How do I change the size of the points based on the value of the column using ggplot?










0














Using ggplot on rstudio, I am trying to change the size of the point of my scatter plot based on the log of the pvalue column. This is how my matrix looks like.



head(BDpvalue)
id t-value pvalue mean.f mean.m Gene Chromosome
1 ILMN_1212619 3.0512842692996 0.00938046962249251 85.40076 80.02744 Mfap3l 8
2 ILMN_1212693 3.40887110529531 0.00452088152864021 87.28189 82.89533 Snx33 9
3 ILMN_1213324 -4.54750670298688 0.000414140589714275 82.68924 88.81421 Zfp961 8
4 ILMN_1213848 -3.63180275429357 0.00246745595956587 421.61780 469.51845 Itgb1bp1 12
5 ILMN_1213961 2.97573716869553 0.00960659647288939 82.01748 78.44721 Copg2 6
6 ILMN_1214482 -4.23666060706341 0.000813240203181102 136.55021 153.34681 2700081O15Rik 19


>



The code to change the size based on the log of the pvalue column seems correct to me, but for some reason I am not seeing a change in the graph, this is the code that I used.



ggplot(BDpvalue, aes(x=(log(mean.m,10)+log(mean.f,10))/2,
y= log(mean.f/mean.m,10),color=Chromosome) + geom_point(aes(size=(-log(pvalue,10))))









share|improve this question























  • please post a reproducible dataset with dput()
    – the_darkside
    Nov 12 '18 at 1:24






  • 3




    Your parentheses are wrong; geom_point should be outside of ggplot: ggplot(BDpvalue, aes(x = (log(mean.m, 10) + log(mean.f, 10))/2, y = log(mean.f/mean.m,10), color = Chromosome)) + geom_point(aes(size = -log(pvalue,10)))
    – alistaire
    Nov 12 '18 at 1:28










  • I tried using the code from above and got an error message: Error in Math.factor(pvalue, 10) : ‘log’ not meaningful for factors
    – 151
    Nov 12 '18 at 1:53







  • 1




    try BDpvalue$pvalue <- as.numeric(BDpvalue$pvalue)
    – passiflora
    Nov 12 '18 at 3:35










  • @passiflora, BDpvalue$pvalue <- as.numeric(BDpvalue$pvalue) will return the factor levels. To get the original numerical values of the factor use BDpvalue$pvalue <-as.numeric(as.character(BDpvalue$pvalue))
    – Niek
    Nov 12 '18 at 7:47















0














Using ggplot on rstudio, I am trying to change the size of the point of my scatter plot based on the log of the pvalue column. This is how my matrix looks like.



head(BDpvalue)
id t-value pvalue mean.f mean.m Gene Chromosome
1 ILMN_1212619 3.0512842692996 0.00938046962249251 85.40076 80.02744 Mfap3l 8
2 ILMN_1212693 3.40887110529531 0.00452088152864021 87.28189 82.89533 Snx33 9
3 ILMN_1213324 -4.54750670298688 0.000414140589714275 82.68924 88.81421 Zfp961 8
4 ILMN_1213848 -3.63180275429357 0.00246745595956587 421.61780 469.51845 Itgb1bp1 12
5 ILMN_1213961 2.97573716869553 0.00960659647288939 82.01748 78.44721 Copg2 6
6 ILMN_1214482 -4.23666060706341 0.000813240203181102 136.55021 153.34681 2700081O15Rik 19


>



The code to change the size based on the log of the pvalue column seems correct to me, but for some reason I am not seeing a change in the graph, this is the code that I used.



ggplot(BDpvalue, aes(x=(log(mean.m,10)+log(mean.f,10))/2,
y= log(mean.f/mean.m,10),color=Chromosome) + geom_point(aes(size=(-log(pvalue,10))))









share|improve this question























  • please post a reproducible dataset with dput()
    – the_darkside
    Nov 12 '18 at 1:24






