如何使用R删除值为0的行 [英] How to remove rows with 0 values using R
本文介绍了如何使用R删除值为0的行的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
输入
gene ZPT.1 ZPT.0 ZPT.2 ZPT.3 PDGT.1 PDGT.0
XLOC_000001 3516 626 1277 770 4309 9030
XLOC_000002 342 82 185 72 835 1095
XLOC_000003 2000 361 867 438 454 687
XLOC_000004 143 30 67 37 90 236
XLOC_000005 0 0 0 0 0 0
XLOC_000006 0 0 0 0 0 0
XLOC_000007 0 0 0 0 1 3
XLOC_000008 0 0 0 0 0 0
XLOC_000009 0 0 0 0 0 0
XLOC_000010 7 1 5 3 0 1
XLOC_000011 63 10 19 15 92 228
所需的输出
gene ZPT.1 ZPT.0 ZPT.2 ZPT.3 PDGT.1 PDGT.0
XLOC_000001 3516 626 1277 770 4309 9030
XLOC_000002 342 82 185 72 835 1095
XLOC_000003 2000 361 867 438 454 687
XLOC_000004 143 30 67 37 90 236
XLOC_000007 0 0 0 0 1 3
XLOC_000010 7 1 5 3 0 1
XLOC_000011 63 10 19 15 92 228
到目前为止,如果在任何行中某些值均为0而其他值不为零,那么我只想删除所有碎片计数列均为0的那些行,如您在上面的示例中所见,我想保持该行的完整性.
请让我知道该怎么做.
解决方案
df[apply(df[,-1], 1, function(x) !all(x==0)),]
Hi am using a matrix of gene expression, frag counts to calculate differentially expressed genes. I would like to know how to remove the rows which have values as 0. Then my data set will be compact and less spurious results will be given for the downstream analysis I do using this matrix.
Input
gene ZPT.1 ZPT.0 ZPT.2 ZPT.3 PDGT.1 PDGT.0
XLOC_000001 3516 626 1277 770 4309 9030
XLOC_000002 342 82 185 72 835 1095
XLOC_000003 2000 361 867 438 454 687
XLOC_000004 143 30 67 37 90 236
XLOC_000005 0 0 0 0 0 0
XLOC_000006 0 0 0 0 0 0
XLOC_000007 0 0 0 0 1 3
XLOC_000008 0 0 0 0 0 0
XLOC_000009 0 0 0 0 0 0
XLOC_000010 7 1 5 3 0 1
XLOC_000011 63 10 19 15 92 228
Desired output
gene ZPT.1 ZPT.0 ZPT.2 ZPT.3 PDGT.1 PDGT.0
XLOC_000001 3516 626 1277 770 4309 9030
XLOC_000002 342 82 185 72 835 1095
XLOC_000003 2000 361 867 438 454 687
XLOC_000004 143 30 67 37 90 236
XLOC_000007 0 0 0 0 1 3
XLOC_000010 7 1 5 3 0 1
XLOC_000011 63 10 19 15 92 228
As of now I only want to remove those rows where all the frag count columns are 0 if in any row some values are 0 and others are non zero I would like to keep that row intact as you can see my example above.
Please let me know how to do this.
解决方案
df[apply(df[,-1], 1, function(x) !all(x==0)),]
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