Last updated: 2020-04-28

Checks: 2 0

Knit directory: BgeeCall_practical/

This reproducible R Markdown analysis was created with workflowr (version 1.6.1). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.


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.

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

The results in this page were generated with repository version ffd74c0. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use 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:    .Rhistory
    Ignored:    .Rproj.user/

Untracked files:
    Untracked:  PCA_dim_1vs2.png
    Untracked:  PCA_prop_explained_variance.png
    Untracked:  analyis.R
    Untracked:  dif_expressed_genes.tsv
    Untracked:  inputFile.tsv
    Untracked:  input_files/
    Untracked:  merge.R
    Untracked:  output_files/
    Untracked:  release.tsv

Unstaged changes:
    Modified:   analysis/_site.yml

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.


These are the previous versions of the repository in which changes were made to the R Markdown (analysis/classes_description.Rmd) and HTML (docs/classes_description.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File Version Author Date Message
html a753e15 Julien 2020-04-28 Build site.
html dc40200 Julien 2020-04-28 Build site.
html f01becc Julien 2020-04-25 Build site.
Rmd 625ed05 Julien 2020-04-24 wflow_publish(files = c(“analysis/analysis.Rmd”, “analysis/classes_description.Rmd”,
html 3f5d76c Julien 2020-04-24 Build site.
html 64f7db8 Julien 2020-04-24 Build site.
Rmd 590e07d Julien 2020-04-24 wflow_publish(files = c(“analysis/analysis.Rmd”, “analysis/classes_description.Rmd”,
html 2c7601e Julien 2020-04-24 Build site.
Rmd 6da0a8d Julien 2020-04-24 wflow_publish(files = c(“analysis/analysis.Rmd”, “analysis/classes_description.Rmd”,
html 15196bf Julien 2020-04-22 Build site.
html b5a9d73 Julien 2020-04-22 Build site.
Rmd 0779975 Julien 2020-04-22 wrote general part
html 0779975 Julien 2020-04-22 wrote general part
html d93bad7 Julien 2020-04-22 update all html files
Rmd 454071e Julien 2020-04-22 create backbone of the website
html 454071e Julien 2020-04-22 create backbone of the website

Introduction

Present/absent gene expression calls can be generated using objects of 3 R classes specific to the BgeeCall package. These classes contain an important number of slots (attributes) in order to tune as much as possible how present/absent expression calls are generated. In this section we will describe these classes and their most important slots. slots written in bold type will be used during the exercices.

KallistoMetadata

This class allows to tune how kallisto will be run and how present/absent calls are generated.
Most important slots are :

  • download_kallisto : A logical allowing to use an already installed version of kallisto or to download a version that will be used only by BgeeCall. Default value is FALSE
  • single_end_parameters : kallisto parameters used to run a single end mapping. Default value is “-t 1 –single -l 180 -s 30 –bias”
  • pair_end_parameters : kallisto parameters used to run a pair end mapping. Default value is “-t 1 –bias”
  • ignoreTxVersion : logical used to remove transcript version in transcript ID. Default is FALSE. Useful if transcript version is only present in annotation or transcriptome.

BgeeMetadata

This class allows to tune which intergenic sequences to use.
Most important slot is :

  • intergenic_release : define the intergenic release that will be used. By default last official intergenic release generated by Bgee will be used.

UserMetadata

Both KallistoMetadata and BgeeMetadata could be used with default values.
The object of class UserMetadata is the only one it is necessary to modify. It contains information specific to the analysis the user wants to run.
Most important slots are :

  • species_id : The NCBI Taxon Id of the species for which the calls will be generated
  • rnaseq_lib_path : Path to the directory of the RNA-Seq library that contains fastq files
  • reads_size : size of the reads of the RNA-Seq library
  • transcriptome_object : a DNAStringSet object containing the transcriptome
  • annotation_object : a GRanges object containing the annotation
  • working_path : path to the directory where species specific intermediate files will be generated (e.g. kallisto index, transcriptome with intergenic sequences, etc.)
  • output_dir : path to the directory where files specific to the library will be generated (e.g. calls, kallisto output, etc.)

The slot transcriptome_object has to be initialized with one of the methods setTranscriptomeFromFile() or setTranscriptomeFromObject()
The slot annotation_object has to be initialized with one of the methods setAnnotationFromFile() or setAnnotationFromObject()