There are two types of license model for GeneSpring:
1) Desktop License
2) Enterprise/Workgroup License
 
Desktop License:
GeneSpring Desktop licenses can be divided into two categories :
a) Fixed / Standalone license
b) Floating / Concurrent license
 
Enterprise/Workgroup License:
Enterprise licenses can be divided into two categories :
i) Work Group Server (WG Server)
ii) Work Group Client (WG_Client)
GeneSpring Work Group Server/ Enterprise licenses are only available as fixed licenses.
 
GeneSpring Work Group Client can be further classified as:
a) Fixed / Standalone license
b) Floating / Concurrent license
 
Currently module specific licenses are available for GeneSpring (WG Client or Desktop Client) software. There are four modules in GeneSpring which can be obtained separately. They are GeneSpring GX (Gene Expression), GeneSpring MPP (Mass Profiler Professional), GeneSpring NGS (Next Generation Sequencing) and GeneSpring PA (Pathway Architect).

A GeneSpring fixed license is system specific. This type of license can only be activated on individual machines, and cannot be transferred to other machines without being surrendered on the previous machine first.

A floating license / concurrent license allows multiple users to share the use of an application. A single floating license can be used by a number of concurrent users. The Floating License Server holds the license and serves licenses to the users based on availability. The number of concurrent keys has to be specified at the time of purchase. This number determines the maximum number of GeneSpring applications that can be run simultaneously.
 
For example, if you have purchased a floating license with two concurrent keys, GeneSpring can be installed on multiple systems (more than two) but GeneSpring can only be used on two machines at a time.

A fixed license is specific for a single machine and can be accessed by a single user at any given time, whereas a floating/concurrent license can be used by multiple users at a time with the help of concurrent licenses (see Q3.).

If multiple users want to use GeneSpring with a single license, then your organisation can purchase a GeneSpring desktop floating/concurrent license. In this case, a single license with a number of concurrent keys specified by you will be issued. The number of concurrent keys determines how many users are able to use GeneSpring at the same time. This license needs to be activated through the Floating License Server application, which serves licenses to the client installations and controls the number of users that can use GeneSpring simultaneously, based on the number of concurrent keys that were purchased with the license.
 
To activate the GeneSpring client software, the user needs to provide the IP address of the machine where the Floating License Server has been installed. This will assign them one concurrent key from the number of concurrent keys available at the Floating License Server. If another user would like to start GeneSpring after all the concurrent keys have already been assigned, an existing user would have to shut down GeneSpring for the new user to be able to start GeneSpring.

Please visit the GeneSpring support portal at http://genespring-support.com.
 
Select the ‘Request Free Trial’ option and you will be asked to register to download the free trial if you have not registered already.
If you are already registered, please log into the portal to download the software and request the trial license following these instructions:

1. Review the System Requirements.
2. Download GeneSpring Software.
3. Request 7 day trial License.

You will be asked to answer certain questions before we can provide a trial license. Submit the answers and you will be sent an email containing your trial license.

You can work with both GeneSpring GX 7.3 and GeneSpring 12.x simultaneously on the same computer if you have separate licenses for each version.

It is not possible to activate GeneSpring 12.x using a GeneSpring 7.3 license key. To activate GeneSpring 12.x you require a new valid 'Order ID'.

You cannot use one Order ID to activate two instances of GeneSpring.
 
To activate another instance of GeneSpring on a virtual machine which is on the same machine, using the same Order ID, you need to 'Surrender' the license/Order ID from the first instance. Then, use the same license to activate GeneSpring on the virtual machine (To surrender the Order ID: Go to Help -> License Manager -> Surrender).
 
When you want to switch back, you need to surrender the Order ID again.

GeneSpring Workgroup streamlines Multi-Omics data management at large and multi-campus organizations, providing server-side data analysis and secure archiving. It provides a secure repository for complete data analysis, which can be shared among users, whenever required.
 
When there is a large number of users and important data needs to be used in the analysis to-and-fro, it is recommended to use GeneSpring Workgroup, which allows server management capabilities to the users, through which data integrity can be maintained.

Both WorkGroup and Floating License Server are server-based applications but they work in different ways.
 
