在特定列中保留具有值的行?
Keep rows with valus in specific columns?
我有一个像下面这样的 table 合并了多个数据,我想只保留在“-log10.qvalue”列中存在值的行。
输入:
chr_enhancer Start_enhancer End_enhancer source_enhancer.x source_marks.x -log10.qvalue.x source_enhancer.y -log10.qvalue.y source_enhancer -log10.qvalue
chr1 100036100 100036650 Reilly_Hu_12Opcw_H3K4me2_rep1_2_merge . . Reilly_Hu_12Opcw_H3K4me2_rep1_2_merge . Reilly_Hu_12Opcw_H3K4me2_rep1_2_merge .
chr1 100042226 100043575 Reilly_Hu_12Fpcw_H3K4me2_rep1_2_merge Fetalbrain.H3K4me1_narrow_peak_2501 2.145 Reilly_Hu_12Fpcw_H3K4me2_rep1_2_merge . Reilly_Hu_12Fpcw_H3K4me2_rep1_2_merge 1.254
chr1 100042310 100043300 enhancer_atlas_Fetal_brain Fetalbrain.H3K4me1_narrow_peak_2501 5.145 enhancer_atlas_Fetal_brain 1.356 enhancer_atlas_Fetal_brain 6.325
输出:
chr1 100042310 100043300 enhancer_atlas_Fetal_brain Fetalbrain.H3K4me1_narrow_peak_2501 5.145 enhancer_atlas_Fetal_brain 1.356 enhancer_atlas_Fetal_brain 6.325
首先使用 'grepl' 获取所有以 log10.
开头的列,然后使用 apply
检查每行中的 .
或 na
并求和。
最后,return 行,其中 sum(x=='.'| is.na(x))==0
df[apply(df[,grepl('log10.',names(df))],1,function(x)sum(x=='.'| is.na(x))==0),]
chr_enhancer Start_enhancer End_enhancer source_enhancer.x source_marks.x X.log10.qvalue.x
3 chr1 100042310 100043300 enhancer_atlas_Fetal_brain Fetalbrain.H3K4me1_narrow_peak_2501 5.145
source_enhancer.y X.log10.qvalue.y source_enhancer X.log10.qvalue
3 enhancer_atlas_Fetal_brain 1.356 enhancer_atlas_Fetal_brain 6.325
数据
df <- read.table(text="chr_enhancer Start_enhancer End_enhancer source_enhancer.x source_marks.x -log10.qvalue.x source_enhancer.y -log10.qvalue.y source_enhancer -log10.qvalue
chr1 100036100 100036650 Reilly_Hu_12Opcw_H3K4me2_rep1_2_merge . . Reilly_Hu_12Opcw_H3K4me2_rep1_2_merge . Reilly_Hu_12Opcw_H3K4me2_rep1_2_merge .
chr1 100042226 100043575 Reilly_Hu_12Fpcw_H3K4me2_rep1_2_merge Fetalbrain.H3K4me1_narrow_peak_2501 2.145 Reilly_Hu_12Fpcw_H3K4me2_rep1_2_merge . Reilly_Hu_12Fpcw_H3K4me2_rep1_2_merge 1.254
chr1 100042310 100043300 enhancer_atlas_Fetal_brain Fetalbrain.H3K4me1_narrow_peak_2501 5.145 enhancer_atlas_Fetal_brain 1.356 enhancer_atlas_Fetal_brain 6.325
",header=T)
我有一个像下面这样的 table 合并了多个数据,我想只保留在“-log10.qvalue”列中存在值的行。
输入:
chr_enhancer Start_enhancer End_enhancer source_enhancer.x source_marks.x -log10.qvalue.x source_enhancer.y -log10.qvalue.y source_enhancer -log10.qvalue
chr1 100036100 100036650 Reilly_Hu_12Opcw_H3K4me2_rep1_2_merge . . Reilly_Hu_12Opcw_H3K4me2_rep1_2_merge . Reilly_Hu_12Opcw_H3K4me2_rep1_2_merge .
chr1 100042226 100043575 Reilly_Hu_12Fpcw_H3K4me2_rep1_2_merge Fetalbrain.H3K4me1_narrow_peak_2501 2.145 Reilly_Hu_12Fpcw_H3K4me2_rep1_2_merge . Reilly_Hu_12Fpcw_H3K4me2_rep1_2_merge 1.254
chr1 100042310 100043300 enhancer_atlas_Fetal_brain Fetalbrain.H3K4me1_narrow_peak_2501 5.145 enhancer_atlas_Fetal_brain 1.356 enhancer_atlas_Fetal_brain 6.325
输出:
chr1 100042310 100043300 enhancer_atlas_Fetal_brain Fetalbrain.H3K4me1_narrow_peak_2501 5.145 enhancer_atlas_Fetal_brain 1.356 enhancer_atlas_Fetal_brain 6.325
首先使用 'grepl' 获取所有以 log10.
开头的列,然后使用 apply
检查每行中的 .
或 na
并求和。
最后,return 行,其中 sum(x=='.'| is.na(x))==0
df[apply(df[,grepl('log10.',names(df))],1,function(x)sum(x=='.'| is.na(x))==0),]
chr_enhancer Start_enhancer End_enhancer source_enhancer.x source_marks.x X.log10.qvalue.x
3 chr1 100042310 100043300 enhancer_atlas_Fetal_brain Fetalbrain.H3K4me1_narrow_peak_2501 5.145
source_enhancer.y X.log10.qvalue.y source_enhancer X.log10.qvalue
3 enhancer_atlas_Fetal_brain 1.356 enhancer_atlas_Fetal_brain 6.325
数据
df <- read.table(text="chr_enhancer Start_enhancer End_enhancer source_enhancer.x source_marks.x -log10.qvalue.x source_enhancer.y -log10.qvalue.y source_enhancer -log10.qvalue
chr1 100036100 100036650 Reilly_Hu_12Opcw_H3K4me2_rep1_2_merge . . Reilly_Hu_12Opcw_H3K4me2_rep1_2_merge . Reilly_Hu_12Opcw_H3K4me2_rep1_2_merge .
chr1 100042226 100043575 Reilly_Hu_12Fpcw_H3K4me2_rep1_2_merge Fetalbrain.H3K4me1_narrow_peak_2501 2.145 Reilly_Hu_12Fpcw_H3K4me2_rep1_2_merge . Reilly_Hu_12Fpcw_H3K4me2_rep1_2_merge 1.254
chr1 100042310 100043300 enhancer_atlas_Fetal_brain Fetalbrain.H3K4me1_narrow_peak_2501 5.145 enhancer_atlas_Fetal_brain 1.356 enhancer_atlas_Fetal_brain 6.325
",header=T)