<blockquote>
  <p>This is, for two identical samples with identical final coverage, sample A having an average insert size of 250bp and sample B having an average of 450bp, would the fraction of MAPQ=0 change between the two?</p>
</blockquote>

<p>For human, I <em>expect</em> sample B will have fewer MAPQ=0 reads (I don't have concrete data to prove). A large part of human genome consists of ALU repeats. The average size of an ALU is ~320bp. If your insert size is ~450bp, you can map reads into most of isolated ALUs in principle. With ~250bp insert, fragments in the middle of ALUs won't be mappable uniquely.</p>

<p>Note that to see the difference, you need to use a mapper that sufficiently takes the advantage of paired-end information.</p>

CC BY-SA 3.0
2018-01-11T08:18:48.207Z
Does bwamem take advantage of it?
719016
CC BY-SA 3.0
2018-01-11T02:10:33.020Z
2018-01-11T02:10:33.020Z
user172818
<p>Yes, as a general rule of thumb mappability increases with insert size (up to a limit) and read length. Whether this will actually occur in a given case will depend more on how randomly the sequencing samples from the genome to begin with (i.e., if the library prep happens to select for/against high mappability regions then the insert size won't much matter). The basic reason behind this is that if one end of a read aligns to a repetitive element that the likelihood of being able to use the other end as an anchor will increase a bit if it's further away. Now having said that, Illumina sequencers in particular like a certain fragment length for efficient sequencing, so you can't go too crazy on increasing the insert sizes and still get decent output (unless you modify your library prep).</p>

CC BY-SA 3.0
2018-01-09T10:35:17.187Z
2018-01-09T10:35:17.187Z
Devon Ryan
<p>When doing Illumina 2x150bp sequencing of genomic DNA, and after aligning the reads to GRCh38, does the percentage of the non-N fraction of the human genome as MAPQ=0 depend on the insert sizes of the genomic fragments?</p>

<p>This is, for two identical samples with identical final coverage, sample A having an average insert size of 250bp and sample B having an average of 450bp, would the fraction of MAPQ=0 change between the two?</p>

<sam><illumina><mapq>
Does the MAPQ=0 fraction of a BAM file depend on the insert sizes?
# Does the MAPQ=0 fraction of a BAM file depend on the insert sizes?

(Asked by: username_0 on 2018-01-09)

When doing Illumina 2x150bp sequencing of genomic DNA, and after aligning the reads to GRCh38, does the percentage of the non-N fraction of the human genome as MAPQ=0 depend on the insert sizes of the genomic fragments?

This is, for two identical samples with identical final coverage, sample A having an average insert size of 250bp and sample B having an average of 450bp, would the fraction of MAPQ=0 change between the two?

**Tags:** sam, illumina, mapq

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## 2 answers

### Answer by username_2 on 2018-01-09. Score: 4 | Accepted answer

Yes, as a general rule of thumb mappability increases with insert size (up to a limit) and read length. Whether this will actually occur in a given case will depend more on how randomly the sequencing samples from the genome to begin with (i.e., if the library prep happens to select for/against high mappability regions then the insert size won't much matter). The basic reason behind this is that if one end of a read aligns to a repetitive element that the likelihood of being able to use the other end as an anchor will increase a bit if it's further away. Now having said that, Illumina sequencers in particular like a certain fragment length for efficient sequencing, so you can't go too crazy on increasing the insert sizes and still get decent output (unless you modify your library prep).


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### Answer by username_1 on 2018-01-11. Score: 0

> This is, for two identical samples with identical final coverage, sample A having an average insert size of 250bp and sample B having an average of 450bp, would the fraction of MAPQ=0 change between the two?

For human, I *expect* sample B will have fewer MAPQ=0 reads (I don't have concrete data to prove). A large part of human genome consists of ALU repeats. The average size of an ALU is ~320bp. If your insert size is ~450bp, you can map reads into most of isolated ALUs in principle. With ~250bp insert, fragments in the middle of ALUs won't be mappable uniquely.

Note that to see the difference, you need to use a mapper that sufficiently takes the advantage of paired-end information.

> **Comments:**
> **username_0**: Does bwamem take advantage of it?  

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