correlation between expression and tumor size

Question

[newbie]

I have the following information in a dataframe data. First two columns are expression of two genes and third column is tumour size.

data:

structure(list(KRAS = c(1.84799690655495, 0.485426827170242, 
1.58496250072116, 0.925999418556223, 2.82781902461732, 1.53605290024021, 
1.37851162325373, 1.0703893278914, 0.765534746362977, 1.63226821549951, 
3.13750352374994, 0.84799690655495, 1, 0.137503523749935, 0.37851162325373, 
2.98185265328974, 1.13750352374994, 4.54225804976692, 1.53605290024021, 
4.53605290024021, 4.12928301694497, 0.84799690655495, 1.13750352374994, 
2.60880924267552, 1.13750352374994, 0.678071905112638, 0.765534746362977, 
0.84799690655495, 4.93545974780529, 0.584962500721156, 1.8073549220576, 
2.16992500144231, 1.13750352374994, 1.53605290024021, 1.32192809488736, 
1.72246602447109, 3.40599235967584, 1.72246602447109, 2.20163386116965, 
2.58496250072116, 0.584962500721156, 0.925999418556223, 1.0703893278914, 
1.37851162325373, 2.58496250072116, 0.765534746362977, 1.43295940727611, 
1.48542682717024, 2, 3.83794324189103), HRAS = c(2.88752527074159, 
2.88752527074159, 2.10433665981474, 0.925999418556223, 4.54843662469604, 
3.33628338786443, 3.30742852519225, 3.32192809488736, 1.58496250072116, 
4.41278152533848, 4.20945336562895, 3.92599941855622, 2.51096191927738, 
1.84799690655495, 3, 1.8073549220576, 3.01792190799726, 5.24412594328373, 
1.88752527074159, 5.6409679104499, 5.02680005934372, 3.877744249949, 
1.88752527074159, 2.13750352374994, 1.67807190511264, 0.925999418556223, 
2.48542682717024, 3.26303440583379, 5.95419631038687, 4.12928301694497, 
3.47248777146274, 3.91647664443772, 2.26303440583379, 3.96347412397489, 
0.678071905112638, 2.56071495447448, 4.65535182861255, 3.20163386116965, 
3.12101540096137, 3.62058641045188, 2.56071495447448, 1.32192809488736, 
1.84799690655495, 4.62643913669732, 3.91647664443772, 2.0703893278914, 
1.37851162325373, 1.48542682717024, 3.85798099512757, 4.12101540096137
), tumsize = c("6.5", "3", "3.5", "2.8", "1.3", "3.4", "2.4", 
"3.5", "5.7", "3.7", "4.5", "1.4", "3.6", "3.5", "5.5", "3", 
"3.4", "1.5", "5", "3", "1.7", "1.5", "1", "2.5", "3.3", "2.6", 
"1", "2.6", "0.5", "1.5", "2.5", "1.5", "2.3", "1.5", "3.6", 
"4.5", "3", "1.5", "4", "1.5", "2", "4", "5", "4.5", "2", "2.4", 
"2.5", "2.9", "5.2", "1.7")), row.names = c(1L, 2L, 3L, 4L, 5L, 
7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 
20L, 21L, 22L, 23L, 25L, 26L, 28L, 33L, 34L, 35L, 36L, 37L, 38L, 
39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 
52L, 53L, 54L, 55L, 56L, 57L), class = "data.frame")

Correlation between two genes expression data was done using spearman correlation.

ggscatter(data, x = "KRAS", y = "HRAS", 
          size = 0.3,combine = TRUE, ylab = "HRAS",
          palette = "jco",add = "reg.line", conf.int = TRUE) + 
  stat_cor(method = "spearman")

And I'm interested in looking at correlation between KRAS expression and Tumor size. But I don't get the right way. Is something wrong in this?

ggscatter(data, x = "KRAS", y = "tumsize", 
          size = 0.3,combine = TRUE, ylab = "Tumor size",
          palette = "jco",add = "reg.line", conf.int = TRUE) + 
  stat_cor(method = "spearman")

`geom_smooth()` using formula 'y ~ x'
There were 18 warnings (use warnings() to see them)

And it looks like below. Can anyone tell me how to check correlation between expression and tumor size?

Answer 1

[Kevin Blighe]

It is not stated in your question what is your exact intention or where lies the problem (?).

First, you need to convert tumsize to numeric:

data$tumsize <- as.numeric(data$tumsize)

For correlation, you just need:

cor(x = data[['KRAS']], y = data[['tumsize']], method = 'spearman')
cor.test(x = data[['KRAS']], y = data[['tumsize']], method = 'spearman')

You can also build a linear regression model:

model <- lm(tumsize ~ KRAS, data = data)
summary(model)

Residuals:
    Min      1Q  Median      3Q     Max 
-2.2244 -0.8217 -0.2413  0.6913  3.5984 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)   3.4527     0.3467   9.959  2.9e-13 ***
KRAS         -0.2982     0.1654  -1.803   0.0776 .  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.345 on 48 degrees of freedom
Multiple R-squared:  0.06344,   Adjusted R-squared:  0.04393 
F-statistic: 3.251 on 1 and 48 DF,  p-value: 0.07764

Odds ratios:

exp(cbind('OR' = coef(model), confint.default(model, level = 0.95)))

                    OR      2.5 %    97.5 %
(Intercept) 31.5853430 16.0098441 62.313779
KRAS         0.7421502  0.5366864  1.026273

Kevin

[newbie]

Oh yes. Wondering how come I didn't check this str(data). thanks a lot.

Answer 2

[dunja.vucenovic]

Hi, it looks like you are defining tumour size as character and not a numerical.

If you do str(data) you will see types of all variables in your dataframe

what you could do is to change tumsize in dataframe directly like data$tumsize <- as.numeric(data$tumsize)