I am confused about the inner distance setting. From the manual file, it should be set to (fragementlength-2*readslength , eg: 300-2*50=100). But if the distance counting is based on genome location, then the distance between the pairs should be (fragementlength-2*readslength+inserted_introns_length). Does anybody know how tophat manage the intron insertion?
Unconfigured Ad
Collapse
X
-
I think that the mate inner distances is set in order to detect whether the mates are in different exons etc. That is, if the distance is much larger/smaller than the 200 (300-2*50) that the software has been told to expect, something interesting might be going on.
-
-
Hi snp_analyser. I'm afraid there is no good value - the inner distances depend on the sizes of your fragments and the lengths of your reads, which are experiment specific.
We typically use a tool like Bowtie to help us find our fragment sizes empirically. We run a paired-end alignment with Bowtie, using default parameters for -I and -X. We then examine the output to see, in general, how far apart the reads in a pair as aligned. This indicates the mate inner distance.
In terms of terminology, the "gap" or "inner distance" is the distance between the aligned reads (not counting the reads themselves). The "insert size", on the other hand, includes the reads themselves, so can be thought of as the "fragment size".
If you look at Bowtie output, the alignment position of a read is the position of the first base in the read (from the perspective of the forward reference strand). This means that if you subtract the alignment positions of the two reads in a pair, the result is actually "inner distance" + "read length". So you will need to subtract the read length to get the inner distance.
You should probably write (or find) a script to do this for you to ensure you examine enough pairs to get a representative feel for the value. Our data typically shows a normally distributed inner distance.
Comment
-
Latest Articles
Collapse
-
by SEQadmin2
Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.
The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
...-
Channel: Articles
06-02-2026, 10:05 AM -
-
by SEQadmin2
With the launch of new single-cell sequencing platforms in 2026, the field stands at an exciting inflection point. This article surveys the most impactful advances in the field and discusses how they’re reshaping research in cancer, immunology, and beyond.
Introduction
Single-cell sequencing technologies have undergone remarkable advances over the past decade, transitioning from low-throughput experimental approaches to highly scalable platforms capable of...-
Channel: Articles
05-22-2026, 06:42 AM -
ad_right_rmr
Collapse
News
Collapse
| Topics | Statistics | Last Post | ||
|---|---|---|---|---|
|
Started by SEQadmin2, 06-05-2026, 10:09 AM
|
0 responses
15 views
0 reactions
|
Last Post
by SEQadmin2
06-05-2026, 10:09 AM
|
||
|
Started by SEQadmin2, 06-04-2026, 08:59 AM
|
0 responses
33 views
0 reactions
|
Last Post
by SEQadmin2
06-04-2026, 08:59 AM
|
||
|
Started by SEQadmin2, 06-02-2026, 12:03 PM
|
0 responses
35 views
0 reactions
|
Last Post
by SEQadmin2
06-02-2026, 12:03 PM
|
||
|
Started by SEQadmin2, 06-02-2026, 11:40 AM
|
0 responses
23 views
0 reactions
|
Last Post
by SEQadmin2
06-02-2026, 11:40 AM
|
Comment