text: user1492: So I'm basically so new to this that I'm just trying to find out what tools, methods, and keywords I should go look up by myself.
  I have a unique strain of a bacteria.
  I was given RNAseq data for this unique strain.
  I want to analyze the RNAseq data, but I need an annotated genome to do that.
  As a resource, I do have the annotated genome of the common lab strain.
  The common strain should be pretty similar to the unique strain, but I don't know how similar.
  Can anyone tell me what tools/methods might be applicable so I can go look them up?
  
  user73: For a quick (but reliable) analysis, I'd recommend using Kallisto or Salmon to quantify isoform read counts using the transcriptome of the lab strain.
  If you have a concern about transcripts that are in your sample but not in the lab strain, you can do two Trinity assemblies: one fully de-novo, and one genome-guided. These transcripts can then be used as a reference assembly for Kallisto/Salmon, and counts compared to the lab-strain results. Note that the Trinity assemblies will only apply to the particular environments that are in your samples; if a transcript isn't expressed, it won't be in the assembly.
  Any transcripts in the de-novo assembly that are not in the genome-guided assembly are potentially novel to your strain. However, care must be taken in interpreting this: if there is any other contamination in the sample, those contaminant transcripts will also be assembled.
  I'm not too familiar with annotation pipelines, but based on a couple of Twitter posts it looks like Prokka might be a reasonable start. Torsten Seeman (lead developer of Prokka) has done a post about alternative annotation pipelines:
  http://thegenomefactory.blogspot.co.nz/2013/03/bacterial-genome-annotation-systems.html
  
original_text: 1492: <p>So I'm basically so new to this that I'm just trying to find out what tools, methods, and keywords I should go look up by myself.</p>
  
  <p>I have a unique strain of a bacteria.</p>
  
  <p>I was given RNAseq data for this unique strain.</p>
  
  <p>I want to analyze the RNAseq data, but I need an annotated genome to do that.</p>
  
  <p>As a resource, I do have the annotated genome of the common lab strain.</p>
  
  <p>The common strain should be pretty similar to the unique strain, but I don't know how similar.</p>
  
  <p>Can anyone tell me what tools/methods might be applicable so I can go look them up?</p>
   73: <p>For a quick (but reliable) analysis, I'd recommend using <a href="https://pachterlab.github.io/kallisto/download" rel="nofollow noreferrer">Kallisto</a> or <a href="https://github.com/COMBINE-lab/salmon/releases" rel="nofollow noreferrer">Salmon</a> to quantify isoform read counts using the transcriptome of the lab strain.</p>
  
  <p>If you have a concern about transcripts that are in your sample but not in the lab strain, you can do two <a href="https://github.com/trinityrnaseq/trinityrnaseq/releases" rel="nofollow noreferrer">Trinity</a> assemblies: one fully <em>de-novo</em>, and one <a href="https://github.com/trinityrnaseq/trinityrnaseq/wiki/Genome-Guided-Trinity-Transcriptome-Assembly" rel="nofollow noreferrer">genome-guided</a>. These transcripts can then be used as a reference assembly for Kallisto/Salmon, and counts compared to the lab-strain results. Note that the Trinity assemblies will only apply to the particular environments that are in your samples; if a transcript isn't expressed, it won't be in the assembly.</p>
  
  <p>Any transcripts in the <em>de-novo</em> assembly that are not in the genome-guided assembly are potentially novel to your strain. However, care must be taken in interpreting this: if there is any other contamination in the sample, those contaminant transcripts will also be assembled.</p>
  
  <p>I'm not too familiar with annotation pipelines, but based on a couple of Twitter posts it looks like <a href="http://www.vicbioinformatics.com/software.prokka.shtml" rel="nofollow noreferrer">Prokka</a> might be a reasonable start. Torsten Seeman (lead developer of Prokka) has done a post about alternative annotation pipelines:</p>
  
  <p><a href="http://thegenomefactory.blogspot.co.nz/2013/03/bacterial-genome-annotation-systems.html" rel="nofollow noreferrer">http://thegenomefactory.blogspot.co.nz/2013/03/bacterial-genome-annotation-systems.html</a></p>
  