Paul Flicek: Okay, thank you Stephen and thank you everybody
who's come out tonight. I'm going to spend maybe the next five to ten minutes talking
about the 1000 Genomes browser. So as Stephen described, the data sets are very large and
honestly to really work with the full, rich, and complex nature of the data, the ideal
way is to download the data sets, especially the VCF files, use the tools that exist for
them. It's very difficult to imagine how a web display scales to 1000 or to 2,500 or
to more. So you'll see some of the conventions that we use in the browser. We display things
by populations and we display other summary level data but as I said, to really get into
the richness of the data sets, there's a good argument to downloading the VCF files and
to investing in the tools.
The 1000 Genomes browser is based on version 54 of the ensemble code based. Those of you
who have used ensemble in the past will find it reasonably familiar because of this. It
contains all of the gene information that you would normally expect in ensemble. Gene
and transcript information, external references so connections to other databases, sequence
data. It's important to remember that the 1000 Genomes pilot project — all the analyses
was done, all the data was released on the NCBI 36 version of the human assembly. For
the full project going forward and the alignments that are being done in the full project, in
fact even the SNPs that were released today as part of the full project — those are
on the GRCH 37 assembly and so there's a difference between the human assembly that were used
and the pilot project and will be used for the full project.
So the pilot project browser incorporates essentially all of the 1000 Genomes pilot
data. There's still a few details there that we continue to add and refine as we go forward.
Eventually the pilot project will represent a stable collection, and we'll keep it in
perpetuity to be able to view the 1000 Genomes pilot project data. And as we — and as I
mentioned, as we release data on the full project, we're actually going to create new
browser for that. So there'll be the stable pilot project browser and then a new updateable
browser as we continue to release data going forward. All questions about that, in fact
all questions about data access as well can go to the info.thousandgenomes — info@thousandgenomes.org
address.
So here's just a view of the homepage. One of the things that has been mentioned already;
I just want to reiterate this is that all of the data that was reported in the paper
last week, in fact, we released this — this was the March 2010 release of the data. So,
in fact, the data's been completely available — all the SNP-calls have been completely
available for people to use for a quite a number of months before the paper was released.
And this goes back to what Gill said about how the project is very committed to releasing
data as soon as possible to make it as widely useful as possible for the community.
This is the most recent version of the browser. We actually just updated it today and as I
said, we have a few additional things to go. The main location view of the browser, again
this was built on ensemble. There's two — two important points here — there's navigation
on this side, zoom into that section right here where you have regions of the genome,
chromosome summaries, there's a link for re-sequencing, I'll get back to that in a second; that's
where we have information about each of the individuals in the high coverage trio. And
then, lower down, there's aspects of page configuration, so the key link here is configure
this page which changes what you're looking at, changes which tracks are available, as
well as export data which I'll come back to again in a few minutes.
So, if you click on the page configuration link, this is what comes up. There's a whole
host of things that can be configured if you look over here, going down to the types of
genes. Up at the very top, the first category is 1000 Genomes; so currently, well in this
configuration, 11 of 27 1000 Genomes tracks were turned on. I've listed all 27 of them
over on the side of the page and you can see that we've labeled the tracks just like we
labeled the pilot projects; so there's three types: the trio project, the low coverage
project, and the XM project, as well as the three letter codes for the populations. We
display tracks with the entire populations variance combined together so there are sixty
individuals in the CEU low coverage pilot. They're combined into a population level track.
Similarly for the trios, we have trio level tracks. There's a couple of other things just
to highlight going forward.
So, to give a preview to the things Jan will talk about. We have things like tandem duplications
and other structural variance. For more details on what these are, the show info button always
brings up little additional information. And finally there's a few other supporting data
sets like recombination hot spots and things like that that we incorporate in the 1000
Genome set of tracks.
So I mentioned already that we have these SNP tracks, the SNP tracks are based on the
populations. This is just an example of what they look like, where they are on the page,
and when you zoom in and take a look at them. So here we have three of SNP tracks and then
the recombination hot spots is also displayed there. Those of you who might notice that
the SNPs turn different colors here; the colors are associated with how they're annotated
within genes, so in this case, these SNPs are just upstream of a gene that you can't
see on this zoom in version, but when we have these light blue SNPs, those are color coded
for upstream of genes. The green SNPs in here, which I hope you're able to see right in this
area, those are synonymous coding SNPs so this is actually in a coding exon where those
SNPs are located.
All of the SNPs themselves are clickable and they bring up additional information when
you click on one of them. This is just an example of the box that pops up when you click
on one of the SNPs. It tells you the location. It provides additional information here — where
it was seen, you can see it was seen in the low coverage pilots, there's some additional
information as well, and a link will take you to a main SNP page that contains information
about the SNP properties. Much of this information has been extracted from DB-SNP and is provided
on that link.
