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Related Concept Videos

Genomics02:02

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...

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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Atlas2 Cloud: a framework for personal genome analysis in the cloud.

Uday S Evani1, Danny Challis, Jin Yu

  • 1The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA.

BMC Genomics
|November 9, 2012
PubMed
Summary
This summary is machine-generated.

Cloud computing and Software-as-a-Service (SaaS) can overcome computational bottlenecks in personal genome analysis. Enabling user-friendly pipelines on cloud platforms facilitates broader access to genomic data interpretation for research and clinical applications.

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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Area of Science:

  • Genomics
  • Bioinformatics
  • Cloud Computing

Background:

  • Genomic sequencing technologies have advanced, leading to widespread data dissemination.
  • Limited computational infrastructure and bioinformatics expertise hinder widespread genomic analysis.
  • Cloud computing and Software-as-a-Service (SaaS) offer potential solutions to these challenges.

Purpose of the Study:

  • To evaluate the feasibility of cloud-based personal genome analysis using the Atlas2 pipeline.
  • To assess the utility of community and commercial cloud platforms for genomic data processing.
  • To analyze the cost-effectiveness of cloud solutions for large-scale genomic datasets.

Main Methods:

  • Implementation of the Atlas2 Cloud pipeline on Genboree Workbench (community cloud) and Amazon Web Services (commercial cloud).
  • Case study of personal genome analysis using the Atlas2 Genboree pipeline.
  • Detailed cost analysis for running Atlas2 on Amazon Web Services with whole exome capture data.

Main Results:

  • Successful deployment of the Atlas2 Cloud pipeline on both community and commercial cloud platforms.
  • Demonstrated personal genome analysis capabilities via the Atlas2 Genboree pipeline.
  • Provided cost projections for storage, compute, and I/O for large datasets on Atlas2 Amazon.

Conclusions:

  • Web interfaces and optimized pipelines enhance cloud computing adoption for personal genome analysis.
  • Widespread adoption for large-scale projects requires paradigm shifts in tool development, standard operating procedures, and funding.
  • Cloud solutions show promise for democratizing access to genomic data analysis.