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Introduction

library(Damsel)
library(plyranges)
Loading required package: BiocGenerics

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

    IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':

    anyDuplicated, aperm, append, as.data.frame, basename, cbind,
    colnames, dirname, do.call, duplicated, eval, evalq, Filter, Find,
    get, grep, grepl, intersect, is.unsorted, lapply, Map, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
    Position, rank, rbind, Reduce, rownames, sapply, setdiff, table,
    tapply, union, unique, unsplit, which.max, which.min
Loading required package: IRanges
Warning: package 'IRanges' was built under R version 4.4.1
Loading required package: S4Vectors
Warning: package 'S4Vectors' was built under R version 4.4.1
Loading required package: stats4

Attaching package: 'S4Vectors'
The following object is masked from 'package:utils':

    findMatches
The following objects are masked from 'package:base':

    expand.grid, I, unname
Loading required package: GenomicRanges
Loading required package: GenomeInfoDb

Attaching package: 'plyranges'
The following object is masked from 'package:IRanges':

    slice
The following object is masked from 'package:stats':

    filter
library(dplyr)

Attaching package: 'dplyr'
The following objects are masked from 'package:plyranges':

    between, n, n_distinct
The following objects are masked from 'package:GenomicRanges':

    intersect, setdiff, union
The following object is masked from 'package:GenomeInfoDb':

    intersect
The following objects are masked from 'package:IRanges':

    collapse, desc, intersect, setdiff, slice, union
The following objects are masked from 'package:S4Vectors':

    first, intersect, rename, setdiff, setequal, union
The following objects are masked from 'package:BiocGenerics':

    combine, intersect, setdiff, union
The following objects are masked from 'package:stats':

    filter, lag
The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union
library(ggplot2)
library(BSgenome.Dmelanogaster.UCSC.dm6)
Loading required package: BSgenome
Loading required package: Biostrings
Loading required package: XVector

Attaching package: 'Biostrings'
The following object is masked from 'package:base':

    strsplit
Loading required package: BiocIO
Loading required package: rtracklayer

Attaching package: 'rtracklayer'
The following object is masked from 'package:BiocIO':

    FileForFormat
library(edgeR)
Warning: package 'edgeR' was built under R version 4.4.1
Loading required package: limma
Warning: package 'limma' was built under R version 4.4.1

Attaching package: 'limma'
The following object is masked from 'package:BiocGenerics':

    plotMA
damsel_counts <- rbind(readRDS("../data/damsel_counts_a.rds"), readRDS("../data/damsel_counts_b.rds"))
gatc_regions <- getGatcRegions(BSgenome.Dmelanogaster.UCSC.dm6::BSgenome.Dmelanogaster.UCSC.dm6)$regions
Warning in .local(x, row.names, optional, ...): 'optional' argument was ignored
Warning in .local(x, row.names, optional, ...): 'optional' argument was ignored
Warning in .local(x, row.names, optional, ...): 'optional' argument was ignored
Warning in .local(x, row.names, optional, ...): 'optional' argument was ignored
Warning in .local(x, row.names, optional, ...): 'optional' argument was ignored
Warning in .local(x, row.names, optional, ...): 'optional' argument was ignored
Warning in .local(x, row.names, optional, ...): 'optional' argument was ignored
Warning in GenomeInfoDb::renameSeqlevels(x = df_, value = newStyle): invalid
seqlevels 'chrM' ignored

Normally, the design matrix in Damsel for differential testing has 2 columns, 1 for the grouping factor (Dam, Fusion), and an optional column for the replicates.

Normal format * A: group1 = dam1, dam2 | group2 = fusion1, fusion2

False positive testing * B: group1 = dam1, fusion2 | group2 = dam2, fusion1 * C: group1 = dam1, fusion1 | group2 = dam2, fusion2

To do Damsel’s false positive testing, the replicates will not be included.

