suppressPackageStartupMessages(library(tidyverse))
devtools::load_all('~/Google Drive/My Drive/Scripts/R_packages/myUtilities/')
## ℹ Loading myUtilities
Settings
data_dir <- '/Volumes/Mitsu_NGS_3/METTL2A/'
wd <- "/Users/shuheimitsutomi/Google Drive/My Drive/Analysis/METTL2A/"
setwd(wd)
figdir <- paste0(wd, 'Figures/DRS_m3C_sites/Methods/')
tabledir <- paste0(wd, 'Tables/DRS_m3C_sites/')
pval_thresh <- .05
theme_set(
theme_classic(base_size = 7) +
theme(legend.position = 'bottom')
)
Functions
add_commonchange_info <- function(df) {
df |>
mutate(
intensity_up = case_when(
intensity_up_G == 'up' & intensity_up_I == 'up' ~ 'common',
intensity_up_G == 'up' ~ 'only G',
intensity_up_I == 'up' ~ 'only I',
.default = 'others'
),
intensity_down = case_when(
intensity_down_G == 'down' & intensity_down_I == 'down' ~ 'common',
intensity_down_G == 'down' ~ 'only G',
intensity_down_I == 'down' ~ 'only I',
.default = 'others'
),
dwell_up = case_when(
dwell_up_G == 'up' & dwell_up_I == 'up' ~ 'common',
dwell_up_G == 'up' ~ 'only G',
dwell_up_I == 'up' ~ 'only I',
.default = 'others'
),
dwell_down = case_when(
dwell_down_G == 'down' & dwell_down_I == 'down' ~ 'common',
dwell_down_G == 'down' ~ 'only G',
dwell_down_I == 'down' ~ 'only I',
.default = 'others'
),
GMM_change = case_when(
GMM_change_G == 'change' & GMM_change_I == 'change' ~ 'common',
GMM_change_G == 'change' ~ 'only G',
GMM_change_I == 'change' ~ 'only I',
.default = 'others'
)
)
}
calc_method_percentage <- function(df) {
df |>
group_by(params) |>
mutate(percentage = 100 * n / sum(n))
}
change_factor_levels <- function(df) {
df |>
mutate(
sig_in = factor(sig_in,
levels = c('only G', 'common', 'only I', 'others')),
params = factor(params,
levels = c('intensity_up', 'intensity_down',
'dwell_up', 'dwell_down', 'GMM_change'))
)
}
add_middle_Cinfo <- function(df) {
df |>
mutate(middle_base = str_sub(ref_kmer, 3,3)) |>
mutate(middle_isC = ifelse(middle_base == 'C', 'C', 'others'))
}
add_consecutive_C_info <- function(df) {
df |>
mutate(
have_CC_middle = ifelse(
grepl('.{1}CC.{2}', ref_kmer) | grepl('.{2}CC.{1}', ref_kmer),
'yes', 'no'
),
have_C3_middle = ifelse(
grepl('.{1}CCC.{1}', ref_kmer), 'yes', 'no'
)
) |>
mutate(
middleC_info = case_when(
have_C3_middle == 'yes' ~ 'C3',
have_CC_middle == 'yes' ~ 'C2',
middle_isC == 'C' ~ 'C1',
middle_isC == 'others' ~ 'others',
.default = NA
)
)
}
Read data
sampcomp_G <-
read_tsv(paste0(wd,
'Tables/DRS_sampcomp_results/siMETTL2A_G_sampcomp_results_2024-04-07.tsv.gz'
))
## Rows: 5884004 Columns: 27
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (10): transcript_id, ref_kmer, GMM_cov_type, cluster_counts, Logit_LOR, ...
