alternative splicing quantification and analysis

2018 ◽  
Author(s):  
Nuno Saraiva-Agostinho ◽  
Nuno L. Barbosa-Morais
Keyword(s):  
Alternative Splicing ◽  
R Package ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Global Studies ◽  
Rna Seq ◽  
Cellular Processes ◽  
Cancer Genome Atlas ◽  
Downstream Analysis ◽  
User Friendly

Alternative pre-mRNA splicing generates functionally distinct transcripts from the same gene and is involved in the control of multiple cellular processes, with its dysregulation being associated with a variety of pathologies. The advent of next-generation sequencing has enabled global studies of alternative splicing in different physiological and disease contexts. However, current bioinformatics tools for alternative splicing analysis from RNA-seq data are not user-friendly, disregard available exon-exon junction quantification or have limited downstream analysis features. To overcome such limitations, we have developedpsichomics, an R package with an intuitive graphical interface for alternative splicing quantification and downstream dimensionality reduction, differential splicing and gene expression and survival analyses based on The Cancer Genome Atlas, the Genotype-Tissue Expression project and user-provided data. These integrative analyses can also incorporate clinical and molecular sample-associated features. We successfully usedpsichomicsto reveal alternative splicing signatures specific to stage I breast cancer and associated novel putative prognostic factors.

scholarly journals DIANA-miTED: a microRNA tissue expression database

2021 ◽  
Author(s):  
Ioannis Kavakiotis ◽  
Athanasios Alexiou ◽  
Spyros Tastsoglou ◽  
Ioannis S Vlachos ◽  
Artemis G Hatzigeorgiou
Keyword(s):  
Mirna Expression ◽  
Cell Types ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Starting Point ◽  
Metadata Quality ◽  
Cancer Genome Atlas ◽  
Downstream Analysis ◽  
Systematic Collection

Abstract microRNAs (miRNAs) are short (∼23nt) single-stranded non-coding RNAs that act as potent post-transcriptional gene expression regulators. Information about miRNA expression and distribution across cell types and tissues is crucial to the understanding of their function and for their translational use as biomarkers or therapeutic targets. DIANA-miTED is the most comprehensive and systematic collection of miRNA expression values derived from the analysis of 15 183 raw human small RNA-Seq (sRNA-Seq) datasets from the Sequence Read Archive (SRA) and The Cancer Genome Atlas (TCGA). Metadata quality maximizes the utility of expression atlases, therefore we manually curated SRA and TCGA-derived information to deliver a comprehensive and standardized set, incorporating in total 199 tissues, 82 anatomical sublocations, 267 cell lines and 261 diseases. miTED offers rich instant visualizations of the expression and sample distributions of requested data across variables, as well as study-wide diagrams and graphs enabling efficient content exploration. Queries also generate links towards state-of-the-art miRNA functional resources, deeming miTED an ideal starting point for expression retrieval, exploration, comparison, and downstream analysis, without requiring bioinformatics support or expertise. DIANA-miTED is freely available at http://www.microrna.gr/mited.

scholarly journals Visual Display of 5p-arm and 3p-arm miRNA Expression with a Mobile Application

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Chao-Yu Pan ◽  
Wei-Ting Kuo ◽  
Chien-Yuan Chiu ◽  
Wen-chang Lin
Keyword(s):  
Mirna Expression ◽  
Expression Patterns ◽  
Mirna Gene ◽  
Visual Display ◽  
Mature Mirnas ◽  
Mobile App ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
User Friendly

MicroRNAs (miRNAs) play important roles in human cancers. In previous studies, we have demonstrated that both 5p-arm and 3p-arm of mature miRNAs could be expressed from the same precursor and we further interrogated the 5p-arm and 3p-arm miRNA expression with a comprehensive arm feature annotation list. To assist biologists to visualize the differential 5p-arm and 3p-arm miRNA expression patterns, we utilized a user-friendly mobile App to display. The Cancer Genome Atlas (TCGA) miRNA-Seq expression information. We have collected over 4,500 miRNA-Seq datasets from 15 TCGA cancer types and further processed them with the 5p-arm and 3p-arm annotation analysis pipeline. In order to be displayed with the RNA-Seq Viewer App, annotated 5p-arm and 3p-arm miRNA expression information and miRNA gene loci information were converted into SQLite tables. In this distinct application, for any given miRNA gene, 5p-arm miRNA is illustrated on the top of chromosome ideogram and 3p-arm miRNA is illustrated on the bottom of chromosome ideogram. Users can then easily interrogate the differentially 5p-arm/3p-arm expressed miRNAs with their mobile devices. This study demonstrates the feasibility and utility of RNA-Seq Viewer App in addition to mRNA-Seq data visualization.