A - Normal analysis

The Samples are: * D1: Dam1 * F1: Sd1 * D2: Dam2 * F2: Sd2

head(damsel_counts)
           Position seqnames start end width strand dam_1_SRR7948872.BAM
chr2L-82   chr2L-82    chr2L    82 230   149      *                  1.0
chr2L-231 chr2L-231    chr2L   231 371   141      *                  1.5
chr2L-372 chr2L-372    chr2L   372 539   168      *                  2.5
chr2L-540 chr2L-540    chr2L   540 688   149      *                  2.0
chr2L-689 chr2L-689    chr2L   689 829   141      *                  0.0
chr2L-830 chr2L-830    chr2L   830 997   168      *                  0.0
          sd_1_SRR7948874.BAM dam_2_SRR7948876.BAM sd_2_SRR7948877.BAM
chr2L-82                 0.33                  0.0                 0.0
chr2L-231                5.67                 87.0                57.5
chr2L-372                6.17                 88.0                58.5
chr2L-540                4.83                  0.0                 0.0
chr2L-689                0.00                  0.5                 0.5
chr2L-830                1.33                  4.5                 3.5
testDmRegions(makeDGE2(damsel_counts, min.samples=2, include_replicate = TRUE), regions = gatc_regions) %>% 
  group_by(meth_status) %>%
  summarise(n=n())
Warning in plot.xy(xy.coords(x, y), type = type, ...): "panel.first" is not a
graphical parameter

Version Author Date
e240e57 caitlinpage 2024-10-07
# A tibble: 3 × 2
  meth_status       n
  <chr>         <int>
1 No_sig       113787
2 Not_included 232982
3 Upreg         36885

Normally when Damsel runs, the design matrix looks like this:

makeDGE2(damsel_counts, min.samples=2, include_replicate = TRUE)$design
  (Intercept) groupFusion rep
1           1           0   0
2           1           1   0
3           1           0   1
4           1           1   1
attr(,"assign")
[1] 0 1 2
attr(,"contrasts")
attr(,"contrasts")$group
[1] "contr.treatment"

However, replicates can be exlcuded - making the design look like this:

makeDGE2(damsel_counts, min.samples=2, include_replicate = FALSE)$design
  (Intercept) groupFusion
1           1           0
2           1           1
3           1           0
4           1           1
attr(,"assign")
[1] 0 1
attr(,"contrasts")
attr(,"contrasts")$group
[1] "contr.treatment"
source("../code/helper-vissers.R")
test_vissers_dm(damsel_counts)$design
  (Intercept) groupSd
1           1       0
2           1       1
3           1       0
4           1       1
attr(,"assign")
[1] 0 1
attr(,"contrasts")
attr(,"contrasts")$group
[1] "contr.treatment"
test_vissers_dm(damsel_counts)$results %>% 
  group_by(significant) %>%
  summarise(n=n())
# A tibble: 3 × 2
  significant      n
        <int>  <int>
1          -1  20346
2           0 110709
3           1  19630

B: False positive test

  • group1 = dam1, fusion2 | group2 = dam2, fusion1
head(damsel_counts)
           Position seqnames start end width strand dam_1_SRR7948872.BAM
chr2L-82   chr2L-82    chr2L    82 230   149      *                  1.0
chr2L-231 chr2L-231    chr2L   231 371   141      *                  1.5
chr2L-372 chr2L-372    chr2L   372 539   168      *                  2.5
chr2L-540 chr2L-540    chr2L   540 688   149      *                  2.0
chr2L-689 chr2L-689    chr2L   689 829   141      *                  0.0
chr2L-830 chr2L-830    chr2L   830 997   168      *                  0.0
          sd_1_SRR7948874.BAM dam_2_SRR7948876.BAM sd_2_SRR7948877.BAM
chr2L-82                 0.33                  0.0                 0.0
chr2L-231                5.67                 87.0                57.5
chr2L-372                6.17                 88.0                58.5
chr2L-540                4.83                  0.0                 0.0
chr2L-689                0.00                  0.5                 0.5
chr2L-830                1.33                  4.5                 3.5
  • rearrange samples to reflect new groups
group <- c("Dam", "Fusion", "Fusion", "Dam")

damsel_counts_a <- damsel_counts[,c(1:7,9,10,8)]
head(damsel_counts_a)
           Position seqnames start end width strand dam_1_SRR7948872.BAM
chr2L-82   chr2L-82    chr2L    82 230   149      *                  1.0
chr2L-231 chr2L-231    chr2L   231 371   141      *                  1.5
chr2L-372 chr2L-372    chr2L   372 539   168      *                  2.5
chr2L-540 chr2L-540    chr2L   540 688   149      *                  2.0
chr2L-689 chr2L-689    chr2L   689 829   141      *                  0.0
chr2L-830 chr2L-830    chr2L   830 997   168      *                  0.0
          dam_2_SRR7948876.BAM sd_2_SRR7948877.BAM sd_1_SRR7948874.BAM
chr2L-82                   0.0                 0.0                0.33
chr2L-231                 87.0                57.5                5.67
chr2L-372                 88.0                58.5                6.17
chr2L-540                  0.0                 0.0                4.83
chr2L-689                  0.5                 0.5                0.00
chr2L-830                  4.5                 3.5                1.33

