Last updated: 2020-04-24
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Knit directory: BgeeCall_practical/
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This page describe how to generate present/absent calls for one RNA-Seq library.
These 2 classes are useful to tune how BgeeCall works. No need to create an object of the class BgeeMetada as only default values will be used (last official Bgee intergenic release).
An object of the KallistoMetadata class has to be created to specify to download kallisto (as it is not installed on RStudio cloud).
kallisto <- new("KallistoMetadata", download_kallisto = TRUE)An object of this class has to be created and value of some slots have to be modified to run BgeeCall
user <- new("UserMetadata", species_id = "NCBI_TAXON_ID", reads_size=READS_SIZE)
user <- setRNASeqLibPath(user, "PATH_TO_RNASEQ_LIBRARY_DIR")
user <- setTranscriptomeFromFile(user, "PATH_TO_TRANSCRIPTOME")
user <- setAnnotationFromFile(user, "PATH_TO_GTF_FILE")
user <- setOutputDir(user, "PATH_TO_OUTPUT_DIR")
user <- setWorkingPath(user, "PATH_TO_WORKING_DIR")Now that all objects have been created it is possible to run the generation of present/absent gene expression calls with one unique line of code
output_files_info <- generate_calls_workflow(abundanceMetadata = kallisto, userMetadata = user)
output_files_info$calls_tsv_path
[1] "path/to/gene_level_abundance+calls.tsv"
$cutoff_info_file_path
[1] "path/to/gene_cutoff_info_file.tsv"
$abundance_tsv
[1] "abundance.tsv"
$TPM_distribution_path
[1] "path/to/gene_TPM_genic_intergenic+cutoff.pdf"
$S4_slots_summary
[1] "path/to/S4_slots_summary.tsv"This command generates a list with a link to 5 generated files.
It is possible to open text files in RStudio with the command file.edit(PATH_TO_FILE).
For example :
# open calls tsv file
file.edit(output_files_info$calls_tsv_path)
sessionInfo()R version 3.6.3 (2020-02-29)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.4 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so
locale:
[1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C
[3] LC_TIME=fr_FR.UTF-8 LC_COLLATE=en_GB.UTF-8
[5] LC_MONETARY=fr_FR.UTF-8 LC_MESSAGES=en_GB.UTF-8
[7] LC_PAPER=fr_FR.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=fr_FR.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] BgeeCall_1.2.1 workflowr_1.6.1
loaded via a namespace (and not attached):
[1] Rcpp_1.0.3 lattice_0.20-41
[3] prettyunits_1.1.1 Rsamtools_2.2.3
[5] Biostrings_2.54.0 assertthat_0.2.1
[7] rprojroot_1.3-2 digest_0.6.25
[9] BiocFileCache_1.10.2 R6_2.4.1
[11] GenomeInfoDb_1.22.0 backports_1.1.5
[13] stats4_3.6.3 RSQLite_2.2.0
[15] evaluate_0.14 httr_1.4.1
[17] pillar_1.4.3 zlibbioc_1.32.0
[19] rlang_0.4.5 GenomicFeatures_1.38.2
[21] progress_1.2.2 curl_4.3
[23] whisker_0.4 blob_1.2.1
[25] S4Vectors_0.24.3 Matrix_1.2-18
[27] rmarkdown_2.1 BiocParallel_1.20.1
[29] stringr_1.4.0 RCurl_1.98-1.1
[31] bit_1.1-15.2 biomaRt_2.42.0
[33] DelayedArray_0.12.2 compiler_3.6.3
[35] httpuv_1.5.2 rtracklayer_1.46.0
[37] xfun_0.12 pkgconfig_2.0.3
[39] askpass_1.1 BiocGenerics_0.32.0
[41] htmltools_0.4.0 tximport_1.14.0
[43] openssl_1.4.1 tidyselect_1.0.0
[45] SummarizedExperiment_1.16.1 tibble_2.1.3
[47] GenomeInfoDbData_1.2.2 matrixStats_0.55.0
[49] IRanges_2.20.2 XML_3.99-0.3
[51] crayon_1.3.4 dplyr_0.8.4
[53] dbplyr_1.4.2 later_1.0.0
[55] GenomicAlignments_1.22.1 bitops_1.0-6
[57] rappdirs_0.3.1 grid_3.6.3
[59] jsonlite_1.6.1 DBI_1.1.0
[61] git2r_0.26.1 magrittr_1.5
[63] stringi_1.4.6 XVector_0.26.0
[65] fs_1.3.2 promises_1.1.0
[67] vctrs_0.2.3 Rhdf5lib_1.8.0
[69] tools_3.6.3 bit64_0.9-7
[71] Biobase_2.46.0 glue_1.3.1
[73] purrr_0.3.3 hms_0.5.3
[75] parallel_3.6.3 yaml_2.2.1
[77] rhdf5_2.30.1 AnnotationDbi_1.48.0
[79] GenomicRanges_1.38.0 memoise_1.1.0
[81] knitr_1.28