Nextflow 通道创建条件

如何解决Nextflow 通道创建条件

[Kasumi_H3K36,Kasumi_IgG,/mnt/Data/cut_and_tag/work/d0/3db2bde9eb1bdb0578073fb128bc4c/Kasumi_H3K36.no0.bedgraph]
[Kasumi_JMJD1C,/mnt/Data/cut_and_tag/work/b1/dffe2120acda5b05860e1a3bb0c1bf/Kasumi_JMJD1C.no0.bedgraph]
[Kasumi_NCOR1,/mnt/Data/cut_and_tag/work/9f/7c3680a1ff0ae0a5a27f42e1a27225/Kasumi_NCOR1.no0.bedgraph]
[Kasumi_IgG,/mnt/Data/cut_and_tag/work/21/1038cd4ecbc5b3f88da23ad1ee3147/Kasumi_IgG.no0.bedgraph]
[Kasumi_H4K5,/mnt/Data/cut_and_tag/work/3d/7b5239ab9dc83b00f992fea8926630/Kasumi_H4K5.no0.bedgraph]

这是我的频道视图之一。当第一个和第二个 ID 相同时，我试图创建一个新的控制通道，其余的作为示例通道。

解决方法

这是使用 branch 运算符的一种方法。我对字段的名称做了一些假设，但希望该模式与您要查找的内容相近：

nextflow.enable.dsl=2

Channel
    .of(
        ['Kasumi_H3K36','Kasumi_IgG',file('/mnt/Data/cut_and_tag/work/d0/3db2bde9eb1bdb0578073fb128bc4c/Kasumi_H3K36.no0.bedgraph')],['Kasumi_JMJD1C',file('/mnt/Data/cut_and_tag/work/b1/dffe2120acda5b05860e1a3bb0c1bf/Kasumi_JMJD1C.no0.bedgraph')],['Kasumi_NCOR1',file('/mnt/Data/cut_and_tag/work/9f/7c3680a1ff0ae0a5a27f42e1a27225/Kasumi_NCOR1.no0.bedgraph')],['Kasumi_IgG',file('/mnt/Data/cut_and_tag/work/21/1038cd4ecbc5b3f88da23ad1ee3147/Kasumi_IgG.no0.bedgraph')],['Kasumi_H4K5',file('/mnt/Data/cut_and_tag/work/3d/7b5239ab9dc83b00f992fea8926630/Kasumi_H4K5.no0.bedgraph')],) \
    .branch { sample1,sample2,bedgraph ->
        controls: sample1 == sample2
            return tuple( sample1,bedgraph )
        others: true
            return tuple( sample1,bedgraph )
    } \
    .set { inputs } 

inputs.controls.view { "controls: $it" } 
inputs.others.view { "others: $it" }

结果：

others: [Kasumi_H3K36,Kasumi_IgG,/mnt/Data/cut_and_tag/work/d0/3db2bde9eb1bdb0578073fb128bc4c/Kasumi_H3K36.no0.bedgraph]
controls: [Kasumi_IgG,/mnt/Data/cut_and_tag/work/21/1038cd4ecbc5b3f88da23ad1ee3147/Kasumi_IgG.no0.bedgraph]
others: [Kasumi_JMJD1C,/mnt/Data/cut_and_tag/work/b1/dffe2120acda5b05860e1a3bb0c1bf/Kasumi_JMJD1C.no0.bedgraph]
others: [Kasumi_NCOR1,/mnt/Data/cut_and_tag/work/9f/7c3680a1ff0ae0a5a27f42e1a27225/Kasumi_NCOR1.no0.bedgraph]
others: [Kasumi_H4K5,/mnt/Data/cut_and_tag/work/3d/7b5239ab9dc83b00f992fea8926630/Kasumi_H4K5.no0.bedgraph]

---

评论更新：

Channel
    .of(
        ['Kasumi_H3K36',file('/path/to/Kasumi_H3K36.no0.bedgraph')],file('/path/to/Kasumi_JMJD1C.no0.bedgraph')],file('/path/to/Kasumi_NCOR1.no0.bedgraph')],file('/path/to/Kasumi_IgG.no0.bedgraph')],file('/path/to/Kasumi_H4K5.no0.bedgraph')],['NB4_H3K36','NB4_IgG',file('/path/to/NB4_H3K36.no0.bedgraph')],['NB4_JMJD1C',file('/path/to/NB4_JMJD1C.no0.bedgraph')],['NB4_NCOR1',file('/path/to/NB4_NCOR1.no0.bedgraph')],['NB4_IgG',file('/path/to/NB4_IgG.no0.bedgraph')],['NB4_H4K5',file('/path/to/NB4_H4K5.no0.bedgraph')],) \
    .branch { test_sample,control_sample,bedgraph ->
        control_samples: test_sample == control_sample
            return tuple( control_sample,tuple( test_sample,bedgraph ) )
        test_samples: true
            return tuple( control_sample,bedgraph ) )
    } \
    .set { inputs }

inputs.test_samples
    .combine( inputs.control_samples,by: 0 ) \
    .map { group,test_tuple,control_tuple ->
        tuple( *test_tuple,*control_tuple )
    } \
    .view()

结果：

[Kasumi_H3K36,/path/to/Kasumi_H3K36.no0.bedgraph,/path/to/Kasumi_IgG.no0.bedgraph]
[Kasumi_JMJD1C,/path/to/Kasumi_JMJD1C.no0.bedgraph,/path/to/Kasumi_IgG.no0.bedgraph]
[Kasumi_NCOR1,/path/to/Kasumi_NCOR1.no0.bedgraph,/path/to/Kasumi_IgG.no0.bedgraph]
[Kasumi_H4K5,/path/to/Kasumi_H4K5.no0.bedgraph,/path/to/Kasumi_IgG.no0.bedgraph]
[NB4_H3K36,/path/to/NB4_H3K36.no0.bedgraph,NB4_IgG,/path/to/NB4_IgG.no0.bedgraph]
[NB4_JMJD1C,/path/to/NB4_JMJD1C.no0.bedgraph,/path/to/NB4_IgG.no0.bedgraph]
[NB4_NCOR1,/path/to/NB4_NCOR1.no0.bedgraph,/path/to/NB4_IgG.no0.bedgraph]
[NB4_H4K5,/path/to/NB4_H4K5.no0.bedgraph,/path/to/NB4_IgG.no0.bedgraph]