WorkGroup is used to keep all your data secure and can be shared among authorized WorkGroup users only.
 
The Floating License Server is used to share licenses for the GeneSpring client. The analysis done by multiple users cannot be shared, though it allows multiple users to share a single license with many concurrent keys at any given time. The Floating License Server can be used in conjunction with GeneSpring WorkGroup or GeneSpring Desktop versions, but WorkGroup is also a standalone application.

GeneSpring WG_Client Fixed license is used on a single machine at a time. It is machine specific and gets locked with the machine on which it is activated and cannot be transferred to another machine.
GeneSpring WG_Client Floating License on the other hand is not machine specific and can be used on multiple machines simultaneously by connecting to the Floating License Server to be served an available license. The number of available licenses depends on the number of concurrent keys purchased with the floating license.

No, the license for GeneSpring WorkGroup is different from the license for the Floating License Server.

No, it is not mandatory to use the Floating License Server with GeneSpring WorkGroup. The Floating License Server is used when there are many users of a GeneSpring client and most of them want to use the software at the same time.

This error appears if you are using the same Order ID to activate GeneSpring on two different systems.
GeneSpring has the 'Surrender' feature which is useful to transfer the Order ID from one system to another. To surrender an Order ID follow the steps below:

1. Click Help in the main menu.
2. Select License Manager.
3. Click Surrender.
4. Click OK.

The 'License has been surrendered successfully' message comes up. Now the same Order ID can be used on another system.

Please try the following instructions:

1. Go to GeneSpring installation directory\app\msvc_redist\
2. Run the following executable vcredist_86.ext (for 32 bit) vcredist_64.ext (for 64 bit)
3. Delete all files in this folder: \bin\license\
4. Launch GeneSpring.

If you are still unable to launch GeneSpring, please send the following files to GeneSpring Support (informatics_support [at] agilent [dot] com):

• Recent log files from the 'logs' folder of the installation directory.
• The compressed (zipped) \bin\license folder.

These files will help us in identifying why the error has occurred.

You would encounter the Error 3007 due to an issue with the proxy or firewall settings of your system or if you are not connected to the internet.
 
In case the system is behind a proxy server, provide server details in the activation dialog box during activation. Check with your system administrator regarding your organisation's proxy settings.
 
Auto-activation is only possible when you are connected to Internet.
 
If the proxy or firewall settings are fine and your computer is connected to the internet but you are still unable to activate GeneSpring, then please follow the instructions below for Manual Activation:

1. Please open the link below in a computer which is connected to the internet: http://lcosgens.cos.agilent.com/gsLicense/MultipleActivateNew.html
2. Enter the Order ID/IDs and attach the manualActivation.txt file (this can be found under \bin\license folder of your GeneSpring installation directory) in the Activation File field.
3. Click Submit. You will receive one or more .lic files by email.
4. Copy these .lic files into the \bin\license folder.
5. Launch GeneSpring.

GeneSpring should be activated now. Please contact GeneSpring Support if the issue persists or if you would like assistance with manual activation.

Error 4015 appears, if the Floating License Server has stopped or the connection between the server and the client is disrupted (LAN or internet). Please note that, each time you reboot the server machine the Floating License Server has to be re-started.
To get the current status of the server (if it is a Windows machine), please follow the steps below:

1. Open a command prompt and cd to the directory where the Floating License Server is installed.
2. Run the command ./lmstat -c bin/license/strand.lic -f marray/ genespring
   Please check (in the Task Manager) if the two processes 'lmgrd.exe' and 'strand.exe' are running on the server machine to confirm that the Floating License Server has been started.
3. Once this is confirmed try to connect to the Floating License Server from the GeneSpring GX client.

The Floating License Server should be accessible through the network on the port used by FlexLM, which is between 27000 and 27010, by default.
If the server is installed on Linux or Mac, please refer to the Floating License Server administration details in the FloatingServer.pdf document in the Floating License Server installation directory.

