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ddSeeker: a tool for processing Bio-Rad ddSEQ single cell RNA-seq data.

Dario Romagnoli1, Giulia Boccalini2, Martina Bonechi2

  • 1Bioinformatics Unit, Hospital of Prato, Prato, Italy.

BMC Genomics
|December 26, 2018
PubMed
Summary
This summary is machine-generated.

A new tool, ddSeeker, enhances single-cell transcriptomic analysis by improving the processing of Bio-Rad ddSEQ/Illumina sequencing reads. This software offers better performance than existing methods for demultiplexing and quality control.

Keywords:
BioinformaticsSingle-cell transcriptomicsscRNA-seq

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Advancements in single-cell isolation technologies enable transcriptomic studies of individual cells.
  • The Bio-Rad ddSEQ system, combined with Illumina sequencing, allows for high-throughput gene expression analysis.
  • Unique read features from ddSEQ/Illumina experiments pose challenges for existing demultiplexing tools.

Purpose of the Study:

  • To develop and present ddSeeker, a novel computational tool.
  • To address the need for specialized software for processing Bio-Rad ddSEQ/Illumina single-cell RNA-sequencing data.
  • To provide a solution for accurate single-cell demultiplexing and quality assessment.

Main Methods:

  • Development of the ddSeeker software tool.
  • Evaluation of ddSeeker using an Illumina test dataset.
  • Assessment of ddSeeker's performance on in-house datasets with varying sequencing quality.

Main Results:

  • ddSeeker demonstrates superior performance compared to Illumina BaseSpace software.
  • The tool achieves higher recovery rates of valid sequencing reads.
  • ddSeeker effectively processes datasets with both low and high sequencing quality.

Conclusions:

  • ddSeeker is a valuable, freely available tool for the initial processing and quality control of Bio-Rad ddSEQ/Illumina single-cell transcriptomic data.
  • The software facilitates more robust analysis of single-cell gene expression.
  • ddSeeker improves the reliability of transcriptomic studies at the single-cell level.