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Related Concept Videos

Aliasing01:18

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are slanted or...
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the C=O, C=N, and C=C occur between 1600–1850 cm−1.
The...
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n) to the number of categories (k).

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An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
05:35

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Published on: September 20, 2022

False discovery rates in spectral identification.

Kyowon Jeong1, Sangtae Kim, Nuno Bandeira

  • 1Department of Electrical and Computer Engineering, University of California San Diego, San Diego, CA, USA.

BMC Bioinformatics
|November 27, 2012
PubMed
Summary
This summary is machine-generated.

Automated proteomics searches can overestimate accuracy. This study reveals the Target-Decoy Approach (TDA) may report false discovery rates (FDR) up to 10x lower than actual, impacting high-throughput proteomics data reliability.

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Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Bioinformatics

Background:

  • High-throughput proteomics relies on automated database searches for peptide and protein identification.
  • Manual validation of large-scale MS/MS data is infeasible.
  • The Target-Decoy Approach (TDA) is standard for estimating empirical False Discovery Rate (FDR).

Purpose of the Study:

  • To evaluate the accuracy of TDA in estimating empirical FDR in automated proteomics searches.
  • To identify potential biases and limitations in common TDA methodologies.
  • To provide recommendations for robust FDR estimation in high-throughput proteomics.

Main Methods:

  • Evaluation of various TDA variants using MS/MS spectra with a known 'true' FDR.
  • Comparative analysis of TDA performance across different database search contexts.
  • Assessment of the two-pass search strategy for proteomics data analysis.

Main Results:

  • TDA can significantly underestimate the true FDR, with false identifications sometimes exceeding reported values by over 10-fold.
  • Certain database search contexts may inherently lead to high false identification rates.
  • The two-pass search strategy emerged as a promising approach for improved accuracy.

Conclusions:

  • Current TDA practices may lead to unreliable FDR estimates in high-throughput proteomics.
  • Strict adherence to rigorous TDA procedures is crucial for data integrity.
  • Recommendations are provided to enhance the robustness and reproducibility of FDR estimation in proteomics studies.