Qlucore Omics Explorer is used by scientists and corporations across the globe.
"Qlucore is a great help for us as translational immunologists and cancer researchers to analyze our data independently and observe changes in real time. Of course, it requires a certain understanding of statistics, p- and q-values, but this gives the analysis a very large scope for design, for which one would otherwise need biostatisticians and graphic designers."
"Since we realized the value of Qlucore for our research, we have not published a paper without Qlucore analyses."
Head of Research, PhD Matthias Hardtke-Wolenski, Department of Gastroenterology and Hepatology in Essen, Germany
Group Leader, PhD Laura Buitrago Molina, Department of Gastroenterology, Hepatology and Endocrinology at Hannover Medical School, Germany
"Qlucore helps me to get an overview of what happens with the gene expression profile as we change our sampling location over space and time with the patient.”
“As I see it the two top benefits of Qlucore Omics Explorer is that you can get an overview of the data but at the same time it is transparent in the sense that you know when you add or take away a variable from the data, it´s not just a black box, it´s a transparent software, it´s very clear.”
Research Group Leader, MD, PhD, David Gisselsson Nord, Principal Investigator, Lund University, Sweden
"Qlucore allows us a quick and efficient analysis of large data sets of proteomics and genomics data, in a simple an intuitive manner. Together with a quick statistical analysis generates publication ready figures accelerating data analysis. This software has boosted our research in sperm biology"
PhD, Fernando J Peña Vega, Laboratory of Equine Reproduction, Veterinary Teaching Hospital, University of Extremadura, Spain
"Qlucore Omics Explorer has helped me and my colleagues to perform bioinformatic analyses on data from different omics disciplines on our own. The software is a useful tool for statistical analyses and also offers several ways of data visualization."
PhD student, Mark Mensink, Department of Immunology, Leiden University Medical Center, Leiden, The Netherlands
“We use Qlucore as a first step to get an overview of the data, and to identify deeper questions we should be asking,“ says Dr Bianchi. “I start with a PCA [principal component analysis], as a first quality analysis of the samples and to start identifying patterns in the data. We then perform statistical analysis and visualize the data using a heatmap.”
Dr Elisabetta Bianchi, Senior staff scientist, Pasteur Institute in Paris, France
“With just a couple of mouse clicks, clinicians can quickly analyze their data by generating a heat map or principal component analysis (PCA) and get the list of differentially expressed molecules”
Rolando Garcia-Milian, MLS, AHIP, Yale School of Medicine, US
“It is now years that we use Qlucore to identify gene expression patterns in immune cells and microbes. Its simplicity of use, versatility and multiple data visualization modes makes it a very attractive and powerful statistical analysis tool”.
Gerard Eberl, Professor Microenvironment & Immunity Unit, Institute Pasteur, France
“Qlucore accelerates our research in an unprecedented manner. This extremely useful tool highlights for its simplicity, robustness, and usability with a wide range of proteomics and genomic datasets. It supports both explorative and hypothesis-driven research on fundamental and translational studies. A computational solution for biomedical researchers.”
Dr. Sergi Aranda, Center for Genomic Regulation, Barcelona, Spain
“We have used the Qlucore Omics Explorer program for the past few years and cannot imagine working without it. The user interface is incredibly intuitive and we are able to teach new lab members how to use the program in a matter of minutes. We love how quickly the software is able to transition between different visualizations and how easily we can customize the visuals and the output. The power of the software is a definite strength in that we are able to input a large number of files, either self-generated or from the public repositories, and the program easily accommodates these large datasets and performs beautifully. We have tested a number of different programs over the years and none compare to Qlucore."
James Mulloy, PhD, Adjunct Professor of Pediatrics, Cincinnati Children's Hospital Medical Center, Ohio, USA
"This tool might literally save you years of your life."
Professor Ulrich Steidl at Albert Einstein College of Medicine, New York, USA
“With Qlucore I instantly see how my data responds to changes in statistical parameters and cutoffs, and have a choice of the best methods for high dimensional data. I can use both supervised and unsupervised methods as 3D PCA, heatmaps, and clustering. Hypotheses testing is significantly helped by this constant feedback, as I can set up analysis, view results, and modify settings with a few clicks.”
Dr. Berkley Lynch, Senior Director of CNS Research at Rodin, USA
“Before we had the Qlucore tool, the group was analyzing data on a smaller scale. We would focus on a few genes and we could analyse them using Excel and Graphpad. Now that we carry out large scale analyses that generate more data, Qlucore is vital.”
Dr Elisabetta Bianchi, Senior staff scientist, Pasteur Institute in Paris, France
“Omics Explorer has become our ‘go-to’ tool for getting a first glance of any multivariant data problem. It provides us with simple and fast visualisation of data, irrespective of the data source.“
“Typically we are looking at thousands of changing features and it’s great to have those summarised in a PCA [principal component analysis] plot or heat map. It means we can very quickly see if there is something interesting going on and if so whether we should dig deeper.”
“With Omics Explorer, we could work together with the proteomics and transcriptomics data on the same platform so there was no need translate the outputs from one tool to another. It made it very easy to compare data, to communicate amongst the researchers, and to discuss the next steps.”
Dr. Josef Rasinger, National Institute of Nutrition and Seafood Research (NIFES), Norway
“The strength of the Qlucore software is being able to conduct and validate statistical analyses and also produce a variety of visualizations. It has excellent visualization tools that can make very nice depictions of the data and heat maps.”
