The Analysis Workflow: Finding the Entities

2000 ◽  
pp. 79-105
Author(s):  
John Hunt
Keyword(s):  
Analysis Workflow

scholarly journals Sequential filtering for clinically relevant variants as a method for clinical interpretation of whole exome sequencing findings in glioma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Ege Ülgen ◽  
Özge Can ◽  
Kaya Bilguvar ◽  
Cemaliye Akyerli Boylu ◽  
Şirin Kılıçturgay Yüksel ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Clinical Analysis ◽  
Clinical Interpretation ◽  
Germline Variants ◽  
Whole Exome ◽  
Gene Level ◽  
Analysis Workflow ◽  
Tumor Mutational Burden ◽  
Diffuse Gliomas

Abstract Background In the clinical setting, workflows for analyzing individual genomics data should be both comprehensive and convenient for clinical interpretation. In an effort for comprehensiveness and practicality, we attempted to create a clinical individual whole exome sequencing (WES) analysis workflow, allowing identification of genomic alterations and presentation of neurooncologically-relevant findings. Methods The analysis workflow detects germline and somatic variants and presents: (1) germline variants, (2) somatic short variants, (3) tumor mutational burden (TMB), (4) microsatellite instability (MSI), (5) somatic copy number alterations (SCNA), (6) SCNA burden, (7) loss of heterozygosity, (8) genes with double-hit, (9) mutational signatures, and (10) pathway enrichment analyses. Using the workflow, 58 WES analyses from matched blood and tumor samples of 52 patients were analyzed: 47 primary and 11 recurrent diffuse gliomas. Results The median mean read depths were 199.88 for tumor and 110.955 for normal samples. For germline variants, a median of 22 (14–33) variants per patient was reported. There was a median of 6 (0–590) reported somatic short variants per tumor. A median of 19 (0–94) broad SCNAs and a median of 6 (0–12) gene-level SCNAs were reported per tumor. The gene with the most frequent somatic short variants was TP53 (41.38%). The most frequent chromosome-/arm-level SCNA events were chr7 amplification, chr22q loss, and chr10 loss. TMB in primary gliomas were significantly lower than in recurrent tumors (p = 0.002). MSI incidence was low (6.9%). Conclusions We demonstrate that WES can be practically and efficiently utilized for clinical analysis of individual brain tumors. The results display that NOTATES produces clinically relevant results in a concise but exhaustive manner.

scholarly journals Analysis workflow of publicly available RNA-sequencing datasets

2021 ◽  
Vol 2 (2) ◽  
pp. 100478
Author(s):  
Pablo Sanchis ◽  
Rosario Lavignolle ◽  
Mercedes Abbate ◽  
Sofía Lage-Vickers ◽  
Elba Vazquez ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Analysis Workflow

scholarly journals Correction to Fully Automated Sample Processing and Analysis Workflow for Low-Input Proteome Profiling

2021 ◽  
Author(s):  
Yiran Liang ◽  
Hayden Acor ◽  
Michaela A. McCown ◽  
Andikan J. Nwosu ◽  
Hannah Boekweg ◽  
...  
Keyword(s):  
Sample Processing ◽  
Proteome Profiling ◽  
Low Input ◽  
Analysis Workflow

scholarly journals Meta-Analysis of Oxidative Transcriptomes in Insects

Antioxidants ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 345
Author(s):  
Hidemasa Bono
Keyword(s):  
Oxidative Stress ◽  
Stress Response ◽  
Meta Analysis ◽  
Adherens Junction ◽  
Enrichment Analysis ◽  
Oxidative Stress Response ◽  
Insect Species ◽  
Rna Seq ◽  
Manual Curation ◽  
Analysis Workflow

Data accumulation in public databases has resulted in extensive use of meta-analysis, a statistical analysis that combines the results of multiple studies. Oxidative stress occurs when there is an imbalance between free radical activity and antioxidant activity, which can be studied in insects by transcriptome analysis. This study aimed to apply a meta-analysis approach to evaluate insect oxidative transcriptomes using publicly available data. We collected oxidative stress response-related RNA sequencing (RNA-seq) data for a wide variety of insect species, mainly from public gene expression databases, by manual curation. Only RNA-seq data of Drosophila melanogaster were found and were systematically analyzed using a newly developed RNA-seq analysis workflow for species without a reference genome sequence. The results were evaluated by two metric methods to construct a reference dataset for oxidative stress response studies. Many genes were found to be downregulated under oxidative stress and related to organ system process (GO:0003008) and adherens junction organization (GO:0034332) by gene enrichment analysis. A cross-species analysis was also performed. RNA-seq data of Caenorhabditis elegans were curated, since no RNA-seq data of insect species are currently available in public databases. This method, including the workflow developed, represents a powerful tool for deciphering conserved networks in oxidative stress response.

scholarly journals ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra

2019 ◽  
Vol 35 (21) ◽  
pp. 4356-4363 ◽  
Author(s):  
Gaëlle Lefort ◽  
Laurence Liaubet ◽  
Cécile Canlet ◽  
Patrick Tardivel ◽  
Marie-Christine Père ◽  
...  
Keyword(s):  
Metabolic Pathways ◽  
Nmr Spectra ◽  
Complex Mixture ◽  
R Package ◽  
Statistical Analyses ◽  
Supplementary Information ◽  
Automatic Identification ◽  
Analysis Workflow ◽  
Expert Analysis ◽  
New Biomarkers

Abstract Motivation In metabolomics, the detection of new biomarkers from Nuclear Magnetic Resonance (NMR) spectra is a promising approach. However, this analysis remains difficult due to the lack of a whole workflow that handles spectra pre-processing, automatic identification and quantification of metabolites and statistical analyses, in a reproducible way. Results We present ASICS, an R package that contains a complete workflow to analyse spectra from NMR experiments. It contains an automatic approach to identify and quantify metabolites in a complex mixture spectrum and uses the results of the quantification in untargeted and targeted statistical analyses. ASICS was shown to improve the precision of quantification in comparison to existing methods on two independent datasets. In addition, ASICS successfully recovered most metabolites that were found important to explain a two level condition describing the samples by a manual and expert analysis based on bucketing. It also found new relevant metabolites involved in metabolic pathways related to risk factors associated with the condition. Availability and implementation ASICS is distributed as an R package, available on Bioconductor. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Analysis workflow to assess de novo genetic variants from human whole-exome sequencing

2021 ◽  
Vol 2 (1) ◽  
pp. 100383
Author(s):  
Nicholas S. Diab ◽  
Spencer King ◽  
Weilai Dong ◽  
Garrett Allington ◽  
Amar Sheth ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Genetic Variants ◽  
De Novo ◽  
Whole Exome ◽  
Analysis Workflow

scholarly journals Benchmarking cryo-EM Single Particle Analysis Workflow

2018 ◽  
Vol 5 ◽  
Author(s):  
Laura Y. Kim ◽  
William J. Rice ◽  
Edward T. Eng ◽  
Mykhailo Kopylov ◽  
Anchi Cheng ◽  
...  
Keyword(s):  
Single Particle ◽  
Particle Analysis ◽  
Single Particle Analysis ◽  
Analysis Workflow
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