"Computational analysis of high throughout sequencing data-Applications to DNA and RNA studies"

2010 ◽  
Author(s):  
Ankit Malhotra
Keyword(s):  
Computational Analysis ◽  
Sequencing Data ◽  
Dna And Rna ◽  
High Throughout Sequencing

scholarly journals Genopo: a nanopore sequencing analysis toolkit for portable Android devices

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Hiruna Samarakoon ◽  
Sanoj Punchihewa ◽  
Anjana Senanayake ◽  
Jillian M. Hammond ◽  
Igor Stevanovski ◽  
...  
Keyword(s):  
Computational Analysis ◽  
Smartphone Application ◽  
Sequencing Analysis ◽  
Nanopore Sequencing ◽  
Android Application ◽  
Sequencing Data ◽  
Human Coronavirus ◽  
Dna And Rna ◽  
Bioinformatics Tools

Abstract The advent of portable nanopore sequencing devices has enabled DNA and RNA sequencing to be performed in the field or the clinic. However, advances in in situ genomics require parallel development of portable, offline solutions for the computational analysis of sequencing data. Here we introduce Genopo, a mobile toolkit for nanopore sequencing analysis. Genopo compacts popular bioinformatics tools to an Android application, enabling fully portable computation. To demonstrate its utility for in situ genome analysis, we use Genopo to determine the complete genome sequence of the human coronavirus SARS-CoV-2 in nine patient isolates sequenced on a nanopore device, with Genopo executing this workflow in less than 30 min per sample on a range of popular smartphones. We further show how Genopo can be used to profile DNA methylation in a human genome sample, illustrating a flexible, efficient architecture that is suitable to run many popular bioinformatics tools and accommodate small or large genomes. As the first ever smartphone application for nanopore sequencing analysis, Genopo enables the genomics community to harness this cheap, ubiquitous computational resource.

Computational Analysis of DNA and RNA Sequencing Data Obtained from Liquid Biopsies

2019 ◽  
pp. 347-368 ◽  
Author(s):  
Francesco Marass ◽  
Francesc Castro-Giner ◽  
Barbara Maria Szczerba ◽  
Katharina Jahn ◽  
Jack Kuipers ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Computational Analysis ◽  
Sequencing Data ◽  
Liquid Biopsies ◽  
Dna And Rna

Survey of the immunogenomic landscape of solid tumors through clinical DNA and RNA sequencing.

2019 ◽  
Vol 37 (8_suppl) ◽  
pp. 153-153
Author(s):  
Denise Lau ◽  
Alan Chang ◽  
Jason Perera ◽  
Ariane Lozac'hmeur ◽  
Alexandria Bobe ◽  
...  
Keyword(s):  
Dna Sequencing ◽  
Solid Tumors ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Immune Activation ◽  
Clinical Care ◽  
Relative Proportion ◽  
Tumor Infiltration ◽  
Sequencing Data ◽  
Dna And Rna

153 Background: In the past decade, immunotherapy has emerged as an important new modality in cancer treatment. However, studies have shown that only a fraction of patients will experience any clinical benefit when treated with immune checkpoint blockade drugs. Given the cost and potent adverse events associated with immunotherapy, the need for effective biomarkers is clear. We sought to understand the role of key immunotherapy biomarkers, like tumor mutational burden (TMB), microsatellite instability (MSI), and PD-L1 immunohistochemistry (IHC), in the context of the greater immunogenomic landscape of solid tumors in patients. Methods: We analyzed data from a cohort of 500 patients across 10 cancer types who received the Tempus xT 595 gene targeted DNA sequencing assay and whole transcriptome sequencing assay as part of their clinical care. We determined the TMB, MSI status, and neoantigen load for each sample using the DNA sequencing data. We used the RNA expression data to evaluate immune activation and tumor infiltration by determining the expression of inflammatory gene signatures and estimating the relative proportion of key immune cell types. Results: Integrative analysis of the DNA and RNA sequencing data showed that the immunogenicity of the tumor, as measured by TMB or neoantigen load, correlates with levels of immune activation and tumor infiltration. Inflammatory immune cells, like CD8 T cells and M1 polarized macrophages, were significantly higher in TMB-high samples; while non-inflammatory immune cells, like monocytes, were significantly lower in TMB-high samples. Additionally, samples could be clustered into immunologically active “hot” tumors or immunologically silent “cold” tumors based on gene expression. The immunologically “hot” population was enriched for samples that were TMB-high, MSI-high or PD-L1 IHC positive. Conclusions: Paired next generation DNA and RNA sequencing assays allows for the identification of patients that have immunologically active tumors that lack traditional immunotherapy biomarkers. These patients represent an interesting new population who may potentially benefit from immunotherapy.

