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scRNASequest: an ecosystem of scRNA-seq analysis, visualization, and publishing.

Kejie LiYu Huining SunZhengyu OuyangSoumya NegiZhen GaoJing ZhuWanli WangYirui ChenSarbottam PiyaWenxing HuMaria I ZavodszkyHima YalamanchiliShaolong CaoAndrew GehrkeMark SheehanDann HuhFergal CaseyXinmin ZhangBaohong Zhang
Published in: BMC genomics (2023)
We developed scRNASequest, an end-to-end pipeline for single-cell RNA-seq data analysis, visualization, and publishing. The source code under MIT open-source license is provided at https://github.com/interactivereport/scRNASequest . We also prepared a bookdown tutorial for the installation and detailed usage of the pipeline: https://interactivereport.github.io/scRNAsequest/tutorial/docs/ . Users have the option to run it on a local computer with a Linux/Unix system including MacOS, or interact with SGE/Slurm schedulers on high-performance computing (HPC) clusters.
Keyphrases
  • rna seq
  • single cell
  • data analysis
  • high throughput
  • climate change
  • gene expression
  • risk assessment
  • human health
  • genome wide