<p>It strongly depends on exactly what your protocol is. Note that there are a good number of tools for QCing capture data (<a href="https://academic.oup.com/bioinformatics/article/30/12/1767/2748161" rel="nofollow noreferrer">here</a>, <a href="https://www.bioconductor.org/packages/devel/bioc/vignettes/TEQC/inst/doc/TEQC.pdf" rel="nofollow noreferrer">here</a>).</p>
<p>Off-target reads are a standard observation in capture experiments; recall that it is target <strong>enrichment</strong>, not target <strong>perfect purification</strong>, as commenter swbarnes2 suggests.</p>
<p>The real question is whether the proportion of those off-target reads is too high for your application, or otherwise suggests problems. Those depend on details of the technique that you will likely have to figure out yourself.</p>
<p>Here are some tables from the first of those QC papers (supplement), showing on-target proportions for various capture samples (sorry, it would have been a bit of effort to get text of the tables rather than images):</p>
<p><a href="https://i.sstatic.net/ILmxD.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/ILmxD.png" alt="enter image description here" /></a></p>
<p><a href="https://i.sstatic.net/sSqkS.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/sSqkS.png" alt="enter image description here" /></a></p>
<p>These data suggest that on-target reads are 60%-80% of mapped reads. Note that they also lose a lot of reads in mapping, so we cannot exclude the possibility of mis-mapped garbage reads contributing to off-target mapping.</p>

CC BY-SA 4.0
2020-09-23T18:49:11.243Z
2020-09-23T18:49:11.243Z
Maximilian Press
<p>Sorry if this is a stupid question I am new to analysing targeted hybrid capture data.</p>
<p>I am analysing my HTS data from a targeted hybrid capture enrichment method and subsequent sequencing on a NextSeq.</p>
<p>Looking at my bam files, I see there are reads that are overlapping into my non target regions.</p>
<p>For example - my .bed file has two target regions in chr17:</p>
<p><a href="https://i.sstatic.net/vF7BB.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/vF7BB.png" alt="enter image description here" /></a></p>
<p>However I still have reads overlapping between 7578739-7578918 (following example is position 7578850):</p>
<p><a href="https://i.sstatic.net/BMWSZ.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/BMWSZ.png" alt="enter image description here" /></a></p>
<p>Quite a lot of these reads don't hit any part of the targeted regions in my bed file. Are these mistakes? How have they been pulled down for sequencing when they aren't in the target regions of the baits?</p>

CC BY-SA 4.0
2020-09-23T18:13:18.107Z
Are you asking why your pull down experiment was not 100.00000% perfect?  You should read the literature or ask your co-workers who have done pulldowns before what % is typical for samples like yours.
swbarnes2
<sam><hts>
Targeted hybrid capture bam files showing reads outside target regions in my bed file
# Targeted hybrid capture bam files showing reads outside target regions in my bed file

(Asked by: username_0 on 2020-09-23)

Sorry if this is a stupid question I am new to analysing targeted hybrid capture data.

I am analysing my HTS data from a targeted hybrid capture enrichment method and subsequent sequencing on a NextSeq.

Looking at my bam files, I see there are reads that are overlapping into my non target regions.

For example - my .bed file has two target regions in chr17:

[![enter image description here](https://i.sstatic.net/vF7BB.png)](https://i.sstatic.net/vF7BB.png)

However I still have reads overlapping between 7578739-7578918 (following example is position 7578850):

[![enter image description here](https://i.sstatic.net/BMWSZ.png)](https://i.sstatic.net/BMWSZ.png)

Quite a lot of these reads don't hit any part of the targeted regions in my bed file. Are these mistakes? How have they been pulled down for sequencing when they aren't in the target regions of the baits?

**Tags:** sam, hts
> **Comments:**
> **username_1**: Are you asking why your pull down experiment was not 100.00000% perfect?  You should read the literature or ask your co-workers who have done pulldowns before what % is typical for samples like yours.  

---

## 1 answers

### Answer by username_2 on 2020-09-23. Score: 3 | Accepted answer

It strongly depends on exactly what your protocol is. Note that there are a good number of tools for QCing capture data ([here](https://academic.oup.com/bioinformatics/article/30/12/1767/2748161), [here](https://www.bioconductor.org/packages/devel/bioc/vignettes/TEQC/inst/doc/TEQC.pdf)).

Off-target reads are a standard observation in capture experiments; recall that it is target **enrichment**, not target **perfect purification**, as commenter swbarnes2 suggests.

The real question is whether the proportion of those off-target reads is too high for your application, or otherwise suggests problems. Those depend on details of the technique that you will likely have to figure out yourself.

Here are some tables from the first of those QC papers (supplement), showing on-target proportions for various capture samples (sorry, it would have been a bit of effort to get text of the tables rather than images):

[![enter image description here](https://i.sstatic.net/ILmxD.png)](https://i.sstatic.net/ILmxD.png)

[![enter image description here](https://i.sstatic.net/sSqkS.png)](https://i.sstatic.net/sSqkS.png)

These data suggest that on-target reads are 60%-80% of mapped reads. Note that they also lose a lot of reads in mapping, so we cannot exclude the possibility of mis-mapped garbage reads contributing to off-target mapping.


---

