Standards-compliant software tools for curation and public deposition of proteomics data

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We are now in the 'post-genomic' era of biological research since the complete genetic makeup of many organisms is now known. The genome sequence essentially provides us with the parts list of the complete organism and the blueprint describing how the organism functions. The genome sequence is only a static representation though - it is the same in all cells of an organism and does not change during the organism's lifetime. All cellular functions are provided by proteins, which are each encoded by a gene within the genome. The set of proteins expressed in each cell changes dramatically as the organism develops and as it is placed under different environmental conditions, such as external stresses on cells. Researchers are interested in studying the complete set of proteins in a sample, which is called the proteome. Many research laboratories around the world are now performing these proteomics studies, using mass spectrometry to identify large sets of proteins concurrently. Proteomics studies may be used simply to identify the proteins present in the samples of interest, or to compare the proteins present in one condition compared with another. These techniques can be used to find the proteins that are switched on or off, for example during a disease process or following infection with a parasitic organism, helping us to understand the molecular basis of the response. These studies can generate vast data sets, which are produced first by the mass spectrometer and then by the software package chosen for data analysis. It can be difficult for researchers to access and analyse data produced in other laboratories, unless they use the same software package in their laboratory, because each piece of software generally only works with its own data format. A worldwide consortium has formed to standardise how data from these studies are reported, and in this context, my group has led an initiative to create a single data format for storing the results of proteomics studies. We have recently released a standard format for protein identifications made from mass spectrometry data, called mzIdentML. In this application, we are aiming to build software so that it is easy for software developers around the world to build new applications or alter existing applications so that they can read and write data in this format. This will mean that data produced in one laboratory could be analysed using a variety of software packages, not just the software in use in the source laboratory. There is also a growing movement for researchers to store their data in public databases when they publish a study. This will allow other researchers to download the data to check their findings and to integrate the published data with their own results. These processes will be greatly simplified by having a worldwide-accepted standard format. In this application, we are developing a set of software tools for performing standard tasks on identification data, for example performing statistical analysis to determine significance of particular results. These tools are open-source, as we intend for other software developers, working both in academia and industry, to re-use these tools in their applications. We are also developing a graphical viewer so that scientists can visualise their data in different ways to help understand the results contained in the large data sets. The viewer will be integrated into an application produced by one of the main public databases, making it simple for scientists to analyse their data and then upload it directly to the public database when they publish a journal article. These developments will help scientists working in proteomics to share their data. In turn, this will help proteomics databases to grow rapidly, which will benefit all molecular biology researchers as they will have access to huge protein data sets for data mining, allowing new biological discoveries to be made.