Research Article |
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Open Access |
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Omics.pnl.gov: A Portal for the Distribution and
Sharing of Multi-Disciplinary Pan-Omics Information |
Ken J. Auberry, Gary R. Kiebel, Matthew E. Monroe,
Joshua N. Adkins, Gordon A. Anderson, and Richard D. Smith*
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Biological Sciences Division,
Mail Stop: K8-98, Pacific Northwest National Laboratory, P. O. Box 999, 3335 Q Avenue, Richland, WA 99352 |
| *Corresponding author: |
Dr. Richard D. Smith, PhD, Biological Sciences
Division, Mail Stop: K8-98,
Pacific Northwest National Laboratory, P. O.
Box 999, 3335 Q Avenue,
Richland, WA 99352,
Tel : 509-371-6576,
Fax: 509-371-6564,
E-mail : rds@pnl.gov |
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Received December 02, 2009; Accepted January 05, 2010; Published
January 06, 2010 |
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Citation: Auberry KJ, Kiebel GR, Monroe ME, Adkins JN, Anderson GA et al. (2010) Omics.pnl.gov: A Portal for the Distribution and Sharing of Multi-Disciplinary Pan-Omics Information. J Proteomics Bioinform 3: 001- 004. doi:10.4172/jpb.1000114 |
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Copyright: © 2010 Auberry KJ, et al. This is an open-access article
distributed under the terms of the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are credited. |
Introduction |
| The data production of scientific studies is growing at a nearly
exponential rate (Domon and Aebersold, 2006; Kiebel et al.,
2006). This growth leads to challenges in disseminating primary
experimental results for peer review and public access, while
simultaneously providing information that enables reproducing
the studies and/or analyzing the results in a proper context. Recent
mandates from various public funding agencies are requiring
data release plans be included as a project goal. This requirement
is coupled with an increased need for transparency in
complex research, as evidenced by the data release policies now
being implemented by peer-reviewed journals such as Molecular& Cel lular Proteomics (http://mcponline.org/misc/PhiladelphiaGuidelines.dtl). This combination of good scientific
citizenship and funding requirements has brought the data distribution
issue to the domain of scientific information management
researchers. |
Most mass spectrometry-based proteomics groups choose to
utilize one of the prominent data distribution sites, such as
Tranche (Falkner JA, Andrews PC, HUPO Conference 2006.
Long Beach, USA, Poster presentation), PRIDE (Martens et al.,
2005), NCBI’s Peptidome (Slotta et al., 2009), Human
ProteinPedia (Mathivanan et al., 2008), or PeptideAtlas (Desiere
et al., 2006). These sites make sense for small or targeted data
releases, but for large groups with diverse experimental approaches
and myriad biological model systems (e.g. Callister et
al., 2008; Kiebel et al., 2006), the choice may not be so clear.
Additionally, these sites are aimed at managing and disseminating
data that are associated with identifications and do not generally
make all the raw data available. This raw data is particularly
useful to developers of analysis tools, as well as in cases
where the integration of multiple data sources can improve the
confidence of a result. Our goal in the construction of this site is
to augment these pubic repositories by making available entire
sets of raw and processed results along with their associated
metadata. This requires that careful considerations be made regarding
the design of the site in order to render it useful to the
community. Herein, we present an initial version of such a site,
referred to as the Biological MS Data and Software Distribution
Center, which can be visited at http://omics.pnl.gov. This site
leverages vast amounts of pre-existing experimental data and
metadata gathered since 2001 and stored in our purpose-built
data management system, PRISM (Kiebel et al., 2006). |
Design philosophy |
| The initial intent for the site was simply to provide local researchers
with a mechanism for making large sets of experimental
results available to both their collaborators and the greater
scientific community. This intent was coupled with a desire to
organize the data in a hierarchical structure and present results in such a way as to make them readily usable and understandable
by researchers who were familiar with the field, but not
necessarily experts in our particular methodologies. In addition
to presenting the hierarchical metadata, another expectation was
providing website users with a capability for downloading large
sets of raw and processed instrumental data (greater than single
Terabytes). |
Omics research at Pacific Northwest National Laboratory
(PNNL) involves a number of different collaborations, many of
which include bioinformatics components that require large volumes
of raw data at all levels of quality to produce accurate
results. This system provides one model to support the current
needs of these collaborations while also providing the frameworks
necessary to build more advanced capabilities. In the past,
the information generated by these collaborations has necessitated
the shipment of hard drives full of data across the country.
