Last updated: 2023-03-13

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Knit directory: misc/

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Rmd 960ed1b DongyueXie 2023-03-13 wflow_publish("analysis/mutation.Rmd")

AtoG

10k

temp = read.table('/project2/compbio/todongyue/AtoG/mutation.A_to_G.and.mutation.T_to_C.10k')
x = temp$V4
x = as.numeric(x)
Warning: NAs introduced by coercion
x = x[!is.na(x)]
sum(x==0)/length(x)
[1] 0.9494643
range(x)
[1] 0 3

Too many zeros.

100k

temp = read.table('/project2/compbio/todongyue/AtoG/mutation.A_to_G.and.mutation.T_to_C.100k')
temp = temp[temp$V4!='.',]
x = temp$V4
x = as.numeric(x)
x = x[!is.na(x)]
sum(x==0)/length(x)
[1] 0.605107
range(x)
[1] 0 6
s = temp$V5
s = as.numeric(s)
range(s)
[1]  0.00000 15.38728
plot(x,pch='.',col='grey80',cex=1.5)

plot(s,pch='.',col='grey80',cex=1.5)

plot(s,pch='.',col='grey80',cex=1.5,ylim=c(0,2))

Some of the scaling factors \(s\) are exactly 0?

Try smash poisson on the count \(x\),

library(smashr)
fit_smash = smash.poiss(x)
plot(x,pch='.',col='grey80',cex=1.5,xlab='position',main='A to G, 100k')
lines(fit_smash)
legend('topleft',c('data','smash fit'),pch=c('.',NA),lty=c(NA,1))

plot(fit_smash,type='l',xlab='position',main='A to G, 100k, smash fit')

Try smash gaus on the \(log(x/s)\).

x_tilde = log((x+0.1)/(s+0.1))
fit_smash_gaus = smash.gaus(x_tilde,ebnm_param = list(prior_family = "point_laplace"))
plot(x,pch='.',col='grey80',cex=1.5,xlab='position',main='A to G, 100k, x/s')
lines(exp(fit_smash_gaus))
legend('topleft',c('data','smash fit'),pch=c('.',NA),lty=c(NA,1))

plot(fit_smash_gaus,type='l',xlab='position',main='A to G, 100k, smash fit, x/s')

10m

temp = read.table('/project2/compbio/todongyue/AtoG/mutation.A_to_G.and.mutation.T_to_C.10m')
temp = temp[temp$V4!='.',]
x = temp$V4
x = as.numeric(x)
x = x[!is.na(x)]
sum(x==0)/length(x)
[1] 0.04333333
range(x)
[1]  0 90
s = temp$V5
s = as.numeric(s)
range(s)
[1]  0.00000 77.91058
plot(x,pch='.',col='grey80',cex=1.5)

plot(s,pch='.',col='grey80',cex=1.5)

Why range of s is much larger?

Try smash poisson on the count \(x\),

fit_smash = smash.poiss(x)
plot(x,pch='.',col='grey80',cex=2,xlab='position',main='A to G, 10m')
lines(fit_smash)
legend('topleft',c('data','smash fit'),pch=c('.',NA),lty=c(NA,1))

plot(fit_smash,type='l',xlab='position',main='A to G, 100k, smash fit')

library(genlasso)
Loading required package: Matrix
Loading required package: igraph

Attaching package: 'igraph'
The following objects are masked from 'package:stats':

    decompose, spectrum
The following object is masked from 'package:base':

    union
fit_tf = trendfilter(x)
fit_tf_cv =cv.trendfilter(fit_tf)
Fold 1 ... Fold 2 ... Fold 3 ... Fold 4 ... Fold 5 ... 
plot(fit_tf,lambda = fit_tf_cv$lambda.min,col='grey80',pch=20)

CtoT

100k

temp = read.table('/project2/compbio/todongyue/CtoT/mutation.C_to_T.nonCpG.and.mutation.G_to_A.nonCpG.bed.100k')
temp = temp[temp$V4!='.',]
x = temp$V4
x = as.numeric(x)
x = x[!is.na(x)]
sum(x==0)/length(x)
[1] 0.630434
range(x)
[1] 0 5
s = temp$V5
s = as.numeric(s)
range(s)
[1] 0.000000 4.546582
plot(x,pch='.',col='grey80',cex=2)

plot(s,pch='.',col='grey80',cex=2)

plot(s,pch='.',col='grey80',cex=2,ylim=c(0,2))

Try smash poisson on the count \(x\),

fit_smash = smash.poiss(x)
plot(x,pch='.',col='grey80',cex=2,xlab='position',main='C to T, 100k')
lines(fit_smash)
legend('topleft',c('data','smash fit'),pch=c('.',NA),lty=c(NA,1))

plot(fit_smash,type='l',xlab='position',main='C to T, 100k, smash fit')

