# getJaccard: Calculate Jaccard Index for Two Binary Vectors In countTransformers: Transform Counts in RNA-Seq Data Analysis

## Description

Calculate Jaccard index for two binary vectors.

## Usage

 `1` ```getJaccard(cl1, cl2) ```

## Arguments

 `cl1` n by 1 binary vector of classification 1 for the n subjects `cl2` n by 1 binary vector of classification 2 for the n subjects

## Details

Jaccard Index is defined as the ratio

d/(b+c+d

, where d is the number of subjects who were classified to group 1 by both classification rules, b is the number of subjects who were classified to group 1 by classification rule 1 and were classified to group 0 by classification rule 2, c is the number of subjects who were classified to group 0 by classification rule 1 and were classified to group 1 by classification rule 2.

## Value

The Jaccard Index

## Author(s)

Zeyu Zhang, Danyang Yu, Minseok Seo, Craig P. Hersh, Scott T. Weiss, Weiliang Qiu

## References

Zhang Z, Yu D, Seo M, Hersh CP, Weiss ST, Qiu W. Novel Data Transformations for RNA-seq Differential Expression Analysis. (2019) 9:4820 https://rdcu.be/brDe5

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ``` n = 10 set.seed(1234567) # generate two random binary vector of size n cl1 = sample(c(1,0), size = n, prob = c(0.5, 0.5), replace = TRUE) cl2 = sample(c(1,0), size = n, prob = c(0.5, 0.5), replace = TRUE) cat("\n2x2 contingency table >>\n") print(table(cl1, cl2)) JI = getJaccard(cl1, cl2) cat("Jaccard index = ", JI, "\n") ```

countTransformers documentation built on May 1, 2019, 7:59 p.m.