text: user3332: I'm using RepeatMasker to detect, classify the Transposable elements. My Input is a eukaryotic non-reference genome.
  I made a run via RepeatMasker many times to Mask the TEs, but return 0 Annotation tables.
  Further, I used a different -species option each time, but Annotation results contain only short and simple repeats.
  Do I have to create a unique library to detect them?
  The command I used:
  ./RepeatMasker -no_is -noint - species mammal Genome.fna
  
  Results:
  sequences:         32573
  total length: 2004063690 bp  (1981588036 bp excl N/X-runs)
  GC level:         41.28 %
  bases masked:   33282890 bp ( 1.66 %)
  ==================================================
                 number of      length   percentage
                 elements*    occupied  of sequence
  --------------------------------------------------
  SINEs:                0            0 bp    0.00 %
        ALUs            0            0 bp    0.00 %
        MIRs            0            0 bp    0.00 %
  
  LINEs:                0            0 bp    0.00 %
        LINE1           0            0 bp    0.00 %
        LINE2           0            0 bp    0.00 %
        L3/CR1          0            0 bp    0.00 %
  
  LTR elements:         0            0 bp    0.00 %
        ERVL            0            0 bp    0.00 %
        ERVL-MaLRs      0            0 bp    0.00 %
        ERV_classI      0            0 bp    0.00 %
        ERV_classII     0            0 bp    0.00 %
  
  DNA elements:         0            0 bp    0.00 %
       hAT-Charlie      0            0 bp    0.00 %
       TcMar-Tigger     0            0 bp    0.00 %
  
  Unclassified:         0            0 bp    0.00 %
  
  Total interspersed repeats:        0 bp    0.00 %
  
  
  Small RNA:            0            0 bp    0.00 %
  
  Satellites:           1          267 bp    0.00 %
  Simple repeats:  663679     27953718 bp    1.39 %
  Low complexity:  123705      6154714 bp    0.31 %
  ==================================================
  
  
  user4187: That's one answer ^, not sure if you NEED to do that, which wouldn't actually classify your elements as LTRs, it would just find repetitive sequences in your new genome (as you discovered).
  To get them classified one standard approach is to use evidence of homology to sequences of LTR elements with classifications already, and you can get those in Repbase. If you want to download Repbase, you have to sign up for an account with GIRI but I think they give to anyone who asks. Then you can download the section of Repbase you're interested in (e.g. the whole thing, LTR, DNA-TE, ...) and provide the path to the downloaded library (in FASTA format I think) using -lib, like
  RepeatMasker -lib Repbase_LTR.fa genome.fa
  Then your RepeatMasker output table should have info about other kinds of TEs.
  If you want to check out my approach to classification by homology you might find some ideas you'd like to try. I used Dfam+nhmmer and Repbase+tblastx to identify evidence for LTR retrotransposon classification.
  My software pipeline is available as open-source software. If you want detailed high-quality annotations of LTR retrotransponsons, PhyLTR will automatically annotate putative protein-coding sequence regions, classify them, and remove false-positives like a tandem array of DNA TEs which look like LTR-Rs (good diagram of LTR-R false positives here: https://github.com/oushujun/LTR_retriever/blob/master/Manual.pdf)
  Phylogenetic Analysis of LTR retrotransposons
  https://github.com/mcsimenc/PhyLTR
  
  user383: You need to model the repeats in your de novo genome.
  See:
  http://www.repeatmasker.org/RepeatModeler/ and
  https://www.biostars.org/p/154290/ (from previous answer)
  You first build a database named "name_of_your_database" (insert whatever you want to call it) and run it on the fasta file of your genome (e.g. your_genome.fasta).
  Make you find the right paths for the software.
  ## build the database
  BuildDatabase -engine ncbi -name name_of_your_database your_genome.fasta
  
  ## run the modeler (in this case using ncbi)
  RepeatModeler -database name_of_your_database -engine ncbi
  
  
original_text: 3332: <p>I'm using RepeatMasker to detect, classify the Transposable elements. My Input is a eukaryotic non-reference genome.
  I made a run via RepeatMasker many times to Mask the TEs, but return 0 Annotation tables.
  Further, I used a different <code>-species</code> option each time, but Annotation results contain only short and simple repeats.</p>
  