scholarly journals Metannot: A succinct data structure for compression of colors in dynamic de Bruijn graphs

2017 ◽  
Author(s):  
Harun Mustafa ◽  
André Kahles ◽  
Mikhail Karasikov ◽  
Gunnar Rätsch
Keyword(s):  
Data Structure ◽  
High Throughput Sequencing ◽  
Sequence Data ◽  
Data Sets ◽  
Sequencing Data ◽  
Dynamic Data ◽  
De Bruijn Graphs ◽  
Dna And Rna ◽  
Succinct Data Structure ◽  
Dynamic Data Structure

AbstractMuch of the DNA and RNA sequencing data available is in the form of high-throughput sequencing (HTS) reads and is currently unindexed by established sequence search databases. Recent succinct data structures for indexing both reference sequences and HTS data, along with associated metadata, have been based on either hashing or graph models, but many of these structures are static in nature, and thus, not well-suited as backends for dynamic databases.We propose a parallel construction method for and novel application of the wavelet trie as a dynamic data structure for compressing and indexing graph metadata. By developing an algorithm for merging wavelet tries, we are able to construct large tries in parallel by merging smaller tries constructed concurrently from batches of data.When compared against general compression algorithms and those developed specifically for graph colors (VARI and Rainbowfish), our method achieves compression ratios superior to gzip and VARI, converging to compression ratios of 6.5% to 2% on data sets constructed from over 600 virus genomes.While marginally worse than compression by bzip2 or Rainbowfish, this structure allows for both fast extension and query. We also found that additionally encoding graph topology metadata improved compression ratios, particularly on data sets consisting of several mutually-exclusive reference genomes.It was also observed that the compression ratio of wavelet tries grew sublinearly with the density of the annotation matrices.This work is a significant step towards implementing a dynamic data structure for indexing large annotated sequence data sets that supports fast query and update operations. At the time of writing, no established standard tool has filled this niche.

scholarly journals NanoR: a user-friendly R package to analyze and compare nanopore sequencing data

2019 ◽  
Author(s):  
Davide Bolognini ◽  
Niccolò Bartalucci ◽  
Alessandra Mingrino ◽  
Alessandro Maria Vannucchi ◽  
Alberto Magi
Keyword(s):  
Real Time ◽  
Low Cost ◽  
R Package ◽  
Sequencing Data ◽  
High Performing ◽  
Dna And Rna ◽  
Oxford Nanopore ◽  
The One ◽  
User Friendly ◽  
Oxford Nanopore Technologies

AbstractMinION and GridION X5 from Oxford Nanopore Technologies are devices for real-time DNA and RNA sequencing. On the one hand, MinION is the only real-time, low cost and portable sequencing device and, thanks to its unique properties, is becoming more and more popular among biologists; on the other, GridION X5, mainly for its costs, is less widespread but highly suitable for researchers with large sequencing projects. Despite the fact that Oxford Nanopore Technologies’ devices have been increasingly used in the last few years, there is a lack of high-performing and user-friendly tools to handle the data outputted by both MinION and GridION X5 platforms. Here we present NanoR, a cross-platform R package designed with the purpose to simplify and improve nanopore data visualization. Indeed, NanoR is built on few functions but overcomes the capabilities of existing tools to extract meaningful informations from MinION sequencing data; in addition, as exclusive features, NanoR can deal with GridION X5 sequencing outputs and allows comparison of both MinION and GridION X5 sequencing data in one command. NanoR is released as free package for R at https://github.com/davidebolo1993/NanoR.