## dbl (17): position, GMM_logit_pvalue, KS_dwell_pvalue, KS_intensity_pvalue, ...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
sampcomp_G
## # A tibble: 5,884,004 × 27
## position transcript_id ref_kmer GMM_logit_pvalue KS_dwell_pvalue
## <dbl> <chr> <chr> <dbl> <dbl>
## 1 1464 ENST00000264926.7 TCACA NA 1
## 2 1465 ENST00000264926.7 CACAT 1 1
## 3 1466 ENST00000264926.7 ACATA NA 1
## 4 1467 ENST00000264926.7 CATAA 1 1
## 5 1468 ENST00000264926.7 ATAAA NA 1
## 6 1473 ENST00000264926.7 AACGA 1 1
## 7 1475 ENST00000264926.7 CGATC NA 1
## 8 1486 ENST00000264926.7 ACACA NA 1
## 9 1501 ENST00000264926.7 CAAGA 1 1
## 10 1502 ENST00000264926.7 AAGAC NA 1
## # ℹ 5,883,994 more rows
## # ℹ 22 more variables: KS_intensity_pvalue <dbl>, GMM_cov_type <chr>,
## # GMM_n_clust <dbl>, cluster_counts <chr>, Logit_LOR <chr>,
## # c1_mean_intensity <dbl>, c2_mean_intensity <dbl>,
## # c1_median_intensity <dbl>, c2_median_intensity <dbl>,
## # c1_sd_intensity <dbl>, c2_sd_intensity <dbl>, c1_mean_dwell <dbl>,
## # c2_mean_dwell <dbl>, c1_median_dwell <dbl>, c2_median_dwell <dbl>, …
sampcomp_I <-
read_tsv(
paste0(wd, 'Tables/DRS_sampcomp_results/siMETTL2A_I_sampcomp_results_2024-04-07.tsv.gz'
))
## Rows: 3405923 Columns: 27
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (10): transcript_id, ref_kmer, GMM_cov_type, cluster_counts, Logit_LOR, ...
## dbl (17): position, GMM_logit_pvalue, KS_dwell_pvalue, KS_intensity_pvalue, ...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
sampcomp_I
## # A tibble: 3,405,923 × 27
## position transcript_id ref_kmer GMM_logit_pvalue KS_dwell_pvalue
## <dbl> <chr> <chr> <dbl> <dbl>
## 1 1036 ENST00000245046.7 GCACC 1.00 1.00
## 2 1037 ENST00000245046.7 CACCT 0.999 1.00
## 3 1039 ENST00000245046.7 CCTCT 0.999 1.00
## 4 1040 ENST00000245046.7 CTCTT 0.999 1.00
## 5 1041 ENST00000245046.7 TCTTG 0.999 1.00
## 6 1042 ENST00000245046.7 CTTGA 1.00 1.00
## 7 1043 ENST00000245046.7 TTGAA 0.999 1.00
## 8 1044 ENST00000245046.7 TGAAA NA 1.00
## 9 1047 ENST00000245046.7 AATAA 1.00 1.00
## 10 1048 ENST00000245046.7 ATAAA 0.999 1.00
## # ℹ 3,405,913 more rows
## # ℹ 22 more variables: KS_intensity_pvalue <dbl>, GMM_cov_type <chr>,
## # GMM_n_clust <dbl>, cluster_counts <chr>, Logit_LOR <chr>,
## # c1_mean_intensity <dbl>, c2_mean_intensity <dbl>,
## # c1_median_intensity <dbl>, c2_median_intensity <dbl>,
## # c1_sd_intensity <dbl>, c2_sd_intensity <dbl>, c1_mean_dwell <dbl>,
## # c2_mean_dwell <dbl>, c1_median_dwell <dbl>, c2_median_dwell <dbl>, …
Read annotation
espresso_AsPC1_annotation <-
read_tsv(
paste0(wd, 'Tables/Espresso_AsPC1_annotation_cleaned_2024-03-29.tsv')
) |>
select(starts_with('transcript_'), starts_with('gene_'), seqname)
## Rows: 36717 Columns: 14
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (12): seqname, source, feature, score, strand, frame, gene_id, transcrip...