Test Damsel

group <- c("Dam", "Fusion", "Fusion", "Dam")
makeDGE2(damsel_counts, min.samples = 2, include_replicate=FALSE, group = group)$design
  (Intercept) groupFusion
1           1           0
2           1           1
3           1           1
4           1           0
attr(,"assign")
[1] 0 1
attr(,"contrasts")
attr(,"contrasts")$group
[1] "contr.treatment"
testDmRegions(makeDGE2(damsel_counts, min.samples = 2, include_replicate=FALSE, group = group), gatc_regions) %>% 
  group_by(meth_status) %>% summarise(n=n())
Warning in plot.xy(xy.coords(x, y), type = type, ...): "panel.first" is not a
graphical parameter

Version Author Date
b6852e1 caitlinpage 2024-10-07
# A tibble: 2 × 2
  meth_status       n
  <chr>         <int>
1 No_sig       150672
2 Not_included 232982

Test Vissers

source("../code/helper-vissers.R")
group <- c("Dam", "Fusion", "Fusion", "Dam")
test_vissers_dm(damsel_counts, modify_group = group)$design
  (Intercept) groupFusion
1           1           0
2           1           1
3           1           1
4           1           0
attr(,"assign")
[1] 0 1
attr(,"contrasts")
attr(,"contrasts")$group
[1] "contr.treatment"
test_vissers_dm(damsel_counts, modify_group = group)$results %>% group_by(significant) %>% summarise(n=n())
# A tibble: 1 × 2
  significant      n
        <int>  <int>
1           0 150685

C - false positive test

  • C: group1 = dam1, fusion1 | group2 = dam2, fusion2
head(damsel_counts)
           Position seqnames start end width strand dam_1_SRR7948872.BAM
chr2L-82   chr2L-82    chr2L    82 230   149      *                  1.0
chr2L-231 chr2L-231    chr2L   231 371   141      *                  1.5
chr2L-372 chr2L-372    chr2L   372 539   168      *                  2.5
chr2L-540 chr2L-540    chr2L   540 688   149      *                  2.0
chr2L-689 chr2L-689    chr2L   689 829   141      *                  0.0
chr2L-830 chr2L-830    chr2L   830 997   168      *                  0.0
          sd_1_SRR7948874.BAM dam_2_SRR7948876.BAM sd_2_SRR7948877.BAM
chr2L-82                 0.33                  0.0                 0.0
chr2L-231                5.67                 87.0                57.5
chr2L-372                6.17                 88.0                58.5
chr2L-540                4.83                  0.0                 0.0
chr2L-689                0.00                  0.5                 0.5
chr2L-830                1.33                  4.5                 3.5

Test Damsel

group <- c("Dam", "Dam", "Fusion", "Fusion")
makeDGE2(damsel_counts, min.samples = 2, include_replicate=FALSE, group = group)$design
  (Intercept) groupFusion
1           1           0
2           1           0
3           1           1
4           1           1
attr(,"assign")
[1] 0 1
attr(,"contrasts")
attr(,"contrasts")$group
[1] "contr.treatment"
testDmRegions(makeDGE2(damsel_counts, min.samples = 2, include_replicate=FALSE, group = group), gatc_regions) %>% 
  group_by(meth_status) %>% summarise(n=n())
Warning in plot.xy(xy.coords(x, y), type = type, ...): "panel.first" is not a
graphical parameter

Version Author Date
e240e57 caitlinpage 2024-10-07
57141fa caitlinpage 2024-10-07
# A tibble: 2 × 2
  meth_status       n
  <chr>         <int>
1 No_sig       150672
2 Not_included 232982