scholarly journals Escape from nonsense mediated decay associates with anti-tumor immunogenicity

2019 ◽  
Author(s):  
Kevin Litchfield ◽  
James Reading ◽  
Emilia Lim ◽  
Hang Xu ◽  
Po Liu ◽  
...  
Keyword(s):  
Clinical Benefit ◽  
Adoptive Cell Therapy ◽  
Open Reading Frames ◽  
Escape Mutation ◽  
Sequencing Data ◽  
Cell Reactivity ◽  
Specific Expression ◽  
Nonsense Mediated Decay ◽  
Dna And Rna ◽  
T Cell Reactivity

AbstractFrameshift insertion/deletions (fs-indels) are an infrequent but potentially highly immunogenic mutation subtype. Although fs-indel transcripts are susceptible to degradation through the non-sense mediated decay (NMD) pathway, we hypothesise that some fs-indels escape degradation and lead to an increased abundance of tumor specific neoantigens, that are highly distinct from self. We analysed matched DNA and RNA sequencing data from TCGA, and five separate melanoma cohorts treated with immunotherapy. Using allele-specific expression analysis we show that expressed fs-indels were enriched in genomic positions predicted to escape NMD, and associated with higher protein expression, consistent with degradation escape (“NMD-escape”). Across four independent cohorts, fs-indel NMD-escape mutations were found to be significantly associated with clinical benefit to checkpoint inhibitor (CPI) therapy (Pmeta=0.0039), a stronger association than either nsSNV (Pmeta=0.073) or fs-indel (Pmeta=0.064) count. NMD-escape mutations were additionally shown to have independent predictive power in the “low-TMB” setting, and may serve as a biomarker to rescue patients judged ineligible for CPI based on overall TMB, but still with a high chance of response (low-TMB cohort: NMD-escape-positive % clinical benefit=53%, NMD-escape-negative % clinical benefit=16%, P=0.0098). Furthermore, in an adoptive cell therapy (ACT) treated cohort, NMD-escape mutation count was the most significant biomarker associated with clinical benefit (P=0.021). Analysis of functional T-cell reactivity screens from recent personalized vaccine and CPI studies shows direct evidence of fs-indel derived neoantigens eliciting patient anti-tumor immune response (n=15). We additionally observe a subset of fs-indel mutations, with highly elongated neo open reading frames, which are found to be significantly enriched for immunogenic reactivity in these patient studies (P=0.0032). Finally, consistent with the potency of NMD-escape derived neo-antigens and ongoing immune-editing, NMD-escape fs-indels appear to be under negative selective pressure in untreated TCGA cases. Given the strongly immunogenic potential, and relatively rare nature of NMD-escape fs-indels, these alterations may be attractive candidates in immunotherapy biomarker optimisation and neoantigen ACT or vaccine strategies.

scholarly journals Sensitive detection of circular DNAs at single-nucleotide resolution using guided realignment of partially aligned reads

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Iñigo Prada-Luengo ◽  
Anders Krogh ◽  
Lasse Maretty ◽  
Birgitte Regenberg
Keyword(s):  
Real Data ◽  
Circle Map ◽  
Sequencing Data ◽  
Rna Detection ◽  
Short Read ◽  
Circular Dna ◽  
Dna And Rna ◽  
Command Line Tool ◽  
Circular Dnas ◽  
Nucleotide Resolution

Abstract Background Circular DNA has recently been identified across different species including human normal and cancerous tissue, but short-read mappers are unable to align many of the reads crossing circle junctions hence limiting their detection from short-read sequencing data. Results Here, we propose a new method, Circle-Map that guides the realignment of partially aligned reads using information from discordantly mapped reads to map the short unaligned portions using a probabilistic model. We compared Circle-Map to similar up-to-date methods for circular DNA and RNA detection and we demonstrate how the approach implemented in Circle-Map dramatically increases sensitivity for detection of circular DNA on both simulated and real data while retaining high precision. Conclusion Circle-Map is an easy-to-use command line tool that implements the required pipeline to accurately detect circular DNA from circle enriched next generation sequencing experiments. Circle-Map is implemented in python3.6 and it is freely available at https://github.com/iprada/Circle-Map.

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