Three ways you can use the free Gel IQ tool to get more out of your 2D gel experiments

Number 1: Quality control your 2D gel image analysis data

Gel IQ is the perfect tool to assess how correct and complete your image analysis really is.

Short of looking through and checking every single spot in the analysis, there has so far been no comprehensive way of ensuring your analysis was good.  Apart from being a clear scientific shortcoming, this inevitably results in time and money being spent on validating false hits, as well as missing out on potentially important expression changes.

By calculating a combined correctness score for your 2D gel image analysis using Gel IQ, you are able to quickly confirm that your quality is good enough or that either the spot detection or spot matching needs some tweaking.

How does it work? Simply download Gel IQ for free, upload your image analysis file, and score your analysis.

Our experience so far has shown, that anything above 70% can be deemed an acceptable analysis. If you are above 80% you should feel confident that you have a pretty complete and correct data set.

By logging the Combined Correctness scores you achieve for different sample types or stains, you will soon develop a feeling for when an analysis was good or not.

Number 2: Optimize your analysis protocol

In addition to using Gel IQ as a post-analysis quality check, you can use it to iteratively improve your analysis procedure.

Just as you would improve any other experimental protocol in your research, the image analysis process should undergo an equally systematic scrutiny. After all, a chain is only as strong as it’s weakest link!

You can start by running a more or less “automatic” analysis of your gels (for the record: we also do not believe in so-called fully automatic 2D gel image analysis…). Basically, set the parameters to what you consider to be most optimal for the gels in question, run the analysis, and score the outcome using Gel IQ.

Depending on the results, you will quickly see if either the spot detection or spot matching needs improvement. Go back and change the parameters, if possible, and re-run. If you are using a software package that doesn’t allow you to adapt detection or matching parameters, you will know what areas to focus on during manual editing.

Using Gel IQ, you will be able to confidently and systematically optimize the protocols you use for 2D gel image analysis.

After all, only what you are able to measure and quantify can also be systematically optimized…

Number 3: Evaluate the performance of different software packages

Ever stood before the decision of which software package to purchase for your analysis needs?

Now you no longer have to try and guess which software package are service works best on your data, you simply use Gel IQ to score the output you are able to achieve with them.

As always, you simply export the analysis files from the different software packages, score the quality using Gel IQ, and hey presto – you have some hard numbers on how good they really are!

Finally, we’d just like to point out again that Gel IQ is a non-commercial free-ware, based on the Combined Correctness metric, which was developed together with six proteomics research labs. We don’t want to charge for Gel IQ because we feel it is invaluable and necessary in helping you get the most out of your 2D gel experiments. And good science is something we all benefit from.

Jump over to the download page for Gel IQ

Filed under: 2DE Knowledge Base, News, Tips and Tricks , Gel IQ, optimize image analysiss results, Quality assurance

Free proteomics software tools that help you get the most out of your research

Occasionally some of our internal research projects result in really neat innovations, that we are able to spin off as free-ware.

To make it easier for you to access them, we are now collecting these free tools in a new section of the Ludesi website, which we have aptly called “Free Tools“.

Depending on the nature of the tool, you will find links and instructions on how to either download the application for free, or simply access it directly through a website.

Here is a quick introduction to the tools we are currently listing:

1. Gel IQ – score the quality of your 2D gel image analysis data

Finally, an easy-to-use tool to create a quality score of how good your 2D gel image analysis really is. And most importantly – it is independent of what software package was used to perform the analysis.

Just download the free tool, upload your image analysis file (there are instructions on how to do this – don’t worry), and start scoring your quality.

Gel IQ is based on the Combined Correctness metric that was developed by Ludesi in collaboration with leading proteomic research labs.

Ludesi’s CEO Ola Forsstrom-Olsson has been presenting and discussing the issue of 2D gel image analysis data quality on numerous occasions, as part of the HUPO Industrial Advisory Board and most recently at the Quality Control in Proteomics Workshop in Hinxton. The extremely good reception that the Gel IQ tool has had so far underlines the importance of such a free tool to the community.

Try out Gel IQ on your own data by downloading it completely for free here.

2. Protein Relation Miner

Our MS data-mining tool is set out to answer one question:
How can my proteins be described and how are they related?

You simply upload a list of SwissProt accession numbers, and the application digs out information for each protein and finds similarities.

The information used today is GeneOntology terms, SwissProt keywords and SwissProt function description.

The results are displayed as tables showing which information matches among the proteins and what proteins are most similar.

Try the free Protein Relation Miner tool by clicking here

3. Image capture QC tool

Appropriate scanning of your 2D gels can have a greater impact on the outcome of your image analysis as you might think.

