Scripts and data related to a manuscript on translation of polyA tracks in Plasmodium species.
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README.md
riboseq_coverage.R

README.md

polyAplasmodium

Scripts and data related to a manuscript on translation of polyA tracks in Plasmodium species.

System requirements

R language version 3.5.0 or newer with installed libraries:

  • rtracklayer
  • data.table (DT)
  • biomaRt
  • genomeIntervals
  • ggplot2 and their dependencies.

Testing environment

R version 3.5.0 (2018-04-23) Platform: x86_64-apple-darwin17.5.0 (64-bit) Running under: macOS 10.14

Matrix products: default BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib LAPACK: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libLAPACK.dylib

locale: [1] C

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

other attached packages: [1] ggplot2_3.0.0 genomeIntervals_1.36.0 [3] intervals_0.15.1 biomaRt_2.36.1
[5] IRanges_2.14.10 S4Vectors_0.18.3
[7] BiocGenerics_0.26.0

loaded via a namespace (and not attached): [1] Rcpp_0.12.17 bindr_0.1.1
[3] pillar_1.2.3 plyr_1.8.4
[5] compiler_3.5.0 GenomeInfoDb_1.16.0
[7] XVector_0.20.0 prettyunits_1.0.2
[9] bitops_1.0-6 tools_3.5.0
[11] progress_1.2.0 zlibbioc_1.26.0
[13] digest_0.6.15 bit_1.1-14
[15] tibble_1.4.2 gtable_0.2.0
[17] RSQLite_2.1.1 memoise_1.1.0
[19] pkgconfig_2.0.1 rlang_0.2.1
[21] DBI_1.0.0 rstudioapi_0.7
[23] yaml_2.1.19 bindrcpp_0.2.2
[25] GenomeInfoDbData_1.1.0 withr_2.1.2
[27] dplyr_0.7.6 stringr_1.3.1
[29] httr_1.3.1 hms_0.4.2
[31] tidyselect_0.2.4 grid_3.5.0
[33] bit64_0.9-7 glue_1.2.0
[35] Biobase_2.40.0 R6_2.2.2
[37] AnnotationDbi_1.42.1 XML_3.98-1.11
[39] purrr_0.2.5 blob_1.1.1
[41] magrittr_1.5 scales_0.5.0
[43] GenomicRanges_1.32.3 assertthat_0.2.0
[45] colorspace_1.3-2 stringi_1.2.3
[47] lazyeval_0.2.1 munsell_0.5.0
[49] RCurl_1.95-4.10 crayon_1.3.4

Installation instructions

The main script for the paper is called riboseq_coverage.R and can be downloaded from Github together with accompanying data. There's no specific installation instruction. After fulfilling the library requirements, the script should run without problems provided that you set the working directory to the top level directory of this repository.

Running time and output

Preferred way of running the script is to rely on Rstudio. riboseq_coverage.R script runs till the end in less than 30 mins on a modern computer with fast drive. The script does not save any output - plots are generated in the RStudio panel view.