## dbl (2): start, end
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Number of significant sites in each method
sampcomp_G |>
group_by(intensity_up, intensity_down) |>
reframe(n = n())
## # A tibble: 3 × 3
## intensity_up intensity_down n
## <chr> <chr> <int>
## 1 not down 150
## 2 not not 5880811
## 3 up not 3043
sampcomp_G |>
group_by(dwell_up, dwell_down) |>
reframe(n = n())
## # A tibble: 3 × 3
## dwell_up dwell_down n
## <chr> <chr> <int>
## 1 not down 40
## 2 not not 5883947
## 3 up not 17
sampcomp_G |>
group_by(GMM_change) |>
reframe(n = n())
## # A tibble: 3 × 2
## GMM_change n
## <chr> <int>
## 1 change 112
## 2 not 4122746
## 3 <NA> 1761146
sampcomp_I |>
group_by(intensity_up, intensity_down) |>
reframe(n = n())
## # A tibble: 3 × 3
## intensity_up intensity_down n
## <chr> <chr> <int>
## 1 not down 292
## 2 not not 3404487
## 3 up not 1144
sampcomp_I |>
group_by(dwell_up, dwell_down) |>
reframe(n = n())
## # A tibble: 3 × 3
## dwell_up dwell_down n
## <chr> <chr> <int>
## 1 not down 21
## 2 not not 3405875
## 3 up not 27
sampcomp_I |>
group_by(GMM_change) |>
reframe(n = n())
## # A tibble: 3 × 2
## GMM_change n
## <chr> <int>
## 1 change 240
## 2 not 2626931
## 3 <NA> 778752
Join results from G and I
sampcomp_results_joined <- left_join(
sampcomp_G, sampcomp_I,
by = join_by(position, transcript_id, ref_kmer),
suffix = c('_G', '_I')
) |>
add_commonchange_info() |>
add_middle_Cinfo() |>
add_consecutive_C_info() |>
left_join(espresso_AsPC1_annotation) |>
select(transcript_id, transcript_name, everything())
## Joining with `by = join_by(transcript_id)`
sampcomp_results_joined |>
export_tsv(outdir = tabledir, compression = 'gz')
##
## Exported to: /Users/shuheimitsutomi/Google Drive/My Drive/Analysis/METTL2A/Tables/DRS_m3C_sites/sampcomp_results_joined_2024-04-24.tsv.gz
## # A tibble: 5,884,004 × 67
## transcript_id transcript_name position ref_kmer GMM_logit_pvalue_G
## <chr> <chr> <dbl> <chr> <dbl>
## 1 ENST00000264926.7 RAD18-201 1464 TCACA NA
## 2 ENST00000264926.7 RAD18-201 1465 CACAT 1
## 3 ENST00000264926.7 RAD18-201 1466 ACATA NA
## 4 ENST00000264926.7 RAD18-201 1467 CATAA 1
## 5 ENST00000264926.7 RAD18-201 1468 ATAAA NA
## 6 ENST00000264926.7 RAD18-201 1473 AACGA 1
## 7 ENST00000264926.7 RAD18-201 1475 CGATC NA
## 8 ENST00000264926.7 RAD18-201 1486 ACACA NA
## 9 ENST00000264926.7 RAD18-201 1501 CAAGA 1
## 10 ENST00000264926.7 RAD18-201 1502 AAGAC NA
## # ℹ 5,883,994 more rows
## # ℹ 62 more variables: KS_dwell_pvalue_G <dbl>, KS_intensity_pvalue_G <dbl>,
## # GMM_cov_type_G <chr>, GMM_n_clust_G <dbl>, cluster_counts_G <chr>,
## # Logit_LOR_G <chr>, c1_mean_intensity_G <dbl>, c2_mean_intensity_G <dbl>,
## # c1_median_intensity_G <dbl>, c2_median_intensity_G <dbl>,
## # c1_sd_intensity_G <dbl>, c2_sd_intensity_G <dbl>, c1_mean_dwell_G <dbl>,
## # c2_mean_dwell_G <dbl>, c1_median_dwell_G <dbl>, c2_median_dwell_G <dbl>, …
Calculate commonly changed positions in each parameter
sampcomp_intensity_up <-
sampcomp_results_joined |>
group_by(intensity_up) |>
reframe(n = n()) |>
mutate(params = 'intensity_up') |>
pivot_wider(id_cols = c(params), names_from = intensity_up, values_from = n)
sampcomp_intensity_up
## # A tibble: 1 × 5
## params common `only G` `only I` others
## <chr> <int> <int> <int> <int>
## 1 intensity_up 605 2438 535 5880426
sampcomp_intensity_down <-
sampcomp_results_joined |>
group_by(intensity_down) |>
reframe(n = n()) |>
mutate(params = 'intensity_down') |>
pivot_wider(id_cols = c(params), names_from = intensity_down, values_from = n)
sampcomp_dwell_up <-
sampcomp_results_joined |>
group_by(dwell_up) |>
reframe(n = n()) |>
mutate(params = 'dwell_up') |>
pivot_wider(id_cols = c(params), names_from = dwell_up, values_from = n)
sampcomp_dwell_down <-
sampcomp_results_joined |>
group_by(dwell_down) |>
reframe(n = n()) |>
mutate(params = 'dwell_down') |>
pivot_wider(id_cols = c(params), names_from = dwell_down, values_from = n)
sampcomp_GMM_change <-
sampcomp_results_joined |>
group_by(GMM_change) |>
reframe(n = n()) |>
mutate(params = 'GMM_change') |>
pivot_wider(id_cols = c(params), names_from = GMM_change, values_from = n)
sampcomp_GMM_change
## # A tibble: 1 × 5
## params common `only G` `only I` others
## <chr> <int> <int> <int> <int>
## 1 GMM_change 32 80 208 5883684
BInd data of all parameters
sampcomp_sig_nums <- bind_rows(
sampcomp_intensity_up, sampcomp_intensity_down,
sampcomp_dwell_up , sampcomp_dwell_down, sampcomp_GMM_change
) |>
pivot_longer(cols = -params, names_to = 'sig_in', values_to = 'n') |>
calc_method_percentage() |>
change_factor_levels()
sampcomp_sig_nums |>
export_tsv(outdir = tabledir, compression = 'gz')
##
## Exported to: /Users/shuheimitsutomi/Google Drive/My Drive/Analysis/METTL2A/Tables/DRS_m3C_sites/sampcomp_sig_nums_2024-04-24.tsv.gz
