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ST Pipeline: an automated pipeline for spatial mapping of unique transcripts
José Fernández Navarro1, Joel Sjöstrand1, Fredrik Salmén1
1Division of Gene Technology, School of Biotechnology, Royal Institute of Technology (KTH), SE-106 91 Science for Life Laboratory, Solna, Sweden.
Bioinformatics (Oxford, England)
|April 12, 2017
Summary
A new pipeline automates RNA sequencing (RNA-seq) data processing for spatial transcriptomics, enabling efficient analysis of transcript locations within tissues. This tool simplifies complex spatial transcriptomics data for downstream research.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- RNA sequencing (RNA-seq) techniques are increasingly used for transcriptomics.
- Spatial transcriptomics offers spatial mapping of transcripts, adding complexity to data analysis.
- Novel tools and algorithms are needed for efficient and accurate spatial transcriptomics data processing.
Purpose of the Study:
- To present a pipeline for processing RNA-seq data from spatial transcriptomics experiments.
- To generate datasets suitable for downstream analysis from spatial transcriptomics data.
Main Methods:
- Development of an automated pipeline for spatial transcriptomics data processing.
- Implementation of algorithms for efficient and accurate data handling.
Main Results:
- The pipeline automatically and efficiently processes RNA-seq data from spatial transcriptomics.
- Generated datasets are suitable for downstream analysis.
Conclusions:
- The presented pipeline addresses the need for efficient processing of complex spatial transcriptomics data.
- The open-source pipeline facilitates advancements in spatial transcriptomics research.