[mira_talk] Re: Metagenome assembly
- From: Shaun Tyler <Shaun.Tyler@xxxxxxxxxxxxxxx>
- To: mira_talk@xxxxxxxxxxxxx
- Date: Wed, 2 May 2012 08:24:33 -0500
I was thinking along the same lines. Even if it turned out not to be an
issue with the assembly it would certainly speed things up by cutting down
the number of reads.
Shaun
From: Keith Robison <keith.e.robison@xxxxxxxxx>
To: mira_talk@xxxxxxxxxxxxx
Date: 2012-05-01 07:05 PM
Subject: [mira_talk] Re: Metagenome assembly
Sent by: mira_talk-bounce@xxxxxxxxxxxxx
If you are seeing a lot of human contamination, one approach would be to
use Bowtie2 against a human reference assembly. Then take everything that
didn't align & feed that into MIRA. In a similar manner, if there were
some well-known bacterium dominating the data, you could also use this
approach to deplete those reads
Keith
On Tue, May 1, 2012 at 7:47 PM, Shaun Tyler <Shaun.Tyler@xxxxxxxxxxxxxxx>
wrote:
Another thing I thought I'd mention in case you're curious also has to do
with the data I got from the Edena assembly. When I started checking out
some of the large contigs I thought they were all crap because a basic
BLASTn was returning nothing and I would have thought at least some
segments would match well enough. But when I switched to doing BLASTx I
got hits that were 100% and contiguous in the matching genome???? Maybe
this has to do with the consensus called due to the mixed population but
I somehow don't think so. So far I haven't had time to look at this any
further but it sure is weird!!!
Shaun
Edena v3 development version 110920
Loading file "out.ovl"... done
reads length: 90
number of reads: 24447638
number of nodes: 24175258
number of edges: 14877278
minimum overlap size: 50
Concatenating overlaps graph... done
Renumbering nodes... done
Updated number of nodes: 18649163
Discarding non-usable reads... done
16781194 nodes corresponding to 20161590 reads have been discarded
(82.5%)
Removing dead-end path... done
889629 dead-ends (l<=179nt) have been removed
corresponding to 1119882 reads (4.6%)
Concatenating overlaps graph... done
Renumbering nodes... done
Updated number of nodes: 800286
Contextual cleaning: step1... done
Contextual cleaning: step2... done
605279 edges have been cleaned out
Concatenating overlaps graph... done
Renumbering nodes... done
Updated number of nodes: 701294
Removing dead-end path...done
3837 dead-ends (l <= 179nt) have been removed
corresponding to 13623 reads (0.06%)
Concatenating overlaps graph... done
Renumbering nodes... done
Updated number of nodes: 692763
Nodes coverage sampling:
mean: 15.28
median: 9.82
sd: 48.00
minimum average coverage required for the contigs: 2.45
Resolving bubbles... done
bubbles resolved: 28
Concatenating overlaps graph... done
Renumbering nodes... done
Updated number of nodes: 692679
Estimating pairing distance... done
paired-end allowed distance range(s) [min,max] (observed
distribution)
dataset 1: [88,303] (mean=196.119 sd=53.898)
Sorting nodes...done
Building contigs... done
Number of contigs: 21801
sum: 5436997
N50: 259
mean: 249.392
max: 47186
min: 100
Contigs elongations were stopped due to:
branching: 6962
dead-end: 36640
Inactive hide details for Bastien Chevreux ---2012-04-26 03:54:27 PM---On
Apr 25, 2012, at 22:44 , Shaun Tyler wrote: > Does anBastien Chevreux
---2012-04-26 03:54:27 PM---On Apr 25, 2012, at 22:44 , Shaun Tyler
wrote: > Does anyone have experience assembling metagenome d
From: Bastien Chevreux <bach@xxxxxxxxxxxx>
To: mira_talk@xxxxxxxxxxxxx
Date: 2012-04-26 03:54 PM
Subject: [mira_talk] Re: Metagenome assembly
Sent by: mira_talk-bounce@xxxxxxxxxxxxx
On Apr 25, 2012, at 22:44 , Shaun Tyler wrote:
Does anyone have experience assembling metagenome data with Mira.
I have a feeling this might be one of those applications that will
give Mira a nervous breakdown. The data is 100 bp paired end
Illumina reads from libraries derived from nasal swabs. There is
slightly in excess of 2 Gbp of data per sample (25 M reads or so).
25m reads alone are not a big problem, I've done RNASeq assemblies with
40 to 50m and I know at least two users who ventured into the 100m area
(but I'd not recommend doing that). You just need a machine which is big
enough.
However, I fear that some aspects of metagenomes will indeed lead to
problems. If you assemble the date in "genome" mode, I think MIRA will
have a hard time in guessing the "coverage" of this "genome" ... and that
will lead to misassemblies. If you assemble in EST mode, things will
probably go faster, but there again I am almost sure misassemblies will
happen.
The thing is: in metagenomes, there is no such thing as an "average
coverage" because this "average coverage" will be mainly driven by
population ratios. I have no idea how to get around this.
In any case: if you are making trials, set
-SK:bph=31
This will probably greatly reduce misassemblies at the expense of genomes
with low abundance being less well assembled.
Would love to hear back from you on that.
B.
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