scholarly journals IsoformSwitchAnalyzeR: analysis of changes in genome-wide patterns of alternative splicing and its functional consequences

2019 ◽  
Vol 35 (21) ◽  
pp. 4469-4471 ◽  
Author(s):  
Kristoffer Vitting-Seerup ◽  
Albin Sandelin
Keyword(s):  
Alternative Splicing ◽  
The Cancer Genome Atlas ◽  
Supplementary Information ◽  
Rna Seq ◽  
Genome Wide ◽  
Functional Consequences ◽  
Cancer Genome Atlas ◽  
Health And Disease ◽  
Splicing Patterns

Abstract Summary Alternative splicing is an important mechanism involved in health and disease. Recent work highlights the importance of investigating genome-wide changes in splicing patterns and the subsequent functional consequences. Current computational methods only support such analysis on a gene-by-gene basis. Therefore, we extended IsoformSwitchAnalyzeR R library to enable analysis of genome-wide changes in specific types of alternative splicing and predicted functional consequences of the resulting isoform switches. As a case study, we analyzed RNA-seq data from The Cancer Genome Atlas and found systematic changes in alternative splicing and the consequences of the associated isoform switches. Availability and implementation Windows, Linux and Mac OS: http://bioconductor.org/packages/IsoformSwitchAnalyzeR. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals neoANT-HILL: an integrated tool for identification of potential neoantigens

2020 ◽  
Author(s):  
Ana Carolina Coelho ◽  
Andre Fonseca ◽  
Danilo Martins ◽  
Paulo Lins ◽  
Lucas da Cunha ◽  
...  
Keyword(s):  
High Sensitivity ◽  
The Cancer Genome Atlas ◽  
High Rate ◽  
Graphical Interface ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
Automated Pipeline ◽  
User Friendly ◽  
Ngs Data ◽  
Multiple Samples

Abstract Background Cancer neoantigens have attracted great interest in immunotherapy due to their capacity to elicit antitumoral responses. These molecules arise from somatic mutations in cancer cells, resulting in alterations on the original protein. Neoantigens identification remains a challenging task due largely to a high rate of false-positives. Results We have developed an efficient and automated pipeline for the identification of potential neoantigens. neoANT-HILL integrates several immunogenomic analyses to improve neoantigen detection from Next Generation Sequence (NGS) data. The pipeline has been compiled in a pre-built Docker image such that minimal computational background is required for download and setup. NeoANT-HILL was applied in the The Cancer Genome Atlas (TCGA) melanoma dataset and found several putative neoantigens including ones derived from the recurrent RAC1:P29S and SERPINB3:E250K mutations. neoANT-HILL was also used to identify potential neoantigens in RNA-Seq data with a high sensitivity and specificity. Conclusion neoANT-HILL is a user-friendly tool with a graphical interface that performs neoantigens prediction efficiently. neoANT-HILL is able to process multiple samples, provides several binding predictors, enables quantification of tumor-infiltrating immune cells and considers RNA-Seq data for identifying potential neoantigens. The software is available on github at https://github.com/neoanthill/neoANT-HILL .

scholarly journals neoANT-HILL: an integrated tool for identification of potential neoantigens

2020 ◽  
Author(s):  
Ana Carolina Coelho ◽  
Andre Fonseca ◽  
Danilo Martins ◽  
Paulo Lins ◽  
Lucas da Cunha ◽  
...  
Keyword(s):  
High Sensitivity ◽  
The Cancer Genome Atlas ◽  
High Rate ◽  
Graphical Interface ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
Automated Pipeline ◽  
User Friendly ◽  
Ngs Data ◽  
Multiple Samples