## # A tibble: 20 × 4
## # Groups: params [5]
## params sig_in n percentage
## <fct> <fct> <int> <dbl>
## 1 intensity_up common 605 0.0103
## 2 intensity_up only G 2438 0.0414
## 3 intensity_up only I 535 0.00909
## 4 intensity_up others 5880426 99.9
## 5 intensity_down common 21 0.000357
## 6 intensity_down only G 129 0.00219
## 7 intensity_down only I 270 0.00459
## 8 intensity_down others 5883584 100.
## 9 dwell_up common 6 0.000102
## 10 dwell_up only G 11 0.000187
## 11 dwell_up only I 21 0.000357
## 12 dwell_up others 5883966 100.
## 13 dwell_down common 7 0.000119
## 14 dwell_down only G 33 0.000561
## 15 dwell_down only I 14 0.000238
## 16 dwell_down others 5883950 100.
## 17 GMM_change common 32 0.000544
## 18 GMM_change only G 80 0.00136
## 19 GMM_change only I 208 0.00354
## 20 GMM_change others 5883684 100.
sampcomp_sig_nums_barplot <-
sampcomp_sig_nums |>
filter(sig_in == 'common') |>
#filter(sig_in != 'others') |>
ggplot(aes(x = fct_rev(params), y = n, fill = params)) +
geom_bar(stat = 'identity') +
coord_flip() +
scale_fill_manual(
values = c('#f23e3e', '#3e3ef2', '#f23ef2', '#3ef23e', 'gray30')
)
#scale_fill_manual(values = c('#A3A3F9', '#F23E3E', '#37D9CC'))
#scale_fill_viridis_d()
sampcomp_sig_nums_barplot |>
ggsave_multiple_formats(
width = 5, height = 5, fontsize = 7, outdir = figdir
)
C content
whole_kmer_c_percentage <-
sampcomp_results_joined |>
group_by(middleC_info) |>
reframe(n = n()) |>
mutate(percentage = 100 * n / sum(n)) |>
mutate(params = 'whole_kmer') |>
pivot_wider(
id_cols = params, names_from = middleC_info, values_from = percentage
) |>
mutate(sig_in = 'common')
whole_kmer_c_percentage
## # A tibble: 1 × 6
## params C1 C2 C3 others sig_in
## <chr> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 whole_kmer 11.6 8.94 1.59 77.9 common
intensity_up_c_percentage <-
sampcomp_results_joined |>
group_by(intensity_up, middleC_info) |>
reframe(n = n()) |>
group_by(intensity_up) |>
mutate(percentage = 100 * n / sum(n)) |>
mutate(params = 'intensity_up') |>
rename(sig_in = intensity_up) |>
pivot_wider(
id_cols = c(params, sig_in),
names_from = c(middleC_info), values_from = percentage
)
intensity_up_c_percentage
## # A tibble: 4 × 6
## # Groups: sig_in [4]
## params sig_in C1 C2 C3 others
## <chr> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 intensity_up common 7.60 40.8 32.4 19.2
## 2 intensity_up only G 14.0 31.7 16.8 37.5
## 3 intensity_up only I 7.10 39.8 8.79 44.3
## 4 intensity_up others 11.6 8.93 1.58 77.9
intensity_down_c_percentage <-
sampcomp_results_joined |>
group_by(intensity_down, middleC_info) |>
reframe(n = n()) |>
group_by(intensity_down) |>
mutate(percentage = 100 * n / sum(n)) |>
mutate(params = 'intensity_down') |>
rename(sig_in = intensity_down) |>
pivot_wider(
id_cols = c(params, sig_in),
names_from = c(middleC_info), values_from = percentage
)
intensity_down_c_percentage