Streamlining this aspect of our data delivery process has driven
the design of the site’s initial requirements as well as many aspects
of its architecture. We currently have over 150 terabytes of
raw and processed data in our archives and these developments
enable its dissemination. |
Types of data made available |
| The majority of the data available on the site comes from liquid
chromatography coupled mass spectrometry (LC-MS) studies
of proteomes, metabolomes, etc., conducted using either traditional“shotgun” proteomics (e.g. Washburn et al., 2001; Adkins
et al., 2006) or the accurate mass and time tag methodology (e.g.
Smith et al., 2002; Shi et al., 2006). These data include raw LCMS
and tandem mass spectrometric results (LC- MS/MS) from
multiple instrument types, ranging from benchtop linear ion traps
to custom built LC-FTICR platforms with very high mass measurement
accuracy. Also available are processed data in the form
of peptide identifications for LC-MS/MS, peak deconvolution
information for high mass accuracy LC-MS, and MASIC-generated
(Monroe et al., 2008) single ion chromatograms for LC MS(/MS) data. While the current collection of data is largely
composed of mass spectrometric results, it is our intent to present
other types of -omics data on the site as they become available. |
Selected open source software packages are available on the
site that allow others to process or understand the processes used
to analyze the data. Some of these include tools for the manipulation
and parsing of various protein database files, tools to assist
in data extraction, analysis and refinement of LC-MS (/MS)
data, as well as an array of programs to facilitate visualization
and presentation of omics-related data. A selection of these applications
is summarized in Table 1. Presentations and poster
reprints describing many of these processes are also available
on the site, along with a full list of available software packages
(http://omics.pnl.gov/software/). |
| Table 1: Selected software packages available on the site. |
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Using the site |
| Upon arriving at the site (http://omics.pnl.gov/), the user is
presented with a menu of possible activities, including browsing
or searching available data, downloading various data analysis
software packages, viewing research posters and presentations,
registering a new account, etc. While not needed to browse the
contents of the site or download software, a minimal registration
process is necessary in order to download research data. This
registration enables us to gather aggregate usage data required
for reporting purposes, as well as statistical information regarding
how the site is used and which types of data are frequently
downloaded. |
Once signed in, the user can search the site for associated keywords
or browse via several top-level entities that hierarchically
arrange the available data into categories such as journals, associated
publications, organisms, year of production, and mass
spectrometer type. Either method yields a structured tree view
that represents the subset of data selected. From this view, the
user can descend into the hierarchy to obtain increasing levels
of detail. |
From the “Experiment” level down, new options are made
available in the form of downloadable content icons located to
the left of each entry. These icons allow collections of data to be
marked for later retrieval, using a “shopping cart” metaphor familiar
to anyone who has ever made an online purchase (Figure
1). A running tally of selected files and their cumulative sizes is
summarized in the right hand menu column, along with estimated
download times for various speeds of connectivity (Figure 2).
