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ddSeeker: a tool for processing Bio-Rad ddSEQ single cell RNA-seq data
- Source :
- BMC Genomics, Vol 19, Iss 1, Pp 1-7 (2018), BMC Genomics
- Publication Year :
- 2018
- Publisher :
- Springer Science and Business Media LLC, 2018.
-
Abstract
- Background New single-cell isolation technologies are facilitating studies on the transcriptomics of individual cells. Bio-Rad ddSEQ is a droplet-based microfluidic system that, when coupled with downstream Illumina library preparation and sequencing, enables the monitoring of thousands of genes per cell. Sequenced reads show unique features that do not permit the use of freely available tools to perform single cell demultiplexing. Results We present ddSeeker, a tool to perform initial processing and quality metrics of reads generated through Bio-Rad ddSEQ/Illumina experiments. Its application to the Illumina test dataset demonstrates that ddSeeker performs better than Illumina BaseSpace software, enabling a higher recovery of valid reads. We also show its utility in the analysis of an in-house dataset including two read sets characterized by low and high sequencing quality. ddSeeker and its source code are available at https://github.com/cgplab/ddSeeker. Conclusions ddSeeker is a freely available tool to perform initial processing and quality metrics of reads generated through Bio-Rad ddSEQ/Illumina single cell transcriptomic experiments. Electronic supplementary material The online version of this article (10.1186/s12864-018-5249-x) contains supplementary material, which is available to authorized users.
- Subjects :
- 0301 basic medicine
Source code
lcsh:QH426-470
Bioinformatics
lcsh:Biotechnology
Library preparation
Single cell transcriptomics
media_common.quotation_subject
RNA-Seq
Computational biology
Biology
03 medical and health sciences
Software
lcsh:TP248.13-248.65
scRNA-seq
Genetics
Isolation (database systems)
media_common
Sequence Analysis, RNA
business.industry
Gene Expression Profiling
Computational Biology
lcsh:Genetics
030104 developmental biology
RNA
Single-Cell Analysis
DNA microarray
Transcriptome
business
Algorithms
Single-cell transcriptomics
Biotechnology
Subjects
Details
- ISSN :
- 14712164
- Volume :
- 19
- Database :
- OpenAIRE
- Journal :
- BMC Genomics
- Accession number :
- edsair.doi.dedup.....9eef3c985748db38602d3884c336ca68