Last updated: 2019-02-01
workflowr checks: (Click a bullet for more information) ✔ R Markdown file: up-to-date
Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
✔ Environment: empty
Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.
✔ Seed:
set.seed(12345)
The command set.seed(12345)
was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.
✔ Session information: recorded
Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
✔ Repository version: 5b3779c
wflow_publish
or wflow_git_commit
). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
Ignored files:
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Ignored: .Rproj.user/
Ignored: .snakemake/
Ignored: data/molecules/
Ignored: data/reads/
Ignored: data/totals/
Ignored: data/verify/
Ignored: log/
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Untracked files:
Untracked: create-env.sh
Untracked: publish.bash
Untracked: snake.txt
Untracked: snakelog.out
Untracked: update-env.sh
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
File | Version | Author | Date | Message |
---|---|---|---|---|
Rmd | 5b3779c | John Blischak | 2019-02-01 | Update workflowr to 1.0.1 with wflow_update(). |
html | 5b3779c | John Blischak | 2019-02-01 | Update workflowr to 1.0.1 with wflow_update(). |
html | da1fdf3 | John Blischak | 2018-02-06 | Build site. |
html | cf9e702 | Joyce Hsiao | 2017-12-13 | Build site. |
html | 029305c | John Blischak | 2017-12-04 | Build site. |
Rmd | 6018090 | pytung | 2017-11-30 | minor edits |
html | 6898149 | John Blischak | 2017-11-29 | Build site. |
Rmd | 3d5d193 | John Blischak | 2017-11-29 | Visualize sequencing depth per C1 chip. |
library("dplyr")
library("DT")
library("ggplot2")
library("reshape2")
library("Biobase")
theme_set(cowplot::theme_cowplot())
fname <- Sys.glob("../data/eset/*.rds")
eset <- Reduce(combine, Map(readRDS, fname))
pData(eset)$experiment <- as.factor(pData(eset)$experiment)
ggplot(pData(eset), aes(x = raw, color = experiment)) +
geom_density() +
labs(x = "Number of raw sequences per single cell", y = "Number of cells",
title = "Distribution of total raw sequences per single cell") +
scale_color_discrete(name = "C1 chip")
Version | Author | Date |
---|---|---|
da1fdf3 | John Blischak | 2018-02-06 |
6898149 | John Blischak | 2017-11-29 |
Mapped reads per cell
ggplot(pData(eset), aes(x = experiment, y = mapped, color = experiment)) +
geom_violin() +
geom_boxplot(alpha = .01, width = .2, position = position_dodge(width = .9)) +
labs(x = "C1 chip", y = "Number of reads",
title = "Number of mapped sequences per single cell") +
theme(legend.title = element_blank(),
axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1))
Version | Author | Date |
---|---|---|
da1fdf3 | John Blischak | 2018-02-06 |
029305c | John Blischak | 2017-12-04 |
Sum of sequences across the 96 single cells per C1 chip.
total_per_experiment <- pData(eset) %>%
group_by(experiment) %>%
summarize(raw = sum(raw) / 10^6,
mapped = sum(mapped) / 10^6,
molecules = sum(molecules) / 10^6)
datatable(total_per_experiment,
options = list(pageLength = nrow(total_per_experiment)),
colnames = c("C1 chip", "Number of raw sequences",
"Number of mapped",
"Number of molecules"))
ggplot(melt(total_per_experiment, id.vars = "experiment",
variable.name = "type", value.name = "count"),
aes(x = experiment, y = count, color = type)) +
geom_point() +
labs(title = "Sequencing depth per C1 chip",
x = "C1 chip", y = "Number of sequences") +
theme(legend.title = element_blank(),
axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1))
sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS: /project2/gilad/jdblischak/miniconda3/envs/fucci-seq/lib/R/lib/libRblas.so
LAPACK: /project2/gilad/jdblischak/miniconda3/envs/fucci-seq/lib/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] parallel stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] bindrcpp_0.2 Biobase_2.38.0 BiocGenerics_0.24.0
[4] reshape2_1.4.2 ggplot2_2.2.1 DT_0.2
[7] dplyr_0.7.4
loaded via a namespace (and not attached):
[1] Rcpp_0.12.13 compiler_3.4.1 git2r_0.19.0
[4] plyr_1.8.4 workflowr_1.0.1 bindr_0.1
[7] R.methodsS3_1.7.1 R.utils_2.5.0 tools_3.4.1
[10] digest_0.6.12 jsonlite_1.4 evaluate_0.10.1
[13] tibble_1.3.3 gtable_0.2.0 pkgconfig_2.0.1
[16] rlang_0.1.2 yaml_2.1.14 stringr_1.2.0
[19] knitr_1.16 htmlwidgets_0.9 cowplot_0.9.1
[22] rprojroot_1.2 grid_3.4.1 glue_1.1.1
[25] R6_2.2.0 rmarkdown_1.8 magrittr_1.5
[28] whisker_0.3-2 backports_1.0.5 scales_0.5.0
[31] htmltools_0.3.6 assertthat_0.1 colorspace_1.3-2
[34] labeling_0.3 stringi_1.1.2 lazyeval_0.2.0
[37] munsell_0.4.3 R.oo_1.21.0
This reproducible R Markdown analysis was created with workflowr 1.0.1