Test Vissers

source("../code/helper-vissers.R")
group <- c("Dam", "Dam", "Fusion", "Fusion")
test_vissers_dm(damsel_counts, modify_group = group)$design
  (Intercept) groupFusion
1           1           0
2           1           0
3           1           1
4           1           1
attr(,"assign")
[1] 0 1
attr(,"contrasts")
attr(,"contrasts")$group
[1] "contr.treatment"
test_vissers_dm(damsel_counts, modify_group = group)$results %>% group_by(significant) %>% summarise(n=n())
# A tibble: 3 × 2
  significant      n
        <int>  <int>
1          -1   1112
2           0 148319
3           1   1254
source("../code/helper-vissers.R")
test_vissers_peaks(damsel_counts, modify_group = group)
    seqnames    start      end tags      pen aveLogFC sig
1    1660144  1660144  1664422    2 1.000000 2.998255   0
2    1769930  1769930  1773531    2 1.000000 2.445128   0
3    2341183  2341183  2344664    2 1.000000 2.909788   0
4    3183447  3183447  3185888    2 1.000000 3.374901   0
5    4722235  4722235  4724195    2 1.000000 3.079339   0
6    5563475  5563475  5565725    2 1.000000 2.766295   0
7    9091628  9091628  9096153    2 1.000000 3.321103   1
8   10554719 10554719 10559411    2 1.000000 3.179526   1
9   10864436 10864436 10868376    2 1.000000 2.430117   0
10  11542510 11542510 11544037    2 1.000000 2.385797   0
11  11665484 11665484 11669808    2 1.000000 3.386881   1
12  11709065 11709065 11711990    2 1.000000 2.646353   0
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14  11912329 11912329 11913854    2 1.000000 2.421583   0
15  12220021 12220021 12235876    6 1.000000 2.789883   1
16  12880811 12880811 12883825    2 1.000000 2.595128   0
17  12939767 12939767 12940889    2 1.000000 3.412343   1
18  13561270 13561270 13562026    2 0.666667 2.477569   0
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84   2516175  2516175  2522449    2 1.000000 2.740522   0
85   2706785  2706785  2710378    2 1.000000 2.082018   0
86   3000642  3000642  3003573    2 1.000000 2.111565   0
87   5527054  5527054  5529300    2 1.000000 2.593077   0
88   5679909  5679909  5685229    2 1.000000 2.508884   0
89   6942721  6942721  6945090    2 1.000000 3.406480   1
90   7188293  7188293  7197120    4 1.000000 3.399472   1
91   7297376  7297376  7301332    2 1.000000 3.291705   0
92   7917063  7917063  7919112    4 1.000000 3.899381   2
93   8918702  8918702  8924856    2 1.000000 2.972756   1
94   9178870  9178870  9185523    2 1.000000 3.859310   1
95  10128217 10128217 10131938    2 1.000000 4.070214   1
96  10527086 10527086 10531537    2 1.000000 5.203891   1
97  11505106 11505106 11506201    2 1.000000 2.483674   0
98  11568526 11568526 11570685    2 1.000000 3.458098   1
99  12984496 12984496 12990166    4 1.000000 2.417765   1
100 13558305 13558305 13563906    2 1.000000 3.782678   1
101 13572303 13572303 13574149    2 1.000000 2.116714   0
102 13579253 13579253 13582533    2 1.000000 3.624439   1
103 13657219 13657219 13660560    2 1.000000 2.195697   0
104 13806048 13806048 13806819    2 0.666667 2.236574   0
105 13818904 13818904 13822578    4 1.000000 2.748828   1
106 15395182 15395182 15397194    2 1.000000 1.973439   0
107 15614380 15614380 15617347    2 1.000000 2.291337   0
108 15906590 15906590 15913223    2 1.000000 2.184958   0
109 16220003 16220003 16222022    2 1.000000 2.789092   0
110 16548618 16548618 16550341    2 1.000000 2.760284   0
111 17134958 17134958 17140882    2 1.000000 2.179813   0
112 17707053 17707053 17710461    2 1.000000 3.179018   1
113 18338912 18338912 18339451    2 0.666667 3.414287   1
114 18633570 18633570 18635338    2 1.000000 2.587932   0
115 18778054 18778054 18779149    2 1.000000 2.443745   0
116 19072705 19072705 19074763    2 1.000000 2.803983   1
117 19350880 19350880 19353783    2 1.000000 2.080874   0
118 19853306 19853306 19854551    2 1.000000 3.475491   0
119 20756421 20756421 20763276    2 1.000000 2.893863   0