We also have structural variant information. The structural variants are as you saw earlier,
different tracks for different types of structural variants. They're selectable, again, via the
"configure this page" link; and once the structural variants are showing and here's an example
of a larger deletion that I think Jan will also show on chromosome one. If you click
on this, it will give you some information on the validation status of that structural
variant. So you may also be able to see that this structural variant is actually associated
with no SNPs whatsoever in the East Asian population there so that things kind of tie
together. That's actually a deletion.
So I alluded to earlier, this concept of re-sequencing alignment that we provide for the six high
coverage trios. What this allows you to do is view any region of the reference genome
with the SNPs from the six high coverage individuals substituted in. So, this is not a de novo
assembly of these individuals but what it is, it's a view of the reference genome with
the SNPs from these high coverage individuals substituted in. We also marked the areas where
there's no coverage so that 15 percent of the genome that Gabor talked about that we
can't see into.
This is again, on the "configure this page" link, allows you to set up what you want to
look at here, which of the trios, which are located right down here, which of the trio
individuals you would want to see. This is the only place that we provide actually the
individual sequence data for the samples in the project via the browser. Everything else
is either the entire trio track or the population tracks.
This is an example of the output for that. Here we show just dots where the sequence
is the same as the reference. You can configure it to show the actual sequence and over here
we have regions color coded where we have homozygous or heterozygous deletions. When
it's heterozygous we use the ambiguity code for the nucleotide. If there's a little tilda
which isn't shown here that means there's no coverage in that region.
So we also provide sequence level data, the actual sequencing range, you can see aligned.
This is only for the trios. To view this you have to click on this "resemble settings"
button and eventually you can see all of the aligned reeds. For very small regions of the
genome, 200 base pairs, you can actually see all the reeds themselves — all of the reeds
with all of the sequence. But again, this is only for the six trios.
You can view linkage disequilibrium information, in context with the SNPs. Currently we calculate
the linkage disequilibrium from the HapMap and the Perlegen populations and the populations
to view this are selectable.
I talked a little bit earlier about data export, this provides summary data from the region
being viewed, and we're going to work some additional export configuration options to
make this a little bit easier to use to pull out just a small chunk of the genome — small
chunk of the SNPs. There's a whole host of other variation displays where a variation
is incorporated into different things. If you're on the gene page, which you end up
on the gene page if it's highlighted at the top, then you have an arrow over on the side
where you can get to variation information. This actually shows you variation information
in the context of protein domains, so how protein domains are affected by the variation
sequences on the transcript page which, again, highlights the tab to the far right on the
page. We have a couple of different displays showing how here the trio information affects
the transcripts. These are each of the six trios and down here, all the synonymous and
non-synonymous variants in the transcript.
And so, with that, I just have to acknowledge a few people at the EBI who have put this
together, built the back end databases and created this ensemble based browser for the
1000 Genomes and again, any questions about the browser or data access in general can
go to info@1000genomes.org. And I'll take any questions that you have.
[applause]
Male Speaker: Any plan providing API for example, for BIOPEARL
[spelled phonetically].
Paul Flicek: Yeah, so in fact we are going to release — we
are going to put up a [unintelligible] server. I hope we will have that available within
the next couple of weeks and then you can download the appropriate version of the ensemble
API and interact with the database that way. Yeah, so that will be available both for the
pilot project data and in the future, as we release data, on the full project that will
also be available.
Male Speaker: [inaudible]
Paul Flicek: Do we show inverted sequence? I'm not —
Male Speaker: [inaudible]
Paul Flicek: Ah, sequence inversions. Yeah, so, I don't
think — have these been identified by the structure variant?
Jan Korbel: I will answer that a minute. Not yet.
Paul Flicek: Okay.
Jan Korbel: That's the answer.
Paul Flicek: So, it is possible to identify some of these
by looking at arrant [spelled phonetically] sequence align reeds from the display that
I showed you where you could actually see all the reeds aligned. It would be very difficult
though to go through and look for those individually at this point and so Jan will really talk
about the structure variant. As we get, as some of these become discovered in the project,
we will put them into the browser and the full project going forward.
Male Speaker: [inaudible]
Paul Flicek: So, the question is — I'm repeating the
question. [laughs] So, the question is are there tools to dump genotype data and visualization
for haplotypes like there were in the HapMap project. Right now the most effective way
to get the genotype data is to download the VCF files and use the tools for that. We are
working towards graphically user interface that will allow you to do that essentially
by selecting regions of the genome that you're interested in doing that. Creating tools,
we've actually had some discussions as to how we create LD tools based on the 1000 Genomes.
None of those exist at this point. So with that, I'll turn it over to Jan Korbel from
EMBL who will talk about structural variants.