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Related Concept Videos

Sample Handling01:02

Sample Handling

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Transportation of samples from the collection point to the laboratory, as well as storage and preservation techniques, are crucial for maintaining sample integrity and ensuring accurate and reliable test results.
Samples should be transported carefully from collection points to the laboratory. They should be properly sealed and clearly labeled to prevent cross-contamination. To preserve the sample integrity, optimal temperature conditions during transport are essential. This could involve using...
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Sample Preparation for Analysis: Advanced Techniques01:08

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Accurate analysis of complex samples often requires advanced preparation techniques to achieve reliable and reproducible results. Samples containing inorganic or organic materials can be challenging to dissolve or decompose effectively. Standard sample preparation methods include acid digestion, fusion, dry ashing, and wet digestion.
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Sample Preparation for Analysis: Overview01:21

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Sample preparation is an essential step in the analytical process. It involves preparing a sample so that it can be analyzed accurately. The goal is to extract the analyte, the substance you want to measure, from the sample while removing any components that may interfere with the analysis. Sample preparation techniques vary depending on the physical state of the sample.
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2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)01:19

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Heteronuclear single-quantum correlation spectroscopy (HSQC) is a 2D NMR technique that reveals one-bond correlations between hydrogen and a heteronucleus. The HSQC experiment is similar to the heteronuclear correlation experiment (HETCOR) but is more sensitive. In the HSQC spectrum, the proton chemical shift is plotted on the horizontal F2 axis, while the 13C chemical shift is plotted on the vertical F1 axis. The corresponding proton and 13C spectra are also shown. The HSQC contour plot does...
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Sampling Methods: Overview01:06

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A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
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Sampling Methods: Sample Types01:18

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Sampling materials are classified into three main types: solid, liquid, and gas.
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HYSYS: have you swapped your samples?

Jan Schröder1,2,3, Vincent Corbin1,4, Anthony T Papenfuss1,4,3,5

  • 1Bioinformatics Division, The Walter & Eliza Hall Institute, Parkville 3052, Australia.

Bioinformatics (Oxford, England)
|December 23, 2016
PubMed
Summary
This summary is machine-generated.

A new method, HYSYS, identifies sample swaps and contamination in cancer genomics studies by analyzing homozygous single nucleotide polymorphism (SNP) concordance. This ensures data integrity in complex clinical sequencing data.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Research

Background:

  • Cancer genomics studies frequently use genomics assays on patient cohorts.
  • Clinical sequencing involves complex, manual steps prone to sample mislabeling.
  • Existing methods to detect sample swaps in cancer studies are limited.

Purpose of the Study:

  • To introduce HYSYS, a novel method for detecting sample swaps and contamination.
  • To provide tools for estimating sample relatedness and flagging potential errors.
  • To improve the reliability of cancer genomics data.

Main Methods:

  • HYSYS estimates sample relatedness using the concordance of homozygous single nucleotide polymorphisms (SNPs).
  • The method leverages the stability of germline homozygous variants.
  • It is unaffected by somatic changes like loss of heterozygosity.

Main Results:

  • HYSYS successfully identifies sample swaps and contamination.
  • The method includes visualization and a testing framework.
  • Its utility was demonstrated on a small cancer cohort.

Conclusions:

  • HYSYS offers a simple and effective solution for sample integrity in cancer genomics.
  • Accurate sample tracking is crucial for reliable clinical sequencing data.
  • The developed tools enhance the quality control of cancer genomic analyses.