  • 3




    Your parentheses are wrong; geom_point should be outside of ggplot: ggplot(BDpvalue, aes(x = (log(mean.m, 10) + log(mean.f, 10))/2, y = log(mean.f/mean.m,10), color = Chromosome)) + geom_point(aes(size = -log(pvalue,10)))
    – alistaire
    Nov 12 '18 at 1:28










  • I tried using the code from above and got an error message: Error in Math.factor(pvalue, 10) : ‘log’ not meaningful for factors
    – 151
    Nov 12 '18 at 1:53







  • 1




    try BDpvalue$pvalue <- as.numeric(BDpvalue$pvalue)
    – passiflora
    Nov 12 '18 at 3:35










  • @passiflora, BDpvalue$pvalue <- as.numeric(BDpvalue$pvalue) will return the factor levels. To get the original numerical values of the factor use BDpvalue$pvalue <-as.numeric(as.character(BDpvalue$pvalue))
    – Niek
    Nov 12 '18 at 7:47













0












0








0







Using ggplot on rstudio, I am trying to change the size of the point of my scatter plot based on the log of the pvalue column. This is how my matrix looks like.



head(BDpvalue)
id t-value pvalue mean.f mean.m Gene Chromosome
1 ILMN_1212619 3.0512842692996 0.00938046962249251 85.40076 80.02744 Mfap3l 8
2 ILMN_1212693 3.40887110529531 0.00452088152864021 87.28189 82.89533 Snx33 9
3 ILMN_1213324 -4.54750670298688 0.000414140589714275 82.68924 88.81421 Zfp961 8
4 ILMN_1213848 -3.63180275429357 0.00246745595956587 421.61780 469.51845 Itgb1bp1 12
5 ILMN_1213961 2.97573716869553 0.00960659647288939 82.01748 78.44721 Copg2 6
6 ILMN_1214482 -4.23666060706341 0.000813240203181102 136.55021 153.34681 2700081O15Rik 19


>



The code to change the size based on the log of the pvalue column seems correct to me, but for some reason I am not seeing a change in the graph, this is the code that I used.



ggplot(BDpvalue, aes(x=(log(mean.m,10)+log(mean.f,10))/2,
y= log(mean.f/mean.m,10),color=Chromosome) + geom_point(aes(size=(-log(pvalue,10))))









share|improve this question















Using ggplot on rstudio, I am trying to change the size of the point of my scatter plot based on the log of the pvalue column. This is how my matrix looks like.



head(BDpvalue)
id t-value pvalue mean.f mean.m Gene Chromosome
1 ILMN_1212619 3.0512842692996 0.00938046962249251 85.40076 80.02744 Mfap3l 8
2 ILMN_1212693 3.40887110529531 0.00452088152864021 87.28189 82.89533 Snx33 9
3 ILMN_1213324 -4.54750670298688 0.000414140589714275 82.68924 88.81421 Zfp961 8
4 ILMN_1213848 -3.63180275429357 0.00246745595956587 421.61780 469.51845 Itgb1bp1 12
5 ILMN_1213961 2.97573716869553 0.00960659647288939 82.01748 78.44721 Copg2 6
6 ILMN_1214482 -4.23666060706341 0.000813240203181102 136.55021 153.34681 2700081O15Rik 19


>



The code to change the size based on the log of the pvalue column seems correct to me, but for some reason I am not seeing a change in the graph, this is the code that I used.



ggplot(BDpvalue, aes(x=(log(mean.m,10)+log(mean.f,10))/2,
y= log(mean.f/mean.m,10),color=Chromosome) + geom_point(aes(size=(-log(pvalue,10))))






r ggplot2






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edited Nov 12 '18 at 1:17









NelsonGon

846217




846217










asked Nov 12 '18 at 1:13









151

11




11











  • please post a reproducible dataset with dput()
    – the_darkside
    Nov 12 '18 at 1:24






  • 3




    Your parentheses are wrong; geom_point should be outside of ggplot: ggplot(BDpvalue, aes(x = (log(mean.m, 10) + log(mean.f, 10))/2, y = log(mean.f/mean.m,10), color = Chromosome)) + geom_point(aes(size = -log(pvalue,10)))
    – alistaire
    Nov 12 '18 at 1:28










