text: user982: I want to perform a genome comparison on a group of isolates. I want to look into two broad groups of taxa and compare the accessory genome in each group. I have been using prokka (v1.12) and roary (v3.8.2) to do this but it appears the accessory_binary_genes.fa file is actually an untrue representation.
  Note: gene_presence_absence.Rtab does contain all the full presence/ absence for accessory gene sets. Despite this Im still unhappy with the nomenclature of the gene groups [issue for another day] 
  
  [github issue 335] Your best to ignore the accessory_binary_genes.fa file. It is just for creating a quick and dirty tree with FastTree. The file itself is filtered to remove very common and not common variation to speedup the tree generation, hence the difference in numbers.
  The top 5% and bottom 5% are excluded. It is truncated at 4000 genes.
  
  I've been looking into alternative pipelines and a new software BPGA looks promising. Does anyone have experience with this?
  I essentially want a tool which will give me the core and accessory gene sets, without the noise from partial gene hits.
  
  user446: Roary also takes into account paralogs, so sometimes two core genes are split into different groups based on their neighbour genes and they end up with different nomenclature (group_*...). As suggested by Andrew Page in the github issue I would consider the gene_presence_absence.Rtab (this contains all the orthologous genes) and remove rows corresponding to vectors only containing 1s (core genes). In this way you will have a matrix of 1 and 0 corresponding to presence/absence of a particular accessory gene in your isolates. 
  
  user1126: LS-BSR should be able to give you what you're looking for. See the article.
  After you run the primary analysis, there is a simple documented workflow for splitting the pangenome into core and accessory, based on a user defined threshold. I'm the developer, so can help if you run into any problems.
  
original_text: 982: <p>I want to perform a genome comparison on a group of isolates. I want to look into two broad groups of taxa and compare the accessory genome in each group. I have been using prokka (v1.12) and roary (v3.8.2) to do this but it appears the accessory_binary_genes.fa file is actually an untrue representation.</p>
  
  <p><strong>Note:</strong> gene_presence_absence.Rtab does contain all the full presence/ absence for accessory gene sets. Despite this Im still unhappy with the nomenclature of the gene groups [issue for another day] </p>
  
  <blockquote>
    <p><a href="https://github.com/sanger-pathogens/Roary/issues/335" rel="nofollow noreferrer">[github issue 335]</a> Your best to ignore the accessory_binary_genes.fa file. It is just for creating a quick and dirty tree with FastTree. The file itself is filtered to remove very common and not common variation to speedup the tree generation, hence the difference in numbers.</p>
    
    <p>The top 5% and bottom 5% are excluded. It is truncated at 4000 genes.</p>
  </blockquote>
  
  <p>I've been looking into alternative pipelines and a new software <a href="https://www.nature.com/articles/srep24373" rel="nofollow noreferrer">BPGA</a> looks promising. Does anyone have experience with this?</p>
  
  <p>I essentially want a tool which will give me the core and accessory gene sets, without the noise from partial gene hits.</p>
   446: <p>Roary also takes into account paralogs, so sometimes two core genes are split into different groups based on their neighbour genes and they end up with different nomenclature (group_*...). As suggested by Andrew Page in the github issue I would consider the gene_presence_absence.Rtab (this contains all the orthologous genes) and remove rows corresponding to vectors only containing 1s (core genes). In this way you will have a matrix of 1 and 0 corresponding to presence/absence of a particular accessory gene in your isolates. </p>
   1126: <p><a href="https://github.com/jasonsahl/LS-BSR" rel="nofollow noreferrer">LS-BSR</a> should be able to give you what you're looking for. See the <a href="https://peerj.com/articles/332/" rel="nofollow noreferrer">article</a>.</p>
  
  <p>After you run the primary analysis, there is a simple documented workflow for splitting the pangenome into core and accessory, based on a user defined threshold. I'm the developer, so can help if you run into any problems.</p>
  