3week : solution3-2
From Biocourse
3. Gene 별 missing 자료 계산ii) missing 자료를 0으로 채워 넣는다.
==> 각 유전자 별 평균, 분산, 표준편차, 1Q(사분위수), 3Q(사분위수) 계산
> impute.data = data ## data를 이용하여 impute.data를 만든다.
> impute.data[na.data] = 0 ## impute.data에 missing인 자료는 0으로 대체한다.
> row.sum = apply(impute.data,1,summary)
## impute.data를 이용하여 각 유전자의 min,1Q,median, mean, 3Q, max값을 구한다.
row.sum
gene1 gene2 gene3 gene4 gene5 gene6 gene7 gene8 gene9 gene10 gene11 gene12
Min. -0.3000 -0.0900 -0.3600 -0.17000 -0.23000 -0.430 -0.17000 -0.1000 -0.1900 -0.4200 -0.0600 -0.2100
1st Qu. 0.0100 0.0975 -0.1475 -0.03500 -0.03750 -0.100 -0.03500 0.0000 -0.0450 -0.2100 0.0975 0.0025
Median 0.0600 0.2700 -0.0350 0.04000 0.05000 -0.025 0.03000 0.1000 0.1100 -0.1650 0.1700 0.1050
Mean 0.0710 0.2773 -0.0200 0.03633 0.06267 -0.027 0.03833 0.1133 0.1097 -0.1423 0.1690 0.1217
3rd Qu. 0.1575 0.4175 0.1125 0.10250 0.15500 0.080 0.10750 0.1850 0.2600 -0.0525 0.2400 0.2675
Max. 0.3100 0.8700 0.3400 0.44000 0.34000 0.220 0.27000 0.4800 0.4900 0.0600 0.4400 0.5600
## impute.data를 이용하여 각 유전자의 min,1Q,median, mean, 3Q, max값을 구한다.
row.sum
gene1 gene2 gene3 gene4 gene5 gene6 gene7 gene8 gene9 gene10 gene11 gene12
Min. -0.3000 -0.0900 -0.3600 -0.17000 -0.23000 -0.430 -0.17000 -0.1000 -0.1900 -0.4200 -0.0600 -0.2100
1st Qu. 0.0100 0.0975 -0.1475 -0.03500 -0.03750 -0.100 -0.03500 0.0000 -0.0450 -0.2100 0.0975 0.0025
Median 0.0600 0.2700 -0.0350 0.04000 0.05000 -0.025 0.03000 0.1000 0.1100 -0.1650 0.1700 0.1050
Mean 0.0710 0.2773 -0.0200 0.03633 0.06267 -0.027 0.03833 0.1133 0.1097 -0.1423 0.1690 0.1217
3rd Qu. 0.1575 0.4175 0.1125 0.10250 0.15500 0.080 0.10750 0.1850 0.2600 -0.0525 0.2400 0.2675
Max. 0.3100 0.8700 0.3400 0.44000 0.34000 0.220 0.27000 0.4800 0.4900 0.0600 0.4400 0.5600
