Compare_MGI_Illumina
Last updated: 2022-03-10
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Knit directory: rare-mutation-detection/
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| Rmd | b257d52 | Marek Cmero | 2022-03-10 | Added MGI vs. Illumina comparison; refactoring ecoli.Rmd code |
Compare MGI vs. Illumina
Compare duplex statistics for two libraries, one MGI and one Illumina, containing the same samples.
library(ggplot2)
library(data.table)
library(dplyr)
library(here)
library(tibble)
library(stringr)
library(Rsamtools)
library(GenomicRanges)
library(seqinr)source(here('code/load_data.R'))
source(here('code/efficiency_nanoseq_functions.R'))# Ecoli genome max size
genome_max <- 4528118# directory paths
genomeFile <- here('data/ref/Ecoli_strain_BL21_genome.fasta')
ill_rinfo_dir <- here('data/ecoli/jafarJ_201021/QC/read_info')
ill_markdup_dir <- here('data/ecoli/jafarJ_201021/QC/mark_duplicates')
mgi_rinfo_dir <- here('data/ecoli/jafarJ_150222/QC/read_info')
mgi_markdup_dir <- here('data/ecoli/jafarJ_150222/QC/mark_duplicates')
# load and transform read barcode data
ill_rbs <- load_rbs_data(ill_rinfo_dir)
ill_sample_names <- list.files(ill_rinfo_dir) %>%
str_split('\\.txt.gz') %>%
lapply(., dplyr::first) %>%
unlist() %>%
str_split('_') %>%
lapply(., dplyr::first) %>%
unlist()
names(ill_rbs) <- ill_sample_names
mgi_rbs <- load_rbs_data(mgi_rinfo_dir)
mgi_sample_names <- list.files(mgi_rinfo_dir) %>%
str_split('\\.txt.gz') %>%
lapply(., dplyr::first) %>% unlist()
names(mgi_rbs) <- mgi_sample_names
# load and fetch duplicate rate from MarkDuplicates output
ill_mdup <- load_markdup_data(ill_markdup_dir, ill_sample_names)
mgi_mdup <- load_markdup_data(mgi_markdup_dir, mgi_sample_names)# Nan metrics
rlen <- 151; skips <- 5
ill_metrics <- calculate_metrics(head(ill_rbs, 4))
mgi_metrics <- calculate_metrics(head(mgi_rbs, 3))
# Nuxg metrics
rlen <- 151; skips <- 8
ill_metrics <- rbind(ill_metrics,
calculate_metrics(tail(ill_rbs, 4)))
mgi_metrics <- rbind(mgi_metrics,
calculate_metrics(tail(mgi_rbs, 4)))
ill_metrics$duplicate_rate <- as.numeric(ill_mdup)
mgi_metrics$duplicate_rate <- as.numeric(mgi_mdup)Metric comparison plots
mm <- rbind(data.frame(melt(ill_metrics), platform = "Illumina"),
data.frame(melt(mgi_metrics), platform = "MGI"))
metrics <- as.character(mm$variable) %>% unique()
for(metric in metrics) {
p <- ggplot(mm[mm$variable == metric,], aes(sample, value, fill=platform)) +
geom_histogram(stat = 'identity', position = 'dodge') +
theme_bw() +
coord_flip() +
scale_fill_brewer(palette = 'Accent') +
ggtitle(metric)
show(p)
}
sessionInfo()R version 4.0.5 (2021-03-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
Matrix products: default
BLAS: /stornext/System/data/apps/R/R-4.0.5/lib64/R/lib/libRblas.so
LAPACK: /stornext/System/data/apps/R/R-4.0.5/lib64/R/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats4 parallel stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] seqinr_4.2-8 Rsamtools_2.6.0 Biostrings_2.58.0
[4] XVector_0.30.0 GenomicRanges_1.42.0 GenomeInfoDb_1.26.7
[7] IRanges_2.24.1 S4Vectors_0.28.1 BiocGenerics_0.36.1
[10] stringr_1.4.0 tibble_3.1.5 here_1.0.1
[13] dplyr_1.0.7 data.table_1.14.0 ggplot2_3.3.5
[16] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] Rcpp_1.0.7 assertthat_0.2.1 rprojroot_2.0.2
[4] digest_0.6.27 utf8_1.2.2 plyr_1.8.6
[7] R6_2.5.1 evaluate_0.14 highr_0.9
[10] pillar_1.6.4 zlibbioc_1.36.0 rlang_0.4.12
[13] whisker_0.4 jquerylib_0.1.4 R.oo_1.24.0
[16] R.utils_2.11.0 rmarkdown_2.11 labeling_0.4.2
[19] BiocParallel_1.24.1 RCurl_1.98-1.3 munsell_0.5.0
[22] compiler_4.0.5 httpuv_1.6.3 xfun_0.22
[25] pkgconfig_2.0.3 htmltools_0.5.2 tidyselect_1.1.1
[28] GenomeInfoDbData_1.2.4 fansi_0.5.0 crayon_1.4.2
[31] withr_2.4.2 later_1.3.0 R.methodsS3_1.8.1
[34] MASS_7.3-53.1 bitops_1.0-7 grid_4.0.5
[37] jsonlite_1.7.2 gtable_0.3.0 lifecycle_1.0.1
[40] DBI_1.1.1 git2r_0.28.0 magrittr_2.0.1
[43] scales_1.1.1 stringi_1.7.5 farver_2.1.0
[46] reshape2_1.4.4 fs_1.5.0 promises_1.2.0.1
[49] bslib_0.3.0 ellipsis_0.3.2 generics_0.1.1
[52] vctrs_0.3.8 RColorBrewer_1.1-2 tools_4.0.5
[55] ade4_1.7-18 glue_1.4.2 purrr_0.3.4
[58] fastmap_1.1.0 yaml_2.2.1 colorspace_2.0-0
[61] knitr_1.33 sass_0.4.0