Is it unacceptable to remove chimeras, shorter than expected reads, and low q-score reads prior to doing a rarefaction analysis? I'm working with 454 16S data and it just makes sense to remove this kind of data from each library prior to alignment and clustering. I've been questioned on my method that told that rarefaction analysis should be calculated on raw data. Thoughts?
-
Last edited by lisa.brown; 02-11-2014, 07:29 AM. -
Would you have used those reads anyway for downstream analyses? If not, then I would find it difficult to argue against removing them. -
Great! That's my reasoning as well, the removed reads WOULDN'T be used for downstream analysis so why produce rarefaction data that isn't comparable to downstream hierarchy data?Comment
-
The part about this topic feels surprisingly grounded, and the details on the page is the bit that made me slow down. I’d keep <a href="https://kinpict.com/">ai family photo generator</a> bookmarked for later.Today, 06:37 PM -
NGS has revolutionized clinical microbiology by offering new ways to identify and surveil pathogens without prior knowledge of the target. One popular approach is 16S rRNA and ITS amplicon sequencing, which targets specific microbial markers. But studies are increasingly incorporating shotgun metagenomics, a technique that sequences all DNA from a sample without targeting specific microbial markers. This approach allows more detailed taxonomic classification,...10-30-2026, 06:46 AM
| Topics | Statistics | Last Post | ||
|---|---|---|---|---|
|
0 responses
26 views
0 reactions
|
by SEQadmin2
11-12-2026, 07:59 AM
|
|||
|
0 responses
35 views
0 reactions
|
by SEQadmin2
11-05-2026, 09:25 AM
|
|||
|
2 responses
54 views
0 reactions
|
by kinpict.com
Today, 06:49 PM
|
|||
|
0 responses
175 views
0 reactions
|
by SEQadmin2
10-28-2026, 09:57 AM
|
Comment