## # A tibble: 4 × 6
## # Groups: sig_in [4]
## params sig_in C1 C2 C3 others
## <chr> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 intensity_down common 19.0 4.76 9.52 66.7
## 2 intensity_down only G 10.9 4.65 0.775 83.7
## 3 intensity_down only I 12.6 4.81 0.370 82.2
## 4 intensity_down others 11.6 8.94 1.59 77.9
dwell_up_c_percentage <-
sampcomp_results_joined |>
group_by(dwell_up, middleC_info) |>
reframe(n = n()) |>
group_by(dwell_up) |>
mutate(percentage = 100 * n / sum(n)) |>
mutate(params = 'dwell_up') |>
rename(sig_in = dwell_up) |>
pivot_wider(
id_cols = c(params, sig_in),
names_from = c(middleC_info), values_from = percentage
)
dwell_up_c_percentage
## # A tibble: 4 × 6
## # Groups: sig_in [4]
## params sig_in C1 others C2 C3
## <chr> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 dwell_up common 33.3 66.7 NA NA
## 2 dwell_up only G 27.3 54.5 9.09 9.09
## 3 dwell_up only I 14.3 71.4 9.52 4.76
## 4 dwell_up others 11.6 77.9 8.94 1.59
dwell_down_c_percentage <-
sampcomp_results_joined |>
group_by(dwell_down, middleC_info) |>
reframe(n = n()) |>
group_by(dwell_down) |>
mutate(percentage = 100 * n / sum(n)) |>
mutate(params = 'dwell_down') |>
rename(sig_in = dwell_down) |>
pivot_wider(
id_cols = c(params, sig_in),
names_from = c(middleC_info), values_from = percentage
)
dwell_down_c_percentage
## # A tibble: 4 × 6
## # Groups: sig_in [4]
## params sig_in C1 C3 others C2
## <chr> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 dwell_down common 14.3 28.6 57.1 NA
## 2 dwell_down only G 12.1 21.2 45.5 21.2
## 3 dwell_down only I NA NA 78.6 21.4
## 4 dwell_down others 11.6 1.59 77.9 8.94
GMM_change_c_percentage <-
sampcomp_results_joined |>
group_by(GMM_change, middleC_info) |>
reframe(n = n()) |>
group_by(GMM_change) |>
mutate(percentage = 100 * n / sum(n)) |>
mutate(params = 'GMM_change') |>
rename(sig_in = GMM_change) |>
pivot_wider(
id_cols = c(params, sig_in),
names_from = c(middleC_info), values_from = percentage
)
GMM_change_c_percentage
## # A tibble: 4 × 6
## # Groups: sig_in [4]
## params sig_in C1 C2 C3 others
## <chr> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 GMM_change common 25 3.12 12.5 59.4
## 2 GMM_change only G 10 21.2 10 58.8
## 3 GMM_change only I 7.21 15.4 1.92 75.5
## 4 GMM_change others 11.6 8.94 1.59 77.9
c_percentage <- bind_rows(
intensity_up_c_percentage, intensity_down_c_percentage,
dwell_up_c_percentage, dwell_down_c_percentage,
GMM_change_c_percentage, whole_kmer_c_percentage
)
c_percentage
## # A tibble: 21 × 6
## # Groups: sig_in [4]
## params sig_in C1 C2 C3 others
## <chr> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 intensity_up common 7.60 40.8 32.4 19.2
## 2 intensity_up only G 14.0 31.7 16.8 37.5
## 3 intensity_up only I 7.10 39.8 8.79 44.3
## 4 intensity_up others 11.6 8.93 1.58 77.9
## 5 intensity_down common 19.0 4.76 9.52 66.7
## 6 intensity_down only G 10.9 4.65 0.775 83.7
## 7 intensity_down only I 12.6 4.81 0.370 82.2
## 8 intensity_down others 11.6 8.94 1.59 77.9
## 9 dwell_up common 33.3 NA NA 66.7
## 10 dwell_up only G 27.3 9.09 9.09 54.5
## # ℹ 11 more rows
param_levels <- c(