To help you check the quality of your image capture step, prior to committing time and money on the analysis, we have developed a small QC tool that scans your images for the following:

• image size
• image format
• greyscale
• bit depth
• dynamic range
• level of saturation
• intensity level
• grey-level span

If your images don’t pass any of these checks, you will be alerted to it, together with a message on possible consequences and a suggestion for how to improve it.

The image capture QC tool has been integrated into the REDFIN 2D gel image analysis software, but can be accessed by anyone for free simply by downloading REDFIN for free here.

More detailed instructions on how to check the quality of your scanning procedure can be found on Image Capture QC page.

As usual, if you have any questions simply send them to support@ludesi.com.

Filed under: News, Tips and Tricks , Quality assurance, scanning

New in REDFIN: Wizard for adding and warping pick gel images

The picking icon in the REDFIN 2D gel image analysis software (as indicated by the red arrow)

In some experimental designs the gel you are picking spots from for protein identification will not be one of the gels used for image and data analysis. Mostly, this will be the case when the stain you are using is not compatible with, or optimal for, downstream mass spectrometry.

In those cases a designated “pick gel” is run.

This pick gel needs to be matched into the analysis project, so that interesting spot coordinates identified during image analysis can be transferred to the pick gel for subsequent spot excision.

But of course, you know all this.

What is important to you, is to have an easy way in the software to do it!

And that’s where we come in. With the new pick gel wizard in REDFIN we hope to have achieved just that.

Essentially, the pick gel wizard guides you through the following steps:

Step 1: tell REDFIN you would like to pick from a designated pick gel

Step 2: upload the pick gel image(s)

Step 3: Align the pick gel to one of the analytical gels via simplified image warping

Step 4: Export the picking coordinates for your spot cutting robot

Done!

And regardless if you did the image analysis yourself using Solo or requested a Basic or Pro analysis service, the adding and warping of pick gels is of course completely free.

We hope you enjoy using the picking wizard in REDFIN – we for one think it’s a pretty neat little addition to the software!

Filed under: New features in REDFIN , picking

Ludesi CEO talks at Quality Control in Proteomics Workshop

Photo of the main conference room taken during a switch of speakers in the plenary session.

From the 25th to the 27th of November the Quality Control in Proteomics Workshop took place in Hinxton, UK, as part of the ESF Frontiers of Functional Genomics Workshops. Organized by Lennart Martens and Henning Hermjakob from the EBI, the workshops main objective was to assemble a critical mass of representatives from the academic community, from industry (pharma, biotech start-ups, and consumables vendors), and from key scientific journals to discuss quality control (QC) strategies in proteomics.

The QC of data from different instruments and software is vitally important to ensure that what we are seeing is “real” and comparable to similar experiments. Too often we innovate and develop new instruments or workflows and forget to thoroughly validate that the output is correct, complete, and reproducible.

The proteomics community has only recently begun to adopt quality control of the different steps in the complex workflows employed when analysing a sample. As a result, efforts towards QC are currently specific to individual laboratories, resulting in widely divergent and incomparable strategies to verify the operational status of the instrumentation and analysis steps.

Needless to say that this workshop not only addressed this obvious weak-point in proteomics research today, but also represents a much-welcomed and exciting initiative from the community.

As a spotlight on 2D gel-based proteomics, Ludesi’s CEO Ola Forsstrom-Olsson was invited to speak about QC of 2D gel image analysis data. Apart from outlining the need for QC in this area, his talk focused on the new Gel IQ tool – a freely available tool that allows researchers to assess the quality of their data. The official report on the workshop nicely summarizes his talk:

“Dr. Ola Forsstrom-Olsson, from Ludesi, Sweden, presented a highly interesting, freely available application developed by his company to allow any user to perform a semi-automated quality control on their 2D gel image analysis. The software strikes a careful balance between the necessity to automatically call and match gel spots (due to the sheer amount of spots that need to be processed) and the need for manual validation of these automatic assignments for QC purposes. The software does this by first asking the user to specify a number of spots to evaluate manually. Subsequently, that number of spots will be randomly selected from the data, and will be shown in detail to the user. For each spot, the user has to grade the quality of the assignment, with the tool automatically progressing to subsequent spots. As soon as the manual validation quota is reached, the tool outputs the quality metrics, including a ‘combined correctness’ score.”

The development of free tools, such as Gel IQ, is vital to help scientists successfully QC their experiments and we’re happy to report that Gel IQ has so far been extremely well received by the community.

Gel IQ is freely downloadable at www.ludesi.com/free-tools and we will make sure to report more on it in the weeks to come!

Filed under: News , Gel IQ, optimize image analysiss results, Quality assurance

NEW: Handy cheat sheet of all REDFIN features now available!

