Answers.Body: <p>5bp produces a high resolution analysis, providing its sufficiently robust.</p>
  
  <p>Its a sliding window of 5 bp wide and 1 bp step length which runs along the length of each genome. They are performing SNP analysis/classification. The original sequence they were examining was,</p>
  
  <pre><code>ATTAAAGGTTTAT
  </code></pre>
  
  <p>In any sliding window analysis the window size is arbitary towards the resolution and robustness of the analysis. The author believes that 5bp provides sufficiently robust information for a very high resolution classification/training analysis in their example. </p>
  
  <p>The proof is the <code>accuracy</code> of the classification. I assume they have good results from 5bp. In ML the rationale is the general laws of ML (over/under training) and assessed on the test split in the data (probably 20%).</p>
  
  <p>A key reason for the 1bp step is that this is the way ML works, you need a lot of data and by doing 5 bp sliding window at 1 bp step that will generate ~30 000 pieces of data for each sequence. So that's 3 million data points for 100 sequences. </p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-04-20T01:41:56.057Z
Answers.Text: Would the SNP analysis you mention include a classification algorithm such as principal component analysis?
Answers.UserDisplayName: greenpenguin
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-04-20T09:24:40.080Z
Answers.Text: Oh sorry thats different, PCA (ML) is a different analysis to the one I had in mind (supervised learning) and is usually performed in conjunction with tSNE @greenpenguin. PCA is judged on its ability to cluster the classification targets into different groups. PCA/tSNE is called unsupervised learning
Answers.UserDisplayName: M__
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-04-17T19:37:49.467Z
Answers.LastActivityDate: 2020-04-18T09:14:31.297Z
Answers.LastEditDate: 2020-04-18T09:14:31.297Z
Answers.UserDisplayName: M__
Body: <p>I'm getting started in biology and bioinformatics with sequencing the SARS-Cov-2 or Coronavirus genome.  I'm interested in this code which identifies k-mers in the genome:</p>
  
  <pre><code>from skbio import DNA 
  DNA(str(seq.seq)).kmer_frequencies(5)
  kmers = DNA(str(seq1.seq)).kmer_frequencies(5)
  kmers
  {'ATTAA': 60, 'TTAAA': 95, 'TAAAG': 64, 'AAAGG': 45, 'AAGGT': 46, 'AGGTT': 51, 'GGTTT': 55, 
  'GTTTA': 69, 'TTTAT': 75,...}
  </code></pre>
  
  <p>The author of the code wants to use k-mer breakdowns to vectorize the data for machine learning purposes.  What I'm curious about is why the k-mer in this case is five nucleotides?  What factors should go into my selection of the length of the k-mer for analysis?</p>
  
Tags: <python><sequence-analysis><covid-19><k-mer><sars-cov-2>
Title: Significance of k-mer length in COVID-19 sequence analysis?
ThreadText: # Significance of k-mer length in COVID-19 sequence analysis?
  
  (Asked by: username_0 on 2020-04-17)
  
  I'm getting started in biology and bioinformatics with sequencing the SARS-Cov-2 or Coronavirus genome. I'm interested in this code which identifies k-mers in the genome:
  
  ```
  from skbio import DNA 
  DNA(str(seq.seq)).kmer_frequencies(5)
  kmers = DNA(str(seq1.seq)).kmer_frequencies(5)
  kmers
  {'ATTAA': 60, 'TTAAA': 95, 'TAAAG': 64, 'AAAGG': 45, 'AAGGT': 46, 'AGGTT': 51, 'GGTTT': 55, 
  'GTTTA': 69, 'TTTAT': 75,...}
  
  ```
  
  The author of the code wants to use k-mer breakdowns to vectorize the data for machine learning purposes. What I'm curious about is why the k-mer in this case is five nucleotides? What factors should go into my selection of the length of the k-mer for analysis?
  
  **Tags:** python, sequence-analysis, covid-19, k-mer, sars-cov-2
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2020-04-17. Score: 0 | Accepted answer
  
  5bp produces a high resolution analysis, providing its sufficiently robust.
  
  Its a sliding window of 5 bp wide and 1 bp step length which runs along the length of each genome. They are performing SNP analysis/classification. The original sequence they were examining was,
  
  ```
  ATTAAAGGTTTAT
  
  ```
  
  In any sliding window analysis the window size is arbitary towards the resolution and robustness of the analysis. The author believes that 5bp provides sufficiently robust information for a very high resolution classification/training analysis in their example.
  
  The proof is the `accuracy` of the classification. I assume they have good results from 5bp. In ML the rationale is the general laws of ML (over/under training) and assessed on the test split in the data (probably 20%).
  
  A key reason for the 1bp step is that this is the way ML works, you need a lot of data and by doing 5 bp sliding window at 1 bp step that will generate ~30 000 pieces of data for each sequence. So that's 3 million data points for 100 sequences.
  
  > **Comments:**
  > **username_0**: Would the SNP analysis you mention include a classification algorithm such as principal component analysis?  
  > **username_1**: Oh sorry thats different, PCA (ML) is a different analysis to the one I had in mind (supervised learning) and is usually performed in conjunction with tSNE @username_0. PCA is judged on its ability to cluster the classification targets into different groups. PCA/tSNE is called unsupervised learning  
  
  ---
  
  