'intensity_up', 'intensity_down', 'dwell_up', 'dwell_down',
'GMM_change', 'whole_kmer'
)
c_percentage_long <-
c_percentage |>
pivot_longer(
cols = -c(params, sig_in),
names_to = 'base', values_to = 'percentage'
) |>
mutate(params = factor(params, param_levels))
c_percentage_long |>
export_tsv(outdir = tabledir, compression = 'gz')
##
## Exported to: /Users/shuheimitsutomi/Google Drive/My Drive/Analysis/METTL2A/Tables/DRS_m3C_sites/c_percentage_long_2024-04-24.tsv.gz
## # A tibble: 84 × 4
## # Groups: sig_in [4]
## params sig_in base percentage
## <fct> <chr> <chr> <dbl>
## 1 intensity_up common C1 7.60
## 2 intensity_up common C2 40.8
## 3 intensity_up common C3 32.4
## 4 intensity_up common others 19.2
## 5 intensity_up only G C1 14.0
## 6 intensity_up only G C2 31.7
## 7 intensity_up only G C3 16.8
## 8 intensity_up only G others 37.5
## 9 intensity_up only I C1 7.10
## 10 intensity_up only I C2 39.8
## # ℹ 74 more rows
c_percentage_barplot <-
c_percentage_long |>
filter(sig_in == 'common') |>
mutate(base = factor(base, levels = c('C3', 'C2', 'C1', 'others'))) |>
ggplot(aes(
x = params |> fct_rev(), y = percentage,
fill = base |> fct_rev())) +
geom_bar(stat = 'identity', colour = 'gray20', size = 0.4) +
scale_y_continuous(breaks = seq(0, 100, 20)) +
scale_fill_manual(
values = c('#BEBEBE', '#c5c5fb', '#7777F5', '#3131c1')
) +
coord_flip()
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
c_percentage_barplot |>
ggsave_multiple_formats(
outdir = figdir, width = 4, height = 4, fontsize = 7
)
## Warning: Removed 3 rows containing missing values (`position_stack()`).
## Warning: Removed 3 rows containing missing values (`position_stack()`).
## Removed 3 rows containing missing values (`position_stack()`).
## Removed 3 rows containing missing values (`position_stack()`).
## Removed 3 rows containing missing values (`position_stack()`).
Sesison info
sessioninfo::session_info()
## ─ Session info ───────────────────────────────────────────────────────────────
## setting value
## version R version 4.3.1 (2023-06-16)
## os macOS Sonoma 14.3
## system aarch64, darwin20
## ui X11
## language (EN)
## collate en_US.UTF-8
## ctype en_US.UTF-8
## tz Asia/Tokyo
## date 2024-04-24
## pandoc 3.1.1 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown)
##
## ─ Packages ───────────────────────────────────────────────────────────────────
## ! package * version date (UTC) lib source
## abind 1.4-5 2016-07-21 [1] CRAN (R 4.3.0)
## backports 1.4.1 2021-12-13 [1] CRAN (R 4.3.0)
## bit 4.0.5 2022-11-15 [1] CRAN (R 4.3.0)
## bit64 4.0.5 2020-08-30 [1] CRAN (R 4.3.0)
## broom 1.0.5 2023-06-09 [1] CRAN (R 4.3.0)
## bslib 0.5.1 2023-08-11 [1] CRAN (R 4.3.0)
## cachem 1.0.8 2023-05-01 [1] CRAN (R 4.3.0)
## callr 3.7.3 2022-11-02 [1] CRAN (R 4.3.0)
## car 3.1-2 2023-03-30 [1] CRAN (R 4.3.0)
## carData 