120 20825124 20825124 20829293    2 1.000000 2.572956   0
121 20890872 20890872 20893565    2 1.000000 2.185075   0
122 21307661 21307661 21308432    2 0.666667 2.625575   0
123 24461211 24461211 24464611    2 1.000000 2.570874   0
124   354408   354408   355671    2 1.000000 2.538597   0
125   400748   400748   402543    2 1.000000 3.852650   1
126  2154417  2154417  2156035    2 1.000000 2.674355   0
127  4760236  4760236  4764974    2 1.000000 3.411718   0
128  5961406  5961406  5964019    2 1.000000 3.552700   0
129  6795458  6795458  6799077    2 1.000000 2.586178   0
130  7681698  7681698  7684799    2 1.000000 1.908582   0
131  7773127  7773127  7779132    2 1.000000 2.814729   1
132  8077104  8077104  8079709    2 1.000000 2.362005   0
133  9103791  9103791  9114915    4 1.000000 3.425095   2
134  9298126  9298126  9302089    2 1.000000 2.597564   0
135 11060158 11060158 11062255    2 1.000000 2.344862   0
136 11522641 11522641 11528664    2 1.000000 2.132849   0
137 11914656 11914656 11919704    2 1.000000 2.072554   0
138 12920583 12920583 12921722    2 1.000000 3.093956   1
139 13244365 13244365 13246011    2 1.000000 2.207244   0
140 14369206 14369206 14374354    2 1.000000 4.097203   1
141 14548301 14548301 14552162    2 1.000000 2.675625   1
142 14833591 14833591 14839422    2 1.000000 2.555354   0
143 14910003 14910003 14912238    2 1.000000 2.267010   0
144 16162152 16162152 16163859    2 1.000000 2.348634   0
145 18111166 18111166 18113650    2 1.000000 2.855313   0
146 19567680 19567680 19569336    2 1.000000 3.930182   1
147 19725305 19725305 19729424    2 1.000000 2.409642   0
148 20049840 20049840 20051703    2 1.000000 1.950138   0
149 20702011 20702011 20704625    2 1.000000 2.147797   0
150 20884518 20884518 20886518    2 1.000000 3.850692   0
151 21325262 21325262 21327764    2 1.000000 3.108183   1
152 22108536 22108536 22113002    2 1.000000 1.858623   0
153 22499444 22499444 22502165    2 1.000000 2.887703   0
154 22668895 22668895 22671860    2 1.000000 3.290937   1
155 22881939 22881939 22883324    2 1.000000 4.197359   2
156 25514416 25514416 25520874    2 1.000000 2.401385   0
157 26206083 26206083 26207451    2 1.000000 2.434338   0
158 26769057 26769057 26773652    2 1.000000 3.874332   1
159 29424881 29424881 29429377    2 1.000000 4.669522   1
160 30330073 30330073 30332637    2 1.000000 3.859716   1
161 31362930 31362930 31366830    2 1.000000 2.747392   0
162  1052873  1052873  1056003    2 1.000000 2.348849   0
163  2753010  2753010  2755515    2 1.000000 2.095685   0
164  3028713  3028713  3031775    2 1.000000 2.651458   0
165  3738834  3738834  3746119    2 1.000000 3.330065   0
166  4563122  4563122  4563581    2 0.500000 5.358607   1
167  5552647  5552647  5554781    2 1.000000 4.170457   1
168  8410642  8410642  8415419    2 1.000000 3.228957   1
169  9010180  9010180  9014940    2 1.000000 2.774389   0
170 10451569 10451569 10452327    2 1.000000 1.747707   0
171 10729525 10729525 10733527    2 1.000000 3.864927   1
172 11377287 11377287 11380880    2 1.000000 2.156524   0
173 12125340 12125340 12129002    2 1.000000 2.161552   0
174 12166881 12166881 12171472    2 1.000000 2.499250   0
175 12933533 12933533 12935886    2 1.000000 2.889027   1
176 13464716 13464716 13465414    2 1.000000 3.147358   1
177 14532600 14532600 14535457    2 1.000000 2.082354   0
178 16993240 16993240 16997239    2 1.000000 2.999182   0
179 18711904 18711904 18714372    2 1.000000 2.395878   0
180 19359513 19359513 19365236    2 1.000000 3.116972   1
181 20063517 20063517 20066886    2 1.000000 3.090098   0
182 20882685 20882685 20887261    2 1.000000 2.235150   0
183 20957782 20957782 20960282    2 1.000000 2.313234   0
184 21463463 21463463 21464437    2 1.000000 2.742642   0
185 21650892 21650892 21651768    2 1.000000 2.802878   0
186    19187    19187    22227    2 1.000000 2.588925   0

