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

Kejie Li Yu Huining SunZhengyu OuyangSoumya NegiZhen GaoJing ZhuWanli Wang Yirui Chen Sarbottam Piya Wenxing HuMaria I ZavodszkyHima YalamanchiliShaolong CaoAndrew GehrkeMark SheehanDann HuhFergal CaseyXinmin Zhang Baohong 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
deep learning
machine learning
risk assessment
dna methylation
gene expression