Cattle Optical Map analyses

Script and VEP results from the Optical mapping SV analyses from Talenti et al.

Content

The following repository contains two subfolders

1. Results: this folder contains the results from some analyses (e.g. the VEP HTML report here)
2. Code: the code used to run the analyses described in the paper

Code

To successfully run the scripts here presented you will need the following dependencies:

• R with the following packages:
  • tidyverse
  • ggfortify
  • hrbrthemes
  • ggsci
  • ggpubr
  • ComplexHeatmap
  • gridExtra
  • cowplot
  • RColorBrewer
• python
• SURVIVOR
• bedtools
• bcftools
• docker

You will also need the

The Code folder contains the following subfolders:

1. RunBionanoSolve: an example of the code used to process the optical mapping using the Bionano Solve workflow
2. VEP: the code used to run the VEP
3. CountClasses: the code used to generate the histogram in Figure 1 and to extract the numbers represented
4. AssessFiltering: the code to assess multiple filtering thresholds, following the Bionano access prefiltering, and generation of the UpSet plot
5. SizeAndSupportAnalysis: the code used to assess the SV size based on the support (i.e. number of individuals that present the SVs) of the variant
6. nonRedundantDeletions: the code used to extract the filtered Deletions into bed format to compute the non-redundant reference sequence in deletions
7. GeneAnalysis: the code used to extract the coding sequences and gene features that have an overlap with an identified SV