sessionInfo()
R Under development (unstable) (2024-01-17 r85813)
Platform: x86_64-apple-darwin20
Running under: macOS Sonoma 14.1.1

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: Australia/Melbourne
tzcode source: internal

attached base packages:
[1] stats4    stats     graphics  grDevices datasets  utils     methods  
[8] base     

other attached packages:
 [1] edgeR_4.2.1                           limma_3.60.4                         
 [3] BSgenome.Dmelanogaster.UCSC.dm6_1.4.1 BSgenome_1.72.0                      
 [5] rtracklayer_1.64.0                    BiocIO_1.14.0                        
 [7] Biostrings_2.72.1                     XVector_0.44.0                       
 [9] ggplot2_3.5.1                         dplyr_1.1.4                          
[11] plyranges_1.24.0                      GenomicRanges_1.56.1                 
[13] GenomeInfoDb_1.40.1                   IRanges_2.38.1                       
[15] S4Vectors_0.42.1                      BiocGenerics_0.50.0                  
[17] Damsel_1.0.0                          workflowr_1.7.1                      

loaded via a namespace (and not attached):
 [1] tidyselect_1.2.1            bitops_1.0-8               
 [3] fastmap_1.2.0               RCurl_1.98-1.16            
 [5] GenomicAlignments_1.40.0    promises_1.3.0             
 [7] XML_3.99-0.17               digest_0.6.35              
 [9] lifecycle_1.0.4             statmod_1.5.0              
[11] processx_3.8.4              magrittr_2.0.3.9000        
[13] compiler_4.4.0              rlang_1.1.3                
[15] sass_0.4.9                  tools_4.4.0                
[17] utf8_1.2.4                  yaml_2.3.8                 
[19] knitr_1.46                  S4Arrays_1.4.1             
[21] curl_5.2.1                  DelayedArray_0.30.1        
[23] abind_1.4-5                 BiocParallel_1.38.0        
[25] withr_3.0.1                 grid_4.4.0                 
[27] fansi_1.0.6                 git2r_0.33.0               
[29] colorspace_2.1-1            scales_1.3.0               
[31] SummarizedExperiment_1.34.0 cli_3.6.2                  
[33] rmarkdown_2.27              crayon_1.5.3               
[35] generics_0.1.3              rstudioapi_0.16.0          
[37] httr_1.4.7                  rjson_0.2.21               
[39] cachem_1.1.0                stringr_1.5.1.9000         
[41] splines_4.4.0               zlibbioc_1.50.0            
[43] parallel_4.4.0              BiocManager_1.30.23        
[45] restfulr_0.0.15             matrixStats_1.3.0          
[47] vctrs_0.6.5                 Matrix_1.7-0               
[49] jsonlite_1.8.8              callr_3.7.6                
[51] locfit_1.5-9.10             jquerylib_0.1.4            
[53] glue_1.7.0                  codetools_0.2-20           
[55] ps_1.7.6                    stringi_1.8.4              
[57] gtable_0.3.5                later_1.3.2                
[59] UCSC.utils_1.0.0            munsell_0.5.1              
[61] tibble_3.2.1                pillar_1.9.0               
[63] htmltools_0.5.8.1           GenomeInfoDbData_1.2.12    
[65] R6_2.5.1                    rprojroot_2.0.4            
[67] evaluate_0.23               Biobase_2.64.0             
[69] lattice_0.22-6              highr_0.10                 
[71] Rsamtools_2.20.0            renv_1.0.7                 
[73] httpuv_1.6.15               bslib_0.7.0                
[75] Rcpp_1.0.12                 SparseArray_1.4.8          
[77] whisker_0.4.1               xfun_0.44                  
[79] fs_1.6.4                    MatrixGenerics_1.16.0      
[81] getPass_0.2-4               pkgconfig_2.0.3