Try smash gaus on the \(log(x/s)\).

x_tilde = log((x+0.1)/(s+0.1))
fit_smash_gaus = smash.gaus(x_tilde,ebnm_param = list(prior_family = "point_laplace"))
plot(x,pch='.',col='grey80',cex=1.5,xlab='position',main='A to G, 100k, x/s')
lines(exp(fit_smash_gaus))
legend('topleft',c('data','smash fit'),pch=c('.',NA),lty=c(NA,1))

plot(fit_smash_gaus,type='l',xlab='position',main='A to G, 100k, smash fit, x/s')

10m

temp = read.table('/project2/compbio/todongyue/CtoT/mutation.C_to_T.nonCpG.and.mutation.G_to_A.nonCpG.bed.10m')
temp = temp[temp$V4!='.',]
x = temp$V4
x = as.numeric(x)
x = x[!is.na(x)]
sum(x==0)/length(x)
[1] 0.03333333
range(x)
[1]  0 87
s = temp$V5
s = as.numeric(s)
range(s)
[1]  0.00000 82.47824
plot(x,pch='.',col='grey80',cex=2)

plot(s,pch='.',col='grey80',cex=2)

Try smash poisson on the count \(x\),

fit_smash = smash.poiss(x)
plot(x,pch='.',col='grey80',cex=2,xlab='position',main='C to T, 10m')
lines(fit_smash)
legend('topleft',c('data','smash fit'),pch=c('.',NA),lty=c(NA,1))

500k

temp = read.table('/project2/compbio/todongyue/CtoT2/CtoT_nonCpG.500k')
temp = temp[temp$V4!='.',]
x = temp$V4
x = as.numeric(x)
x = x[!is.na(x)]
sum(x==0)/length(x)
[1] 0.1485457
range(x)
[1]  0 16
s = temp$V5
s = as.numeric(s)
range(s)
[1] 0.000000 6.358331
plot(x,pch='.',col='grey80',cex=2)

plot(s,pch='.',col='grey80',cex=2)

Try smash poisson on the count \(x\),

fit_smash = smash.poiss(x)
plot(x,pch='.',col='grey80',cex=2,xlab='position',main='C to T, 500k')
lines(fit_smash)
legend('topleft',c('data','smash fit'),pch=c('.',NA),lty=c(NA,1))


sessionInfo()
R version 4.1.0 (2021-05-18)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS:   /software/R-4.1.0-no-openblas-el7-x86_64/lib64/R/lib/libRblas.so
LAPACK: /software/R-4.1.0-no-openblas-el7-x86_64/lib64/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C         LC_TIME=C           
 [4] LC_COLLATE=C         LC_MONETARY=C        LC_MESSAGES=C       
 [7] LC_PAPER=C           LC_NAME=C            LC_ADDRESS=C        
[10] LC_TELEPHONE=C       LC_MEASUREMENT=C     LC_IDENTIFICATION=C 

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] genlasso_1.6.1  igraph_1.4.1    Matrix_1.5-3    smashr_1.3-6   
[5] workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.10       horseshoe_0.2.0   invgamma_1.1      lattice_0.20-44  
 [5] rprojroot_2.0.2   digest_0.6.31     utf8_1.2.3        truncnorm_1.0-8  
 [9] R6_2.5.1          evaluate_0.14     ggplot2_3.4.1     highr_0.9        
[13] pillar_1.8.1      rlang_1.0.6       wavethresh_4.7.2  rstudioapi_0.13  
[17] data.table_1.14.8 ebnm_1.0-11       irlba_2.3.5.1     whisker_0.4      
[21] jquerylib_0.1.4   rmarkdown_2.9     splines_4.1.0     stringr_1.5.0    
[25] munsell_0.5.0     mixsqp_0.3-48     compiler_4.1.0    httpuv_1.6.1     
[29] xfun_0.24         pkgconfig_2.0.3   SQUAREM_2021.1    htmltools_0.5.4  
[33] tidyselect_1.2.0  tibble_3.1.8      fansi_1.0.4       dplyr_1.1.0      
[37] later_1.3.0       MASS_7.3-54       bitops_1.0-7      grid_4.1.0       
[41] jsonlite_1.8.4    gtable_0.3.1      lifecycle_1.0.3   git2r_0.28.0     
[45] magrittr_2.0.3    scales_1.2.1      cli_3.6.0         stringi_1.6.2    
[49] fs_1.5.0          promises_1.2.0.1  bslib_0.2.5.1     generics_0.1.3   
[53] vctrs_0.5.2       trust_0.1-8       tools_4.1.0       glue_1.6.2       
[57] fastmap_1.1.0     yaml_2.3.7        colorspace_2.1-0  ashr_2.2-54      
[61] caTools_1.18.2    deconvolveR_1.2-1 knitr_1.33        sass_0.4.0