  • I tried using the code from above and got an error message: Error in Math.factor(pvalue, 10) : ‘log’ not meaningful for factors
    – 151
    Nov 12 '18 at 1:53







  • 1




    try BDpvalue$pvalue <- as.numeric(BDpvalue$pvalue)
    – passiflora
    Nov 12 '18 at 3:35










  • @passiflora, BDpvalue$pvalue <- as.numeric(BDpvalue$pvalue) will return the factor levels. To get the original numerical values of the factor use BDpvalue$pvalue <-as.numeric(as.character(BDpvalue$pvalue))
    – Niek
    Nov 12 '18 at 7:47
















  • please post a reproducible dataset with dput()
    – the_darkside
    Nov 12 '18 at 1:24






  • 3




    Your parentheses are wrong; geom_point should be outside of ggplot: ggplot(BDpvalue, aes(x = (log(mean.m, 10) + log(mean.f, 10))/2, y = log(mean.f/mean.m,10), color = Chromosome)) + geom_point(aes(size = -log(pvalue,10)))
    – alistaire
    Nov 12 '18 at 1:28










  • I tried using the code from above and got an error message: Error in Math.factor(pvalue, 10) : ‘log’ not meaningful for factors
    – 151
    Nov 12 '18 at 1:53







  • 1




    try BDpvalue$pvalue <- as.numeric(BDpvalue$pvalue)
    – passiflora
    Nov 12 '18 at 3:35










  • @passiflora, BDpvalue$pvalue <- as.numeric(BDpvalue$pvalue) will return the factor levels. To get the original numerical values of the factor use BDpvalue$pvalue <-as.numeric(as.character(BDpvalue$pvalue))
    – Niek
    Nov 12 '18 at 7:47















please post a reproducible dataset with dput()
– the_darkside
Nov 12 '18 at 1:24




please post a reproducible dataset with dput()
– the_darkside
Nov 12 '18 at 1:24




3




3




Your parentheses are wrong; geom_point should be outside of ggplot: ggplot(BDpvalue, aes(x = (log(mean.m, 10) + log(mean.f, 10))/2, y = log(mean.f/mean.m,10), color = Chromosome)) + geom_point(aes(size = -log(pvalue,10)))
– alistaire
Nov 12 '18 at 1:28




Your parentheses are wrong; geom_point should be outside of ggplot: ggplot(BDpvalue, aes(x = (log(mean.m, 10) + log(mean.f, 10))/2, y = log(mean.f/mean.m,10), color = Chromosome)) + geom_point(aes(size = -log(pvalue,10)))
– alistaire
Nov 12 '18 at 1:28












I tried using the code from above and got an error message: Error in Math.factor(pvalue, 10) : ‘log’ not meaningful for factors
– 151
Nov 12 '18 at 1:53





I tried using the code from above and got an error message: Error in Math.factor(pvalue, 10) : ‘log’ not meaningful for factors
– 151
Nov 12 '18 at 1:53





1




1




try BDpvalue$pvalue <- as.numeric(BDpvalue$pvalue)
– passiflora
Nov 12 '18 at 3:35




try BDpvalue$pvalue <- as.numeric(BDpvalue$pvalue)
– passiflora
Nov 12 '18 at 3:35












@passiflora, BDpvalue$pvalue <- as.numeric(BDpvalue$pvalue) will return the factor levels. To get the original numerical values of the factor use BDpvalue$pvalue <-as.numeric(as.character(BDpvalue$pvalue))
– Niek
Nov 12 '18 at 7:47




@passiflora, BDpvalue$pvalue <- as.numeric(BDpvalue$pvalue) will return the factor levels. To get the original numerical values of the factor use BDpvalue$pvalue <-as.numeric(as.character(BDpvalue$pvalue))
– Niek
Nov 12 '18 at 7:47












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