3.0-5 2022-01-06 [1] CRAN (R 4.3.0)
## class 7.3-22 2023-05-03 [1] CRAN (R 4.3.1)
## cli 3.6.1 2023-03-23 [1] CRAN (R 4.3.0)
## codetools 0.2-19 2023-02-01 [1] CRAN (R 4.3.1)
## colorspace 2.1-0 2023-01-23 [1] CRAN (R 4.3.0)
## crayon 1.5.2 2022-09-29 [1] CRAN (R 4.3.0)
## data.table 1.14.8 2023-02-17 [1] CRAN (R 4.3.0)
## desc 1.4.2 2022-09-08 [1] CRAN (R 4.3.0)
## devtools 2.4.5 2022-10-11 [1] CRAN (R 4.3.0)
## dials 1.2.0 2023-04-03 [1] CRAN (R 4.3.0)
## DiceDesign 1.9 2021-02-13 [1] CRAN (R 4.3.0)
## digest 0.6.33 2023-07-07 [1] CRAN (R 4.3.0)
## dplyr * 1.1.2 2023-04-20 [1] CRAN (R 4.3.0)
## ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.3.0)
## evaluate 0.21 2023-05-05 [1] CRAN (R 4.3.0)
## fansi 1.0.4 2023-01-22 [1] CRAN (R 4.3.0)
## farver 2.1.1 2022-07-06 [1] CRAN (R 4.3.0)
## fastmap 1.1.1 2023-02-24 [1] CRAN (R 4.3.0)
## forcats * 1.0.0 2023-01-29 [1] CRAN (R 4.3.0)
## foreach 1.5.2 2022-02-02 [1] CRAN (R 4.3.0)
## fs 1.6.3 2023-07-20 [1] CRAN (R 4.3.0)
## furrr 0.3.1 2022-08-15 [1] CRAN (R 4.3.0)
## future 1.33.0 2023-07-01 [1] CRAN (R 4.3.0)
## future.apply 1.11.0 2023-05-21 [1] CRAN (R 4.3.0)
## generics 0.1.3 2022-07-05 [1] CRAN (R 4.3.0)
## ggforce 0.4.1 2022-10-04 [1] CRAN (R 4.3.0)
## ggplot2 * 3.4.3 2023-08-14 [1] CRAN (R 4.3.0)
## ggpubr 0.6.0 2023-02-10 [1] CRAN (R 4.3.0)
## ggrepel 0.9.3 2023-02-03 [1] CRAN (R 4.3.0)
## ggsignif 0.6.4 2022-10-13 [1] CRAN (R 4.3.0)
## globals 0.16.2 2022-11-21 [1] CRAN (R 4.3.0)
## glue 1.6.2 2022-02-24 [1] CRAN (R 4.3.0)
## gower 1.0.1 2022-12-22 [1] CRAN (R 4.3.0)
## GPfit 1.0-8 2019-02-08 [1] CRAN (R 4.3.0)
## gtable 0.3.3 2023-03-21 [1] CRAN (R 4.3.0)
## hardhat 1.3.0 2023-03-30 [1] CRAN (R 4.3.0)
## highr 0.10 2022-12-22 [1] CRAN (R 4.3.0)
## hms 1.1.3 2023-03-21 [1] CRAN (R 4.3.0)
## htmltools 0.5.6 2023-08-10 [1] CRAN (R 4.3.0)
## htmlwidgets 1.6.2 2023-03-17 [1] CRAN (R 4.3.0)
## httpuv 1.6.11 2023-05-11 [1] CRAN (R 4.3.0)
## ipred 0.9-14 2023-03-09 [1] CRAN (R 4.3.0)
## iterators 1.0.14 2022-02-05 [1] CRAN (R 4.3.0)
## jquerylib 0.1.4 2021-04-26 [1] CRAN (R 4.3.0)
## jsonlite 1.8.7 2023-06-29 [1] CRAN (R 4.3.0)
## knitr 1.43 2023-05-25 [1] CRAN (R 4.3.0)
## labeling 0.4.2 2020-10-20 [1] CRAN (R 4.3.0)
## later 1.3.1 2023-05-02 [1] CRAN (R 4.3.0)
## lattice 0.21-8 2023-04-05 [1] CRAN (R 4.3.1)
## lava 1.7.2.1 2023-02-27 [1] CRAN (R 4.3.0)
## lhs 1.1.6 2022-12-17 [1] CRAN (R 4.3.0)
## lifecycle 1.0.3 2022-10-07 [1] CRAN (R 4.3.0)
## listenv 0.9.0 2022-12-16 [1] CRAN (R 4.3.0)
## lubridate * 1.9.2 2023-02-10 [1] CRAN (R 4.3.0)
## magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.3.0)
## MASS 7.3-60 2023-05-04 [1] CRAN (R 4.3.1)
## Matrix 1.6-1 2023-08-14 [1] CRAN (R 4.3.0)
## memoise 2.0.1 2021-11-26 [1] CRAN (R 4.3.0)
## mime 0.12 2021-09-28 [1] CRAN (R 4.3.0)
## miniUI 0.1.1.1 2018-05-18 [1] CRAN (R 4.3.0)
## munsell 0.5.0 2018-06-12 [1] CRAN (R 4.3.0)
## R myUtilities * 0.0.0.9000 <NA> [?] <NA>
## nnet 7.3-19 2023-05-03 [1] CRAN (R 4.3.1)
## parallelly 1.36.0 2023-05-26 [1] CRAN (R 4.3.0)
## parsnip 1.1.1 2023-08-17 [1] CRAN (R 4.3.0)
## pillar 1.9.0 2023-03-22 [1] CRAN (R 4.3.0)
## pkgbuild 1.4.2 2023-06-26 [1] CRAN (R 4.3.0)
## pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.3.0)
## pkgload 1.3.2.1 2023-07-08 [1] CRAN (R 4.3.0)
## polyclip 1.10-4 2022-10-20 [1] CRAN (R 4.3.0)
## prettyunits 1.1.1 2020-01-24 [1] CRAN (R 4.3.0)
## processx 3.8.2 2023-06-30 [1] CRAN (R 4.3.0)
## prodlim 2023.08.28 2023-08-28 [1] CRAN (R 4.3.0)
## profvis 0.3.8 2023-05-02 [1] CRAN (R 4.3.0)
## promises 1.2.1 2023-08-10 [1] CRAN (R 4.3.0)
## ps 1.7.5 2023-04-18 [1] CRAN (R 4.3.0)
## purrr * 1.0.2 2023-08-10 [1] CRAN (R 4.3.0)
## R6 2.5.1 2021-08-19 [1] CRAN (R 4.3.0)
## ragg 1.2.5 2023-01-12 [1] CRAN (R 4.3.0)
## Rcpp 1.0.11 2023-07-06 [1] CRAN (R 4.3.0)
## readr * 2.1.4 2023-02-10 [1] CRAN (R 4.3.0)
## recipes 1.0.8 2023-08-25 [1] CRAN (R 4.3.0)
## remotes 2.4.2.1 2023-07-18 [1] CRAN (R 4.3.0)
## rlang 1.1.1 2023-04-28 [1] CRAN (R 4.3.0)
## rmarkdown 2.24 2023-08-14 [1] CRAN (R 4.3.0)
## rpart 4.1.19 2022-10-21 [1] CRAN (R 4.3.1)
## rprojroot 2.0.3 2022-04-02 [1] CRAN (R 4.3.0)
## rsample 1.2.0 2023-08-23 [1] CRAN (R 4.3.0)
## rstatix 0.7.2 2023-02-01 [1] CRAN (R 4.3.0)
## rstudioapi 0.15.0 2023-07-07 [1] CRAN (R 4.3.0)
## sass 0.4.7 2023-07-15 [1] CRAN (R 4.3.0)
## scales 1.2.1 2022-08-20 [1] CRAN (R 4.3.0)
## sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.3.0)
## shiny 1.7.5 2023-08-12 [1] CRAN (R 4.3.0)
## stringi 1.7.12 2023-01-11 [1] CRAN (R 4.3.0)
## stringr * 1.5.0 2022-12-02 [1] CRAN (R 4.3.0)
## survival 3.5-5 2023-03-12 [1] CRAN (R 4.3.1)
## svglite 2.1.1 2023-01-10 [1] CRAN (R 4.3.0)
## systemfonts 1.0.4 2022-02-11 [1] CRAN (R 4.3.0)
## textshaping 0.3.6 2021-10-13 [1] CRAN (R 4.3.0)
## tibble * 3.2.1 2023-03-20 [1] CRAN (R 4.3.0)
## tidyr * 1.3.0 2023-01-24 [1] CRAN (R 4.3.0)
## tidyselect 1.2.0 2022-10-10 [1] CRAN (R 4.3.0)
## tidyverse * 2.0.0 2023-02-22 [1] CRAN (R 4.3.0)
## timechange 0.2.0 2023-01-11 [1] CRAN (R 4.3.0)
## timeDate 4022.108 2023-01-07 [1] CRAN (R 4.3.0)
## tune 1.1.2 2023-08-23 [1] CRAN (R 4.3.0)
## tweenr 2.0.2 2022-09-06 [1] CRAN (R 4.3.0)
## tzdb 0.4.0 2023-05-12 [1] CRAN (R 4.3.0)
## urlchecker 1.0.1 2021-11-30 [1] CRAN (R 4.3.0)
## usethis 2.2.2 2023-07-06 [1] CRAN (R 4.3.0)
## utf8 1.2.3 2023-01-31 [1] CRAN (R 4.3.0)
## vctrs 0.6.3 2023-06-14 [1] CRAN (R 4.3.0)
## vroom 1.6.3 2023-04-28 [1] CRAN (R 4.3.0)
## withr 2.5.0 2022-03-03 [1] CRAN (R 4.3.0)
## workflows 1.1.3 2023-02-22 [1] CRAN (R 4.3.0)
## xfun 0.40 2023-08-09 [1] CRAN (R 4.3.0)
## xtable 1.8-4 2019-04-21 [1] CRAN (R 4.3.0)
## yaml 2.3.7 2023-01-23 [1] CRAN (R 4.3.0)
## yardstick 1.2.0 2023-04-21 [1] CRAN (R 4.3.0)
##
## [1] /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library
##
## R ── Package was removed from disk.
##
## ──────────────────────────────────────────────────────────────────────────────