Currently, a user could conceivably select more than 10 Terabytes
of data, an amount impractical for most users to download or
even store. |
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Figure 1: Browsing data by category. The icons to the left of each detail entry
indicate that data are available and can be added to the user’s cart. The same
icon with the plus sign indicates that data from entry along with all its children
should be added. |
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Figure 2: Cart Status and Estimated File Transfer Times panel. |
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Once the user selects a set of data files to be retrieved, the “Download from your Cart” option can be selected from the side
menu, taking them to a page that summarizes their cart contents
in detail (Figure 3). From this page, individual items can be removed
from the list, and entire classes of data can be enabled/disabled. This option is useful for deselecting data from a certain
type of instrument, for example. The contents of the cart can then be transferred to the user’s computer using a combined
streaming/caching mechanism, described below. |
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Figure 3: Inset view of the Download Cart Management interface. From here,
users can remove items from their cart, or
disable an entire class of results. |
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Implementation details |
| The core component of the site is the metadata storage engine
powered by a PostgreSQL database (PostgreSQL 8.1.3, http://www.postgresql.org/). This framework maintains all of the information
necessary for the operation of the site, such as the
locations of files in the archive storage hierarchy or the contents
of a user’s data "shopping cart". When data are to be made available
on the site, metadata for the entities involved is gathered up
from an internal-only PRISM/DMS server and inserted into the
Postgres database on the publicly accessible server that hosts
the website. This server is connected to a multi-petabyte file
archive system located in EMSL, the Environmental Molecular Sciences Laboratory at PNNL (http://www.emsl.pnl.gov/) via a
10Gbps Ethernet connection. Because all of our instrument and
analysis data are stored in this archive system, no actual mass
transfer of raw data needs to take place. The locations of the
files can simply be referenced in the distribution site’s database
and be served directly from the archive. |
The metadata storage tables are accessed using PHP (PHP
5.1.2, http://www.php.net/) as the server-side scripting language
that dynamically generates page content for various types of
metadata within the hierarchy. These data types include experimental
data that describes the conditions under which a sample
was prepared, LC-MS (/MS) data along with the parameters used
to govern the operation of the instrumentation, and analysis results
that describe things such as the peptides identified in a particular
set of data. This content is then served to the end-user by
an Apache web server (Apache HTTP Server, http://httpd.apache.org/) running under Red Hat Enterprise Linux 4
(Red Hat, Inc, http://www.redhat.com/rhel/). |
To minimize page loading times, navigation elements such as
the tree views used for the data browsing and search pages have
the bulk of their content loaded on demand, using Ajax-style
asynchronous calls (Garrett, 2005) that are triggered as a user
drills down into the available data. These same types of calls are
used to manage and report the contents of the user’s cart, which
lends a greater degree of interactivity to the site while minimizing
the number of full page reloads. |
When full sets of data are triggered to download from the site,
a background process is invoked that steps through the contents
of the user’s cart in a hierarchical fashion that corresponds with
the layout of the requested data. Once the manifest for the package
is generated, the files themselves are collected and combined
into an uncompressed Tar fi le (Gnu Tar, http://www.gnu.org/software/tar/). Even as the file is being constructed
and cached in temporary storage, the server is already starting to
stream the contents to the user, which reduces the wait time experienced
by the user. The use of the cached copy of the file
allows for interrupted downloads to be resumed and mitigates
the possibility of having to restart a large transfer from the beginning
in the event of a network failure, etc. |
Future plans |
| The system is continually undergoing development to add
new capabilities and features to expand its use to the scientific
community. Currently, mass spectrometric information and analysis
results are only made available in formats native to the instruments
or software packages that generated them, rather than
in more generic formats such as mzML (http://www.psidev.info/)
and pepXML (http://tools.proteomecenter.org/wiki/). Efforts
are underway to automate the production of these file formats
from the existing data and display them alongside the native files.
Making these interchangeable files also opens up opportunities
for automating the deposit of data in other public repositories.
Another planned addition to the site is tighter integration with
our existing data management system (Kiebel et al., 2006), which
will provide researchers with the ability to automatically push
data products out to the dissemination site based on previously
established matching criteria. As more and different types of data
are made available on the site, additional options will be added
to the system’s search facility to allow deeper exploration based on the contents of the processed data (proteins ID’s, gene annotations,
etc.) rather than solely through its associated metadata. |
Acknowledgments |
| The research described in this paper was performed in the
Environmental Molecular Sciences Laboratory, a national scientific
user facility sponsored by the U. S. Department of Energy
Office of Biological and Environmental Research and located
at Pacific Northwest National Laboratory. Portions of this
work were supported by the Department of Energy Office of
Biological and Environmental Research at PNNL grant
(ER63232-1018220-0007203), the NIH National Institute of
Allergy and Infectious Diseases (interagency agreements Y1-
AI-4894-01 and Y1-AI-8401-01) and the NIH National Center
for Research Resources (RR18522). PNNL is a multi-program
national laboratory operated by Battelle for the DOE under Contract
DE-AC05-76RLO 1830. |
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