RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control. workflowrna-seqpipelinenextflowrnanf-core UpdatedJan 28, 2025 Nextflow theislab/single-cell-best-practices Star827
On release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to be...
自己在参考大牛的基础上,总结了RNAseq比对流程pipeline脚本。在做好前期准备工作后,可以一步完成从fastq到表达矩阵的所有步骤,目前仅支持human Bulk RNAseq数据,后续有机会会继续学习、完善,扩展更多选项。十分欢迎大家参考使用,并提供建议与意见。 https://github.com/lishensuo/fq2count 或者https://gitee.com/li-...
一个完整的RNA-seq分析pipeline之HISAT2+ StrintTie+ Ballgown以及StringTie和Kallisto的比较(包括得到FPKM、TPM、readscounts) 最重要的参考链接 https://github.com/griffithlab/rnaseq_tutorial 由于可能国内进不去,我这里将关键代码保存下来。 目录截图 image.png 得到FPKM、TPM、Readscounts cd/workspace/rnaseq/...
根据xCELL包的github官网https://github.com/dviraran/xCell中提到,注意rowname需要是 gene ,而不是像cibersort中gene需要是首列。 2,运行xCELL 可以按照github使用 rawEnrichmentAnalysis ,transformScores 和 spillOver分步骤运算。 这里可以使用作者包装好的pipeline的方式运行(推荐)。
如果你简单谷歌搜索关键词:gatk best practices pipeline rna-seq 会搜索到大量过期的教程: 2014年5月6日 -Best Practicesworkflow forRNAseqhttps://gist.github.com/PoisonAlien/c6c03539cf4b1ac41cf1 2016年10月27日 -https://www.biostars.org/p/219281/ ...
HiRES_preprocess_pipeline分析代码需要hickit(https://github.com/lh3/hickit/) Dip-C(https://github.com/tanlongzhi/dip-c)和CHARMtools(https://github.com/skelviper/CHARMtools) . 同时,还需要对应的物种的参考基因组和注释文件。 cd HiRES_preprocess_pipelinevim config.yaml ...
SPEAQeasy workflow diagram.A simplified workflow diagram for each pipeline execution. The red box indicates the FASTQ files are inputs to the pipeline; green coloring denotes major output files from the pipeline; the remaining boxes represent computational steps. Yellow-colored steps are optional or ...
The final step in our pipeline analysis is the detection of DE-genes. Recently, Soneson et al.31benchmarked 36 DE approaches and found that edgeR27, MAST35, limma-trend36and even the T-Test performed well. Moreover, they found that for edgeR, it is important to incorporate an estimate ...
We present pipeComp (https://github.com/plger/pipeComp), a flexible R framework for pipeline comparison handling interactions between analysis steps and relying on multi-level evaluation metrics. We apply it to the benchmark of single-cell RNA-sequencing analysis pipelines using simulated and real...