正则表达式 – 从两个文件中的列中获取值

发布时间：2020-12-14 05:58:23 所属栏目：百科来源：网络整理

导读：我的原始观察结果如下： name Analytespring 0.1winter 0.4 为了计算p值,我做了自举模拟： name Analytespring 0.001winter 0spring 0winter 0.2spring 0.03winter 0spring 0.01winter 0.02spring 0.1winter 0.5spring 0winter 0.04spring 0.2winter 0spring

我的原始观察结果如下：

name Analyte
spring 0.1
winter 0.4

为了计算p值,我做了自举模拟：

name Analyte
spring 0.001
winter 0
spring 0
winter 0.2
spring 0.03
winter 0
spring 0.01
winter 0.02
spring 0.1
winter 0.5
spring 0
winter 0.04
spring 0.2
winter 0
spring 0
winter 0.06
spring 0
winter 0
.....

现在我想计算经验p值：在原始数据中冬季分析物= 0.4-如果在自举数据中冬季分析物> = 0.4(例如1次)并且完成自举(例如100次),则经验p-冬季分析物的价值计算如下：

1/100 = 0.01

(数据与原始数据相同或更高的次数
除以观察总数)
对于弹簧分析物,p值为：

2/100 = 0.02

我想用awk计算那些p值.
我对春天的解决方案是：

awk -v VAR="spring" '($1==VAR && $2>=0.1) {n++} END {print VAR,"p-value=",n/100}'

弹簧p值= 0.02
我需要的帮助是将原始文件(名称为spring and winter及其分析物,观察值和观察次数)传递给awk并分配.

解决方法

说明和脚本内容：

像以下一样运行：awk -f script.awk原始引导程序

# Slurp the original file in an array a
# Ignore the header

NR==FNR && NR>1 {

# Index of this array will be type
# Value of that type will be original value

    a[$1]=$2
    next
}

# If in the bootstrap file value
# of second column is greater than original value

FNR>1 && $2>a[$1] { 

# Increment an array indexed at first column
# which is nothing but type

    b[$1]++
}

# Increment another array regardless to identify
# the number of times bootstrapping was done
{
    c[$1]++
}

# for each type in array a

END {
    for (type in a) {

# print the type and calculate empirical p-value 
# which is done by dividing the number of times higher value
# of a type was seen and total number of times
# bootstrapping was done. 

        print type,b[type]/c[type]
    }
}

测试：

$cat original 
name Analyte
spring 0.1
winter 0.4

$cat bootstrap 
name Analyte
spring 0.001
winter 0
spring 0
winter 0.2
spring 0.03
winter 0
spring 0.01
winter 0.02
spring 0.1
winter 0.5
spring 0
winter 0.04
spring 0.2
winter 0
spring 0
winter 0.06
spring 0
winter 0

$awk -f s.awk original bootstrap 
spring 0.222221
winter 0.222221

分析：

Spring Original Value is 0.1
Winter Original Value is 0.4
Bootstrapping done is 9 times for this sample file
Count of values higher than Spring original value = 1
Count of values higher than Winter's original value = 1
So,1/9 = 0.222221

（编辑：李大同）

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