Abstract Background Cancer neoantigens have attracted great interest in immunotherapy due to their capacity to elicit antitumoral responses. These molecules arise from somatic mutations in cancer cells, resulting in alterations on the original protein. Neoantigens identification remains a challenging task due largely to a high rate of false-positives.Results We have developed an efficient and automated pipeline for the identification of potential neoantigens. neoANT-HILL integrates several immunogenomic analyses to improve neoantigen detection from Next Generation Sequence (NGS) data. The pipeline has been compiled in a pre-built Docker image such that minimal computational background is required for download and setup. NeoANT-HILL was applied in the The Cancer Genome Atlas (TCGA) melanoma dataset and found several putative neoantigens including ones derived from the recurrent RAC1:P29S and SERPINB3:E250K mutations. neoANT-HILL was also used to identify potential neoantigens in RNA-Seq data with a high sensitivity and specificity.Conclusion neoANT-HILL is a user-friendly tool with a graphical interface that performs neoantigens prediction efficiently. neoANT-HILL is able to process multiple samples, provides several binding predictors, enables quantification of tumor-infiltrating immune cells and considers RNA-Seq data for identifying potential neoantigens. The software is available on github at https://github.com/neoanthill/neoANT-HILL .

scholarly journals neoANT-HILL: an integrated tool for identification of potential neoantigens

2020 ◽  
Author(s):  
Ana Carolina Coelho ◽  
Andre Fonseca ◽  
Danilo Martins ◽  
Paulo Lins ◽  
Lucas da Cunha ◽  
...  
Keyword(s):  
High Sensitivity ◽  
The Cancer Genome Atlas ◽  
High Rate ◽  
Graphical Interface ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
Automated Pipeline ◽  
User Friendly ◽  
Ngs Data ◽  
Multiple Samples

Abstract Background: Cancer neoantigens have attracted great interest in immunotherapy due to their capacity to elicit antitumoral responses. These molecules arise from somatic mutations in cancer cells, resulting in alterations on the original protein. Neoantigens identification remains a challenging task due largely to a high rate of false-positives. Results: We have developed an efficient and automated pipeline for the identification of potential neoantigens. neoANT-HILL integrates several immunogenomic analyses to improve neoantigen detection from Next Generation Sequence (NGS) data. The pipeline has been compiled in a pre-built Docker image such that minimal computational background is required for download and setup. NeoANT-HILL was applied in The Cancer Genome Atlas (TCGA) melanoma dataset and found several putative neoantigens including ones derived from the recurrent RAC1:P29S and SERPINB3:E250K mutations. neoANT-HILL was also used to identify potential neoantigens in RNA-Seq data with a high sensitivity and specificity.Conclusion: neoANT-HILL is a user-friendly tool with a graphical interface that performs neoantigens prediction efficiently. neoANT-HILL is able to process multiple samples, provides several binding predictors, enables quantification of tumor-infiltrating immune cells and considers RNA-Seq data for identifying potential neoantigens. The software is available through github at https://github.com/neoanthill/neoANT-HILL.

scholarly journals neoANT-HILL: an integrated tool for identification of potential neoantigens

2020 ◽  
Author(s):  
Ana Carolina Coelho ◽  
Andre Fonseca ◽  
Danilo Martins ◽  
Paulo Lins ◽  
Lucas da Cunha ◽  
...  
Keyword(s):  
High Sensitivity ◽  
The Cancer Genome Atlas ◽  
High Rate ◽  
Graphical Interface ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
Automated Pipeline ◽  
User Friendly ◽  
Ngs Data ◽  
Multiple Samples

Abstract Background Cancer neoantigens have attracted great interest in immunotherapy due to their capacity to elicit antitumoral responses. These molecules arise from somatic mutations in cancer cells, resulting in alterations on the original protein. Neoantigens identification remains a challenging task due largely to a high rate of false-positives. Results We have developed an efficient and automated pipeline for the identification of potential neoantigens. neoANT-HILL integrates several immunogenomic analyses to improve neoantigen detection from Next Generation Sequence (NGS) data. The pipeline has been compiled in a pre-built Docker image such that minimal computational background is required for download and setup. NeoANT-HILL was applied in the The Cancer Genome Atlas (TCGA) melanoma dataset and found several putative neoantigens including ones derived from the recurrent RAC1:P29S and SERPINB3:E250K mutations. neoANT-HILL was also used to identify potential neoantigens in RNA-Seq data with a high sensitivity and specificity. Conclusion neoANT-HILL is a user-friendly tool with a graphical interface that performs neoantigens prediction efficiently. neoANT-HILL is able to process multiple samples, provides several binding predictors, enables quantification of tumor-infiltrating immune cells and considers RNA-Seq data for identifying potential neoantigens. The software is available on github at https://github.com/neoanthill/neoANT-HILL .

