Last updated: 2019-02-14
workflowr checks: (Click a bullet for more information) ✖ R Markdown file: uncommitted changes
The R Markdown is untracked by Git. To know which version of the R Markdown file created these results, you’ll want to first commit it to the Git repo. If you’re still working on the analysis, you can ignore this warning. When you’re finished, you can run wflow_publish
to commit the R Markdown file and build the HTML.
✔ 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(20181119)
The command set.seed(20181119)
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: fcaa341
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:
Ignored: .Rproj.user/
Untracked files:
Untracked: analysis/enrichment.Rmd
Untracked: data/SNP_200000.txt
Untracked: data/SNP_50000.txt
Untracked: data/SNP_500000.txt
Unstaged changes:
Modified: .gitignore
Modified: analysis/index.Rmd
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.
module load mysql
mysql --user=genome --host=genome-mysql.cse.ucsc.edu -A -D hg19 -e '
select
K.name2,
K.name,
S.name,
S.avHet,
S.chrom,
S.chromStart,
K.txStart,
K.txEnd
from snp150 as S
left join refGene as K on
(S.chrom=K.chrom and not(K.txEnd+50000<S.chromStart or S.chromEnd+50000<K.txStart))
where
S.name in ("rs7148456","rs12895055","rs7170068","rs520843","rs12716973","rs2192932","rs17200916","rs1198588","rs324017","rs4151680","rs301791","rs324015","rs9882911","rs11633075","rs2027349","rs186132169","rs9661794","rs7936858","rs3861678","rs10933","rs6071578")' > /project2/xinhe/simingz/CROP-seq/cropseq/data/SNP_50000.txt
SNPfile <- "/project2/xinhe/simingz/CROP-seq/scRNA_seq_SNP_list.txt"
SNPs <- read.table(SNPfile, header=F, stringsAsFactors = F)
cisgene <- read.table("data/SNP_50000.txt", stringsAsFactors = F,sep="\t", header=T)
sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.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] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] workflowr_1.1.1 Rcpp_1.0.0 digest_0.6.18
[4] rprojroot_1.3-2 R.methodsS3_1.7.1 backports_1.1.2
[7] git2r_0.23.0 magrittr_1.5 evaluate_0.12
[10] stringi_1.2.4 whisker_0.3-2 R.oo_1.22.0
[13] R.utils_2.7.0 rmarkdown_1.10 tools_3.5.1
[16] stringr_1.3.1 yaml_2.2.0 compiler_3.5.1
[19] htmltools_0.3.6 knitr_1.20
This reproducible R Markdown analysis was created with workflowr 1.1.1