Nardin Samuel, MD/PhD, Cancer Genetics Program at the Hospital for Sick Children (SickKids) in Toronto, Canada
"In this process of this study, we have found that Qlucore has been very helpful in supporting a biologist without sufficient mathematic background to apply bioinformaticsapproaches in their studies. This has been essential for the implementation of the project."
Xialong Fan, Professor, Beijing Normal University, Beijing, China
“Qlucore is indeed an impressive tool. It is very fast and delivers excellent control of the analysis. I really enjoy it.”
Ole Ammerpohl, PhD, Kiel University, Germany
"With Qlucore we have been able to visualize and rapidly explore microarray data collected from 2 years’ research in less than a few hours."
Carl Borrebaeck, Professor Lund University, Sweden
"With synchronized plots of patients and genes I have discovered new patterns."
Frida Abel, PhD, Sahlgrenska University Hospital, Gothenburg
"The freedom for me to explore data in innovative ways has led to new discoveries."
Pierre Åman, Professor, Gothenburg University
“Qlucore Omics Explorer fulfils an idea we have been considering for 18 months or so, all in the space of a few minutes.”
John Lock, PhD, Karolinska Institutet, Sweden
"Qlucore enables very rapid and intuitive data analysis. By that scientists themselves are doing advanced bioinformatic analysis."
Matthew Arno, Ph.D, Genomics Centre Manager King's College London, UK
“I’m very excited using Qlucore Omics Explorer which besides the 3‐D dynamic PCA also offers a broad range of statistical methods such as t‐test, ANOVA and regression.”
Philippe Guardiola, Ph D, Plateforme SNP, Transcriptome & Epigenomique, University Hospital Angers, France
"For me, one of the most compelling reasons for choosing Qlucore's Omics Explorer for the Human Protein Atlas program was its simplicity."
Professor Mathias Uhlén, Royal Institute of Technology, Sweden
"Not only was the software highly interactive, but it could also be easily understood by biologists, even if they had little or no previous knowledge of bioinformatics."
Dr Kulkarni, Division of Ophthalmology and Visual Sciences at Queen’s Medical Centre (QMC), University of Nottingham, UK
“Qlucore Omics Explorer is the best software on the market and I use it several times a week.”
Professor Finn Cilius Nielsen, Copenhagen University Hospital, Denmark
“Overall, Qlucore is an intuitive and comprehensive toolset empowering scientists to understand the story that data tells, without an obligation to consult with biostatistician for every minor detail of upcoming analysis.”
“Qlucore is a fast and efficient tool to quickly get a sense of complex datasets and better understand dynamics of biomarkers interactions. Qlucore software allowed us to deconvolute and analyse protein dataset derived from 660 Raybiotech (Norcross, GA) biomarkers array full screening service in the monocyte-like cells culture supernatants. In our dataset, we had three experiments conducted in the same way on two cell lines, which were treated not only with different stimulation conditions, but also with different doses of stimulators. Use of Qlucore allowed us to discriminate the differences between the two cell lines and clearly differentiate effects of the stimulator conditions.”
Vera Nezgovorova, Postdoctoral Associate, Yale School of Medicine, USA
"The versatile data import and the ease of use are important benefits. Qlucore forms a key role in our research.”
“If we come in with a hypothesis, it’s simple to use and includes the necessary functionality but the real power of Qlucore is in assessing structure when we are coming in with hypothesis-free data.”
Dr. Adam Stevens, University of Manchester, UK
“Qlucore allows me to do analysis on my own. There are things that I know are biologically relevant that I can check on the fly.”
“I’ve been working with protein arrays for seven years and always had to get bioinfomaticians to do the analysis. They are very much in demand so they are a rate-limiting step. Now it is pretty easy to put my data in and I can get results within an hour – and I play with my dataset more now that I can do it myself.”
“The more I use the software the more I keep discovering new things.”
Steven Kornblau, Professor of Medicine, UT MD Anderson Cancer Center in Houston, Texas, USA
“Qlucore is a really great way to explore large data quickly.”
“Initially I wasn’t sure of the best way to analyze this large dataset and was looking for a solution. When I first put the data into Qlucore, it looked interesting almost straight away. As soon as we started using Qlucore we saw clear differences in some of the chemokines (proteins that control immune cell migration) between the A, B and C virally infected groups.”
Darragh Duffy, Immunologist, Institute Pasteur, France
"What has been interesting since using Qlucore is how the software has made it possible for the biologists to visualize their research results in striking ways."
"Qlucore is fast, very intuitive and the graphical user interface is simple to use. It means that the biologists at CICS can now do fundamental statistical analyses independently, having more control of their own data. It also means that our informaticians can concentrate on very advanced bioinformatics on the wilder frontiers of statistical analyses."
Dr. Sasha Singh, The Center for Interdisciplinary Cardiovascular Sciences, Boston, USA
"With Qlucore, you can see how things are changing in real time when you set a p-value cut-off for statistical analysis. Also it's flexible, so you can run custom R scripts if required."
"We have a high volume of experiments and we want results promptly. The Qlucore software is definitely helping. It means that cell biologists like myself can look at data, analyze and perform statistical analyses for a presentation or a paper without having to go through our bioinformatician."
Dr. Elena Matsa, Stanford University, USA