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?
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2 answers
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
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)
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