nanotubes 1.2.0
Install the most recent stable version from Bioconductor:
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install("nanotubes")And load nanotubes:
library(nanotubes)Alternatively, you can install the development version directly from GitHub using devtools:
devtools::install_github("MalteThodberg/nanotubes")If you use nanotubes, please cite the following article:
citation("nanotubes")##
## Bornholdt et al. Identification of Gene Transcription Start Sites
## and Enhancers Responding to Pulmonary Carbon Nanotube Exposure in
## Vivo, ACS Nano (2017)
##
## A BibTeX entry for LaTeX users is
##
## @Article{,
## title = {Identification of Gene Transcription Start Sites and Enhancers Responding to Pulmonary Carbon Nanotube Exposure in Vivo},
## author = {Jette Bornholdt and Anne Thoustrup Saber and Berit Lilje and Mette Boyd and Mette Jørgensen and Yun Chen and Morana Vitezic and Nicklas Raun Jacobsen and Sarah Søs Poulsen and Trine Berthing and Simon Bressendorff and Kristoffer Vitting-Seerup and Robin Andersson and Karin Sørig Hougaard and Carole L. Yauk and Sabina Halappanavar and Håkan Wallin and Ulla Vogel and Albin Sandelin},
## year = {2017},
## journal = {ACS Nano},
## doi = {10.1021/acsnano.6b07533},
## volume = {11},
## number = {4},
## pages = {3597-3613},
## }For general questions about the usage of nanotubes, use the official Bioconductor support forum and tag your question “nanotubes”. We strive to answer questions as quickly as possible.
For technical questions, bug reports and suggestions for new features, we refer to the nanotubes github page
CAGE Transcription Start Sites (CTSSs), the number of CAGE tag 5’-end mapping to each genomic location data was obtained from the authors of the original study. Remaining data used in the study can be downloaded from GSE70386.
One technical replicate was not included.
Load the data into R to get an overview of the included samples:
data("nanotubes")
knitr::kable(nanotubes)| Class | Name | BigWigPlus | BigWigMinus | |
|---|---|---|---|---|
| C547 | Ctrl | C547 | mm9.CAGE_7J7P_NANO_KON_547.plus.bw | mm9.CAGE_7J7P_NANO_KON_547.minus.bw |
| C548 | Ctrl | C548 | mm9.CAGE_ULAC_NANO_KON_548.plus.bw | mm9.CAGE_ULAC_NANO_KON_548.minus.bw |
| C549 | Ctrl | C549 | mm9.CAGE_YM4F_Nano_KON_549.plus.bw | mm9.CAGE_YM4F_Nano_KON_549.minus.bw |
| C559 | Ctrl | C559 | mm9.CAGE_RSAM_NANO_559.plus.bw | mm9.CAGE_RSAM_NANO_559.minus.bw |
| C560 | Ctrl | C560 | mm9.CAGE_CCLF_NANO_560.plus.bw | mm9.CAGE_CCLF_NANO_560.minus.bw |
| N13 | Nano | N13 | mm9.CAGE_KTRA_Nano_13.plus.bw | mm9.CAGE_KTRA_Nano_13.minus.bw |
| N14 | Nano | N14 | mm9.CAGE_RSAM_NANO_14.plus.bw | mm9.CAGE_RSAM_NANO_14.minus.bw |
| N15 | Nano | N15 | mm9.CAGE_RFQS_Nano_15.plus.bw | mm9.CAGE_RFQS_Nano_15.minus.bw |
| N16 | Nano | N16 | mm9.CAGE_CCLF_NANO_16.plus.bw | mm9.CAGE_CCLF_NANO_16.minus.bw |
| N17 | Nano | N17 | mm9.CAGE_RSAM_NANO_17.plus.bw | mm9.CAGE_RSAM_NANO_17.minus.bw |
| N18 | Nano | N18 | mm9.CAGE_CCLF_NANO_18.plus.bw | mm9.CAGE_CCLF_NANO_18.minus.bw |
Load a data from a BigWig-file into R using the rtracklayer package:
library(rtracklayer)
bw_fname <- system.file("extdata", nanotubes$BigWigPlus[1],
package = "nanotubes",
mustWork = TRUE)
import(bw_fname)## GRanges object with 1055261 ranges and 1 metadata column:
## seqnames ranges strand | score
## <Rle> <IRanges> <Rle> | <numeric>
## [1] chr1 3297935 * | 1
## [2] chr1 3405982 * | 1
## [3] chr1 3575580 * | 1
## [4] chr1 3612051 * | 1
## [5] chr1 3638567 * | 2
## ... ... ... ... . ...
## [1055257] chrY_random 52340197 * | 1
## [1055258] chrY_random 55206004 * | 1
## [1055259] chrY_random 55312786 * | 1
## [1055260] chrY_random 56729517 * | 1
## [1055261] chrY_random 56966442 * | 1
## -------
## seqinfo: 29 sequences from an unspecified genomeThe data contained in the package is correctly formatted for analysis with the CAGEfightR package:
library(CAGEfightR)
# Setup paths
bw_plus <- system.file("extdata", nanotubes$BigWigPlus,
package = "nanotubes",
mustWork = TRUE)
bw_minus <- system.file("extdata", nanotubes$BigWigMinus,
package = "nanotubes",
mustWork = TRUE)
# Save as named BigWigFileList
bw_plus <- BigWigFileList(bw_plus)
bw_minus <- BigWigFileList(bw_minus)
names(bw_plus) <- names(bw_minus) <- nanotubes$Name
# Quantify
CTSSs <- quantifyCTSSs(bw_plus, bw_minus, design=nanotubes)See the CAGEfightR vignette for more details.
sessionInfo()## R version 3.6.1 (2019-07-05)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 18.04.3 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.10-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.10-bioc/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=C
## [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 stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] rtracklayer_1.46.0 GenomicRanges_1.38.0 GenomeInfoDb_1.22.0
## [4] IRanges_2.20.0 S4Vectors_0.24.0 BiocGenerics_0.32.0
## [7] nanotubes_1.2.0 BiocStyle_2.14.0
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.2 compiler_3.6.1
## [3] BiocManager_1.30.9 highr_0.8
## [5] XVector_0.26.0 bitops_1.0-6
## [7] tools_3.6.1 zlibbioc_1.32.0
## [9] digest_0.6.22 lattice_0.20-38
## [11] evaluate_0.14 rlang_0.4.1
## [13] Matrix_1.2-17 DelayedArray_0.12.0
## [15] yaml_2.2.0 xfun_0.10
## [17] GenomeInfoDbData_1.2.2 stringr_1.4.0
## [19] knitr_1.25 Biostrings_2.54.0
## [21] grid_3.6.1 Biobase_2.46.0
## [23] XML_3.98-1.20 BiocParallel_1.20.0
## [25] rmarkdown_1.16 bookdown_0.14
## [27] magrittr_1.5 matrixStats_0.55.0
## [29] Rsamtools_2.2.0 htmltools_0.4.0
## [31] GenomicAlignments_1.22.0 SummarizedExperiment_1.16.0
## [33] stringi_1.4.3 RCurl_1.95-4.12