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Related Concept Videos

Reducing Line Loss01:18

Reducing Line Loss

298
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss in...
298
Lossless Lines01:23

Lossless Lines

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In electrical engineering, a lossless transmission line is characterized by a purely imaginary propagation constant and a resistive characteristic impedance. The ABCD parameters, which describe the relationship between the input and output voltages and currents, indicate an equivalent π circuit with an imaginary series impedance and a shunt admittance. This results in a transmission line that, when the product of the phase constant (beta) and the length of the line is less than pi, exhibits...
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Downsampling01:20

Downsampling

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When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
528
Lossy Lines and Overvoltages01:22

Lossy Lines and Overvoltages

297
Transmission-line series resistance and shunt conductance cause three primary effects: attenuation, distortion, and power losses.
Attenuation
When constant series resistance and shunt conductance are present, voltage and current equations are modified. The propagation constant indicates that voltage and current waves consist of both forward and backward traveling components. These waves attenuate as they propagate, with the attenuation factor related to the resistance and conductance. In a...
297
Upsampling01:22

Upsampling

531
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
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ScaleQC: a scalable lossy to lossless solution for NGS data compression.

Rongshan Yu1,2, Wenxian Yang2

  • 1Digital Fujian Institute of Healthcare and Biomedical Big Data, School of Informatics, Xiamen University, Xiamen 316005, China.

Bioinformatics (Oxford, England)
|May 28, 2020
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Summary

ScaleQC offers scalable compression for Next Generation Sequencing quality values, reducing storage needs. This method achieves efficient lossless and lossy compression, adaptable for various applications.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Next Generation Sequencing (NGS) data quality values occupy significant storage space, even post-compression.
  • Existing compression methods often require trade-offs between data size and compression type (lossy vs. lossless).
  • The need for adaptable compression solutions that cater to diverse application requirements is critical.

Purpose of the Study:

  • To develop a novel compression solution for Next Generation Sequencing quality values that addresses storage limitations.
  • To introduce bit-stream level scalability for quality value compression, allowing dynamic data rate adjustment.
  • To achieve competitive compression performance in both lossless and lossy modes.

Main Methods:

  • Development of ScaleQC (Scalable Quality value Compression), a new compression algorithm for quality values.
  • Implementation of bit-stream level scalability, enabling truncation of compressed data without re-transcoding.
  • Integration of ScaleQC into SAMtools as a specialized quality value encoding mode for CRAM files.

Main Results:

  • ScaleQC provides scalable compression for quality values, significantly reducing storage requirements.
  • The algorithm achieves comparable compression efficiency to existing methods at both lossless and lossy data rates.
  • ScaleQC's bit-stream scalability allows for flexible data rate adjustments without costly re-processing.

Conclusions:

  • ScaleQC offers an effective and scalable solution for compressing Next Generation Sequencing quality values.
  • The developed method enhances data storage efficiency while maintaining data integrity and flexibility.
  • ScaleQC's integration with SAMtools facilitates its practical application in genomic data analysis workflows.