 

You know what its like. You’re working with a software and are wondering if it can actually perform a certain task.

How do you go about finding out if it has that feature?

You might just start clicking around the software in the hope to stumble across it.

You might bite the bullet and start digging in manuals.

You might email support or simply Google for it. After all, Google has worked magic for you before…

Well, now we are going to make it very easy for you should you ever be wondering about a specific feature in REDFIN.

Introducing the REDFIN cheat sheet! A comprehensive list of all features and where to find them.

So if you are evaluating REDFIN, working with REDFIN, or simply curious about it, we invite you to take a peek at this list.

You might be surprised at all the things you can do…

Take a look at the REDFIN cheat sheet

Filed under: Tips and Tricks

Q: How does REDFIN normalize DIGE projects?

Ever wanted to know the nitty gritty of what happens behind the scenes in REDFIN?

Well, if the DIGE normalization procedure in REDFIN has been one of those things you’ve always wanted to know more about, then I dare say you’re in for a treat…

Ok, here goes.

Gaia: “Those rats aren’t normal. I suspect foul play.”

Captain Planet and the Planeteers” (1990)

Normalization is the process of making these spot volumes comparable between gel images in the face of technical differences in staining, scanning, sample volume, and so on.

In projects that use a DIGE methodology, REDFIN applies a two-step normalization procedure.

Step 1 normalizes all spots within a DIGE gel using a method of normalization that works with gel pairs. The algorithm computes a normalization factor for each of the images obtained from that particular gel and uses it to normalize the spot volumes across all three images:

•    For each image pair that has been matched, all matches between the two images are extracted. The top 50% matches, based on the spot volumes, are kept.
•    A spot volume ratio is calculated between each kept spot pair match. A pair-wise normalization factor between the images is computed by taking the median of these ratios. This ensures robustness and accuracy even if the project contains up to 50% regulated spot volumes.
•    Each image normalization factor is computed by optimizing an over-determined equation system, resulting from the pair-wise normalization factors.
•    Finally, the spot volumes in each image are multiplied with the corresponding image normalization factor.

Step 2 normalizes all spots between the DIGE gels.

•    An average internal standard is created using the normalized spot volumes (from step 1) of all internal standards.
•    For each protein in each gel a normalization factor is calculated as: spot volume in the average internal standard divided by the corresponding spot volume of the internal standard in that gel.
•    Every spot volume in every image is then multiplied by its normalization factor.

Professor Sharp: “Wanna bet? Scarab used a simple matter transducer for the transformation. It’ll be easy to reverse. All we have to do is have a fully charged, sonic-specific bionic being commit tactile energy transference.”

“Bionic Six” (1987)

In a data transformation step, the spot volumes are standardized by calculating the ratio between the spot volume in each image and the volume in the internal standard. These standardized values are log-transformed, and the transformed values are used in subsequent statistical tests.

However, for direct volume comparisons or Fold Change calculations, the original (normalized) spot volumes from each image are still used.

Everything crystal clear now? Awesome.

Filed under: 2DE Knowledge Base , internal standard, normalization, statistics, volume calculation

The first of the new REDFIN manuals available now!

New and interactive technologies are great, no question about that.

But lets admit it, sometimes it is nice to be able to print something out and read it the good old fashioned way. To touch the paper, scribble notes on the side and highlight the important passages.

That’s why we decided to create some good old printer friendly manuals for REDFIN in addition to the other more interactive support material we provide.

To make it easier to find the relevant sections, we have split them up into distinct chapters, which are listed on the manuals page on our website.

Also, within each chapter there are sub-categories that allow you to jump right to the part you are looking for.

And just because we’re creating some nice printer-friendly, old-school manuals doesn’t mean we’re going to churn out an incomprehensible, bore-you-to-tears novel… no mister! We want you to have the same mind-blowing, awesome experience with our manuals that you have with our software products!

Well, ok, that might be asking for a little too much, but hey, we’ll do our best to make them as enjoyable as manuals can get.

So without further ado, we present to you the first chapters of the REDFIN manual:

Just click on the image below to jump right over to the list of chapters.

More chapters are being written as we speak and will be added to this page shortly. We’re also planning on creating one big PDF document that contains all the separate chapters in one handy document.

So sit tight, good things are coming your way…

Filed under: News

How to export your 2D gel data from REDFIN: Excel export

REDFIN basically offers you four ways of exporting your 2D gel image analysis results.

1. Exporting for picking

2. Exporting to a PDF report

3. Exporting to an Excel spreadsheet

4. Exporting the raw data

In this post we will focus on options 3 and 4, which are probably most attractive to you if you are intending to process the data further. This may include creating more elaborate, user-defined graphs, applying custom-made algorithms, or running more specific statistical analyses.