  <p>Do I have to create a unique library to detect them?</p>
  
  <p>The command I used:</p>
  
  <pre><code>./RepeatMasker -no_is -noint - species mammal Genome.fna
  </code></pre>
  
  <p>Results:</p>
  
  <pre><code>sequences:         32573
  total length: 2004063690 bp  (1981588036 bp excl N/X-runs)
  GC level:         41.28 %
  bases masked:   33282890 bp ( 1.66 %)
  ==================================================
                 number of      length   percentage
                 elements*    occupied  of sequence
  --------------------------------------------------
  SINEs:                0            0 bp    0.00 %
        ALUs            0            0 bp    0.00 %
        MIRs            0            0 bp    0.00 %
  
  LINEs:                0            0 bp    0.00 %
        LINE1           0            0 bp    0.00 %
        LINE2           0            0 bp    0.00 %
        L3/CR1          0            0 bp    0.00 %
  
  LTR elements:         0            0 bp    0.00 %
        ERVL            0            0 bp    0.00 %
        ERVL-MaLRs      0            0 bp    0.00 %
        ERV_classI      0            0 bp    0.00 %
        ERV_classII     0            0 bp    0.00 %
  
  DNA elements:         0            0 bp    0.00 %
       hAT-Charlie      0            0 bp    0.00 %
       TcMar-Tigger     0            0 bp    0.00 %
  
  Unclassified:         0            0 bp    0.00 %
  
  Total interspersed repeats:        0 bp    0.00 %
  
  
  Small RNA:            0            0 bp    0.00 %
  
  Satellites:           1          267 bp    0.00 %
  Simple repeats:  663679     27953718 bp    1.39 %
  Low complexity:  123705      6154714 bp    0.31 %
  ==================================================
  </code></pre>
   4187: <p>That's one answer ^, not sure if you NEED to do that, which wouldn't actually classify your elements as LTRs, it would just find repetitive sequences in your new genome (as you discovered).</p>
  
  <p>To get them classified one standard approach is to use evidence of homology to sequences of LTR elements with classifications already, and you can get those in Repbase. If you want to download Repbase, you have to sign up for an account with GIRI but I think they give to anyone who asks. Then you can download the section of Repbase you're interested in (e.g. the whole thing, LTR, DNA-TE, ...) and provide the path to the downloaded library (in FASTA format I think) using <code>-lib</code>, like</p>
  
  <p><code>RepeatMasker -lib Repbase_LTR.fa genome.fa</code></p>
  
  <p>Then your RepeatMasker output table should have info about other kinds of TEs.</p>
  
  <p>If you want to check out my approach to classification by homology you might find some ideas you'd like to try. I used Dfam+nhmmer and Repbase+tblastx to identify evidence for LTR retrotransposon classification.</p>
  
  <p>My software pipeline is available as open-source software. If you want detailed high-quality annotations of LTR retrotransponsons, PhyLTR will automatically annotate putative protein-coding sequence regions, classify them, and remove false-positives like a tandem array of DNA TEs which look like LTR-Rs (good diagram of LTR-R false positives here: <a href="https://github.com/oushujun/LTR_retriever/blob/master/Manual.pdf" rel="nofollow noreferrer">https://github.com/oushujun/LTR_retriever/blob/master/Manual.pdf</a>)</p>
  
  <p>Phylogenetic Analysis of LTR retrotransposons
  <a href="https://github.com/mcsimenc/PhyLTR" rel="nofollow noreferrer">https://github.com/mcsimenc/PhyLTR</a></p>
   383: <p>You need to model the repeats in your de novo genome.</p>
  
  <p><em>See:
  <a href="http://www.repeatmasker.org/RepeatModeler/" rel="nofollow noreferrer">http://www.repeatmasker.org/RepeatModeler/</a> and
  <a href="https://www.biostars.org/p/154290/" rel="nofollow noreferrer">https://www.biostars.org/p/154290/</a> (from previous answer)</em></p>
  
  <p>You first build a database named "name_of_your_database" (insert whatever you want to call it) and run it on the fasta file of your genome (e.g. your_genome.fasta).</p>
  
  <p>Make you find the right paths for the software.</p>
  
  <pre><code>## build the database
  BuildDatabase -engine ncbi -name name_of_your_database your_genome.fasta
  
  ## run the modeler (in this case using ncbi)
  RepeatModeler -database name_of_your_database -engine ncbi
  </code></pre>
  