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Related Concept Videos

RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

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Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
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SbacHTS: spatial background noise correction for high-throughput RNAi screening.

Rui Zhong1, Min Soo Kim, Michael A White

  • 1Quantitative Biomedical Research Center, Department of Clinical Science, Harold C. Simmons Comprehensive Cancer Center and Department of Cell Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.

Bioinformatics (Oxford, England)
|July 2, 2013
PubMed
Summary

Spatial background noise in high-throughput screening can skew results. Our new software, SbacHTS, effectively corrects these errors, improving accuracy and enhancing the detection of drug targets and gene functions.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Drug Discovery

Background:

  • High-throughput screening (HTS) is crucial for identifying drug targets and gene functions.
  • HTS experiments generate large datasets from numerous plates, susceptible to spatial background noise.
  • This noise can vary across plates, impacting measurement accuracy and screening outcomes.

Purpose of the Study:

  • To develop and validate a software tool for correcting spatial background noise in HTS.
  • To improve the accuracy and reliability of data generated from HTS experiments.

Main Methods:

  • Development of SbacHTS (Spatial background noise correction for High-Throughput RNAi Screening) software.
  • Implementation within the Galaxy open-source framework, providing a web-accessible interface.
  • Utilizing SbacHTS for visualization, estimation, and correction of spatial background noise.

Main Results:

  • SbacHTS effectively detects and corrects spatial background noise in HTS data.
  • The software enhances the signal-to-noise ratio, leading to more reliable measurements.
  • Statistical detection power is significantly improved, aiding in the identification of significant findings.

Conclusions:

  • SbacHTS offers a robust solution for mitigating spatial background noise in HTS.
  • The software improves data quality, leading to more successful drug target discovery and gene function assignment.
  • Accessible via a user-friendly web interface, SbacHTS facilitates broader adoption in HTS research.