Identification of Prognostic Alternative Splicing Signature in Gastric Cancer

2021 ◽  
Author(s):  
Zhiwu Wang ◽  
Qiong Wu ◽  
Yankun Liu ◽  
Jingwu Li
Keyword(s):  
Gastric Cancer ◽  
Alternative Splicing ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Splicing Factors ◽  
Rna Seq ◽  
Oncogenic Pathways ◽  
Splicing Variants ◽  
Cancer Genome Atlas

Abstract Aberrant alternative splicing (AS) events serve as prognostic indicators in a large number of malignancies, whereas comprehensive analysis of prognostic AS in gastric cancer (GC) has not yet been understood. To identify prognostic AS events and clarify the function of the splicing variants in GC. RNA-Seq data, clinical information and percent spliced in (PSI) values were available in the cancer genome atlas (TCGA) and TCGA SpliceSeq data portal. A three-step regression method was conducted to screen prognostic AS events and construct multi-AS-based signatures. The associations between prognostic AS events and splicing factors were also investigated. We identified a total of 1318 survival related AS events in GC, Parent genes of which were implicated in numerous oncogenic pathways. The final prognostic signatures stratified by seven types of AS events or not stratified performed well in risk prediction for GC patients. Moreover, five signatures base on AA, AD, AT, ES and RI events function as independent prognostic indicators after multivariate adjustment of clinicalpathological variables. Splicing network also showed marked correlation between the expression of splicing factors and PSI value of AS events in GC patients. The AS derived signatures allow to predict GC prognosis and might serve as potential therapeutic target for GC.

scholarly journals Enabling cross-study analysis of RNA-Sequencing data

2017 ◽  
Author(s):  
Qingguo Wang ◽  
Joshua Armenia ◽  
Chao Zhang ◽  
Alexander V. Penson ◽  
Ed Reznik ◽  
...  
Keyword(s):  
Large Scale ◽  
Tissue Expression ◽  
Underlying Disease ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Sequencing Data ◽  
Whole Transcriptome Sequencing ◽  
Cancer Genome Atlas ◽  
Next Generation Sequencing Ngs ◽  
Different Sources

AbstractDriven by the recent advances of next generation sequencing (NGS) technologies and an urgent need to decode complex human diseases, a multitude of large-scale studies were conducted recently that have resulted in an unprecedented volume of whole transcriptome sequencing (RNA-seq) data. While these data offer new opportunities to identify the mechanisms underlying disease, the comparison of data from different sources poses a great challenge, due to differences in sample and data processing. Here, we present a pipeline that processes and unifies RNA-seq data from different studies, which includes uniform realignment and gene expression quantification as well as batch effect removal. We find that uniform alignment and quantification is not sufficient when combining RNA-seq data from different sources and that the removal of other batch effects is essential to facilitate data comparison. We have processed data from the Genotype Tissue Expression project (GTEx) and The Cancer Genome Atlas (TCGA) and have successfully corrected for study-specific biases, enabling comparative analysis across studies. The normalized data are available for download via GitHub (at https://github.com/mskcc/RNAseqDB).

scholarly journals TP53 isoform junction reads based analysis in malignant and normal contexts

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Suleyman Vural ◽  
Lun-Ching Chang ◽  
Laura M. Yee ◽  
Dmitriy Sonkin
Keyword(s):  
Cancer Cell ◽  
Cancer Cell Line ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Wild Type ◽  
Suppressor Activity ◽  
Tumor Suppressor Activity ◽  
Cancer Genome Atlas ◽  
Alternative Isoforms

AbstractTP53 is one of the most frequently altered genes in cancer; it can be inactivated by a number of different mechanisms. NM_000546.6 (ENST00000269305.9) is by far the predominant TP53 isoform, however a few other alternative isoforms have been described to be expressed at much lower levels. To better understand patterns of TP53 alternative isoforms expression in cancer and normal samples we performed exon-exon junction reads based analysis of TP53 isoforms using RNA-seq data from The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), and Genotype-Tissue Expression (GTEx) project. TP53 C-terminal alternative isoforms have abolished or severely decreased tumor suppressor activity, and therefore, an increase in fraction of TP53 C-terminal alternative isoforms may be expected in tumors with wild type TP53. Despite our expectation that there would be increase of fraction of TP53 C-terminal alternative isoforms, we observed no substantial increase in fraction of TP53 C-terminal alternative isoforms in TCGA tumors and CCLE cancer cell lines with wild type TP53, likely indicating that TP53 C-terminal alternative isoforms expression cannot be reliably selected for during tumor progression.

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