Depending on if you would like to export all spot volumes in the project or only selected spot data, you should choose between the export option on the start page (exporting the raw data), or the Export To Excel option in the results view.

Let’s look at those two in more detail.

Exporting the raw data

On your REDFIN start page you will see several different project specific actions listed on the right side of every analyzed project. One of these actions is “Export” and indicated by a white arrow in a orange circle.

The red box marks the location of the Export button on the REDFIN start page

For any project that you wish to export the analysis results for you simply click this button and choose if you want to export the data with or without images. A compressed .zip file will be saved to your computer.

When extracting the files you will find one spreadsheet named RawSpotData. This file contains all spot data, including position, border, and normalized volume for each spot in each gel.

In addition, there is a file called SpotVolumeMatrix. This contains only the normalized volumes – arranged in a grid versus each protein ID. This file is more suitable for quick plotting and comparing of volumes for each protein.

If you ran a DIGE experiment, these files will also contain the spot volumes of the cy2 internal standards.

Exporting to Excel from within the Results View

In most 2D gel image analysis workflows you will not want to export the entire data set after you are done finding proteins of interest. Instead, you will probably want to export only those protein ID’s that you deemed significant in one way or another.

The export to Excel option in the Results View will allow you to do just that.

After selecting the comparison you are interested in, filter the list until only proteins of interest are left (although you can of course export the entire list without filtering, if you would want that).

Just underneath the first comparison tab you will see how many spot ID’s are left in the list after filtering.

Remember that if you have star rated spots, you need to make sure to also filter on the star property in order to only export the star rated spots.

When you are ready to export the contents of the list simply click on the little Excel icon located in the top right of the screen.

After choosing where you would like to save the generated file, REDFIN will automatically start exporting all the values that are currently present in the list to an Excel spreadsheet.

The spreadsheet is already pre-formatted, and not only contains general information about the experiment, such as experiment name, comparison, groups, and filter settings used, but also statistics and individual spot normalized spot volumes.

Remember, that the main difference between exporting from that REDFIN start page and exporting from the REDFIN results view, is that exporting from the start page provides you with all the spot volumes from all the gel images in the project, whereas exporting from within the results only focuses on the spot volumes of a (probably) filtered list within a selected comparison.

If you are unsure about anything, don’t hesitate to contact us directly at support@ludesi.com.

Filed under: How to's in REDFIN , export data to excel

New Feature in REDFIN: Easy Image Inverting

Does the following image look familiar to you?

Sometimes image capture of your 2D gels results in an image with inverted spot intensities.

Although REDFIN is able to handle inverted 2D gel images, some of you wanted the ability to invert those images before proceeding down the analysis workflow chain.

As we recently added image editing functionality into REDFIN, it was pretty straightforward for us to also add a tool for inverting your images.

Now when you enter the REDFIN analysis workflow you will see a button on the edit image step that does just that.

As always, the image manipulation carried out in REDFIN is for visual purposes only and will not alter the image itself, thus not affecting the actual analysis.

Make sure to keep the feedback coming (the good and the bad) so that we can continue creating tools that are just perfect for the job at hand.

Filed under: New features in REDFIN , Image editing

Visiting the HUPO 8th Annual World Congress in Toronto

Last week we greatly enjoyed taking part at the HUPO meeting in Toronto.  For those of you unfamiliar with the Human Proteome Organisation (HUPO), it can be described in a nutshell as aiming to foster international proteomic initiatives to better understand human disease.

Since it’s launch February 2001, HUPO has been organizing world congresses every year and lucky for us at Ludesi, this means we get to jet-set to exciting cities such as Seoul and Amsterdam, and meet some of the leading researchers in the field. As always, we greatly enjoyed meeting old as well as new faces and hearing about whats new and what’s hot in the world of proteomics.

Probably as a result of the financial crisis, this years meeting in Toronto was slightly smaller than usual, but still well enough attended to ensure you will never be able to meet and see everyone/everything you would like to.

The talks and posters provided us with a great overview of the cutting-edge science currently being carried out in proteomics and taken together with the stimulating discussions we had, we have returned to Sweden with lots of great ideas for REDFIN and Ludesi in general.

Unfortunately, the organizers failed to schedule specific poster sessions this year, which meant it was difficult for the presenters of posters to interact with those interested to discuss their research further. Lets hope this gets rectified in next years HUPO taking place in wonderful Sidney!

G’day mate! Looking forward to being there!

Otherwise we’d like to thank everyone involved for making it such an enjoyable event!

Filed under: News, Random Ramblings