Instead of using all the transcripts as reference for the RNA-seq analysis, can I use a small subset which I am interested? I compared the results, of course, the expression values from the small subset is higher than that from the whole set. What I'm concerned is that, Does it cause any bias to the expression values?
Unconfigured Ad
Collapse
X
-
I used RNA-seq analysis in CLC genomic workbench.Originally posted by dpryan View PostThis will depend upon how you do your mapping and then the expression quantitation.
Set parameters is as below
Minimum length fraction: 0.9
Minimum similarity fraction: 0.8
Maximum number of hits for a read: 10
What is the right way to do the mapping and quantitation for a small subset reference? I really appreciate if you can provide a reference for this. Thank you very much!
Comment
-
-
I don't think it's a good idea. It's always better to map to all the transcript because your data is coming from total RNA ( or poly-A RNA). It can happen that when you map to your subset, some reads maybe map in a better way to transcript that are not in your subset..
Comment
-
-
Yes, you're right. It is more robust to use entire assembly, since the result would be normalized by the entire mRNA expression, and also much easier for downstream analysis.Originally posted by NicoBxl View PostI don't think it's a good idea. It's always better to map to all the transcript because your data is coming from total RNA ( or poly-A RNA). It can happen that when you map to your subset, some reads maybe map in a better way to transcript that are not in your subset..
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 -
-
by SEQadmin2
Studying ecosystems means dealing with complex, multi-species communities that are hard to observe at scale. This complexity, however, hides many important questions to be answered, from how biogeochemical cycles work and how climate change can affect species distribution to how conservation strategies can work best.
Genomics, particularly since the expansion of NGS, has transformed ecosystem ecology. By sequencing environmental DNA, we can now assess biodiversity without direct...-
Channel: Articles
05-06-2026, 09:04 AM -
ad_right_rmr
Collapse
News
Collapse
| Topics | Statistics | Last Post | ||
|---|---|---|---|---|
|
Started by SEQadmin2, Today, 08:59 AM
|
0 responses
8 views
0 reactions
|
Last Post
by SEQadmin2
Today, 08:59 AM
|
||
|
Started by SEQadmin2, 06-02-2026, 12:03 PM
|
0 responses
21 views
0 reactions
|
Last Post
by SEQadmin2
06-02-2026, 12:03 PM
|
||
|
Started by SEQadmin2, 06-02-2026, 11:40 AM
|
0 responses
16 views
0 reactions
|
Last Post
by SEQadmin2
06-02-2026, 11:40 AM
|
||
|
Started by SEQadmin2, 05-28-2026, 11:40 AM
|
0 responses
29 views
0 reactions
|
Last Post
by SEQadmin2
05-28-2026, 11:40 AM
|
Comment