Jing
If I have a Galaxy dataset, do you think it is possible to develop a
pipeline that can
Megablast from Shotgun data for:
DNA gyrase only
Ribosomal ITSinternal transcribed spacer only
Cytochrome
RecA
Pol
As well as filter all model organisms?
Have you worked with the Galaxy Toolshed?
Scott
Scott Tighe
Senior Core Laboratory Research Staff
Advanced Genome Technologies Core
University of Vermont
Vermont Cancer Center
149 Beaumont ave
Health Science Research Facility 303/305
Burlington Vermont 05405
802-656-2557
On 10/6/2013 9:59 AM, Jing Yu wrote:
Dear Scott,
I think what you propose is doable.
You may
1. use a 16s or gyrase DNA sequence as feeds to blast against your
data to get the relative sequences,
2. and then use the sequences as feeds to blast against your
nucleotide database with appropriate filters.
There are several ways to make the steps. For example, you may already
have the 16s sequence from assembly against a reference genome.
And for Step 2, if you are not blasting thousands of times a day, and
believe in the recent stability of NCBI, then a simple web_blast code
will do the trick. Otherwise, since the local blast+ toolkit doesn't
provide the equivalent organism filters, you'll have to work a wit bit
on it:
Make a nucleotide database for Prokaryotes.
Search txid561[ORGN] on http://www.ncbi.nlm.nih.gov/nuccore (this is
for Escherichia as an example),
Send to 'File' -> Format ->GI List
When Blast, use this GI list as the value of this argument:
-negative_gilist
Then parse the Blast result.
Most of these can be automated with some code, but I don't know how to
incorporate it into Galaxy.
Regards,
Jing
On 4 Oct 2013, at 23:52, Scott Tighe <[email protected]
<mailto:[email protected]>> wrote:
Dear Jing
What you have outlined below is perfect.
I wonder how hard it would be to design a few filters that only look
a certain genes and or filter model organisms out of the dataset.
For example, say you want only data for 16s or only gyrase, but no
/E.coli/ and no /Pseudomanas aeroginosa/
Scott
Scott Tighe
Senior Core Laboratory Research Staff
Advanced Genome Technologies Core
University of Vermont
Vermont Cancer Center
149 Beaumont ave
Health Science Research Facility 303/305
Burlington Vermont 05405
802-656-2557
On 9/25/2013 12:06 AM, Jing Yu wrote:
Hi Scott,
My first thought is:
1. Remove rDNA sequences (and/or other well known highly-conserved
sequences to reduce the workload in step 2).
2. Blast, then remove sequences with > (say 99%) match to > (say 5)
genus. (Optional if step 1 is already good enough)
For step 1:
Build a fasta file of the chosen highly conserved sequences, and
use it as a feed to blast against your MiSeq result.
Remove positive hits.
For step 2:
Blast remaining MiSeq sequences against NCBI (or whatever) database.
Remove if it hits more than n genus.
Jing
On 24 Sep 2013, at 22:17, Scott Tighe <[email protected]
<mailto:[email protected]>> wrote:
Jing et al
Thank you for the offer to write some code to help advance the
metagenomics arena. It is certainly needed.
So the problem is well known with megablast and shotgun
metagenomics and without proper understanding and correct software
will yield very misleading and in many cases incorrect data. For
those of us who wish NOT to move to a protein level of comparison
for specific reasons, we are stuck.
*The Problem:*
If I megablast 50 million sequences from a HiSeq run, millions of
rRNA sequences will have a 99% match to all microbes rRNA genbank
deposits. Not surprizing since the rRNA is highly conserved. The
difference between E.coli and Shigella is 1 to 2 bases for the full
1540 bp 16s. So 16s is not useful for Genus level, and certainly
not Species
*So what happens:*
The returned matches will have many hits to whatever model organism
is in Genbank. For example E coli has 13000 entries for rRNA and
Sphearotilus has 3 entries for rRNA. If the blasted sequence
matches both, the results will mislead the investigator to think
they have 13000 hits to E coli, EVEN if the microbe is Sphearotilus.
*The cure?:*
If there was a way to filter/ remove all hits ? Let say, for
example, that a result has a first match (say E. coli) at >99% a
second match (say Pseudomanas) at >99% and a third , forth and
fifth match >99 for three other organisms. This sequence _must_ be
discarded because it is a conserve sequence.
Basically conserved sequence is the enemy and invalidates the
entire result.
*
**Another problem:*
If you have a reference sample with 19 non-model microbes, and you
run that by HiSeq Shotgun for metagenomics and then megablast, what
do you think you get? If E coli is not in the reference sample,
how many hits do you think you get? Yes, 10,000 of thousands. So
without removing conserved sequences, your data is wrong and you
are much better served by culturing and running a Biolog metabolic
panel and comparing to the sequence result.
So where do we start? I have some shotgun metagenomics data from
the reference sample which included the 19 microbes. That was data
from a MiSeq.
Scott
Scott Tighe
Senior Core Laboratory Research Staff
Advanced Genome Technologies Core
University of Vermont
Vermont Cancer Center
149 Beaumont ave
Health Science Research Facility 303/305
Burlington Vermont 05405
802-656-2557
On 9/20/2013 9:17 PM, Jing Yu wrote:
Hi Scott,
I can do some perl programming, such as local/remote blasting. Can
you specify your problem a little bit clearer, so that maybe I can
write a program to do just that?
Regards,
Jing
Gerald
16s is basically useless for identification to genus. Since I
started sequencing 16s in 1992, I have come to realize that
without sequencing the full 1540 bases, it is generally
misleading, and even than, it is not accurate enough to nail genus
on more than 1/2 the cases. However, what is your feeling on
ITS and gyrase, They seem to be far more discriminating but those
databases have been decommissioned sometime ago.
The desirable thing would be that Galaxy or NCBI add a "filter
conserved genes" [ ie any hit with a second choice greater than 3%
distance]. Something such as that.
If you (or others) are aware of such a thing, I'd love the here
about it.
Sincerely
Scott
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