Please find the file formats supported in GeneSpring application for different Gene expression analysis Experiment Types below:
Affymetrix Expression, Affymetrix Exon Expression, Affymetrix Splicing Experiment Type/Affymetrix copy Number, Affymetrix Association analysis- .CEL / .CHP file format
Illumina Single Color, Illumina Copy Number/Illumina Association Analysis Experiment Type - .txt file format
Agilent Single Color, Agilent Two Color and Agilent miRNA Experiment Type: .txt file format
Pathway Experiment - .txt, .tsv, .csv and .xls
RT-PCR Experiment Type - RQ 1.2, RQ 2.1, RQ 2.2 and RQ 2.3 formats of the ABI's 7900HT RT-PCR system
Generic Single Color and Generic Two Color Experiment Type: .txt, .tsv, .csv and .xls
Note: Here in generic experiment, the user has an option to select the Identifier and the Signal column based on preference, unlike the above mentioned Standard Experiment Types.

Affymetrix text and pivot files can be loaded in GeneSpring 12.x as standard data and is associated to the standard technologies.

A. GeneSpring supports Affymetrix CEL and CHP files as standard format.
The other file formats such as .txt, .xls, .tsv and .csv are not recognised a standard file formats from affymetrix, but can be imported into GeneSpring for analysis.
You could work with .xls file by ‘Creating a Custom Technology’. To create a custom technology, follow the steps below:
1. Go to Annotations in the Menu bar -> Create Technology -> Custom from File
2. After creating the custom technology, you could create the experiment under ‘Generic Single color’ Experiment Type.
For more details please refer Chapter 13 & 14 on ‘Analyzing Generic Single color/Two Color Expression Data’ from the GeneSpring Manual.

This error occurs when special characters appear anywhere within the file path of the input CEL files. The workaround to resolve this error is to place the CEL files in a directory that does not have any special characters in the file path.

It really depends on what kind of samples you are working with. Please find the benchmarking table for GeneSpring version in the table below:

Note: Benchmarking for copy number and Association analysis are not included here.

You could get this error for the following reasons:
Reason1:
This error could occur while creating the experiment, if the ‘Experiment type’ chosen does not match the data files. Please select the right Experiment type and proceed with the analysis.
Reason 2:
This error could also occur in case you are trying to import the data in an un-supported file format.
For Example: GeneSpring only supports the data files generated by Feature Extractor (FE) version 8.5 and later version. In case the data files generated by earlier versions of FE are imported, this error may occur. In this case you would need to bring the data files as custom data.
To work with custom data, create a custom technology before you load the samples into GeneSpring.
To create custom technology go to -> GeneSpring menu bar -> Annotations ->Create Technology -> Custom from File. For more details on custom technology creation, please refer the chapter 13 and 14 from GeneSpring manual.

GeneSpring supports the Agilent single color miRNA data files from Feature Extraction software, version 8.5 or later version.
In case the user has files in any other format, a Custom technology and a Generic experiment could be created in GeneSpring to perform miRNA analysis.

Yes, There are few standard Agilent miRNA technologies available on GeneSpring update server. Please download the approprite technology from GeneSpring update server before you try to load the data for analysis.
Please contact us for any specific technology you are working with which is not available on update server.

In GeneSpring, the AMADID number field and the Grid_Date fields are considered as unique identifiers for miRNA arrays.
The Grid_Date field gives information on the version of the design file that was used to extract the data during sample creation. This means that even if the AMADID number is same for the same sample (for example: 19118), if they were created using a different design file, then they will not be taken together for experiment creation.
If the data set includes files from different Grid_Dates, you can create a custom technology to analyze them together.
For more details on Custom or generic Single Color/Two Color data analysis, refer to the Chapter 13 and 14 in GeneSpring manual.

To load Affymetrix miRNA data files in txt, csv and xls format, create a Custom Technology ( Annotations-> Create Technology ->Custom from File). Then, import the files under 'Generic Single Color' experiment type.
To perform the 'Target Scan analysis', select the option 'TargetScan' in the Results Interpretations from Workflow Browser.

In GeneSpring, Affymetrix and Illumina data files are supported as standard formats.
Data files in other formats can be converted to the Standard Illumina format and imported into GeneSpring to perform the CNV analysis.
The mandatory columns to be present in the data file to create the technology are dbSNPID, Chromosome Name, Chromosome Position, CNV regions in the same order.
From the data file, GeneSpring directly uses the following values for each sample.
log R - Provides the log (base 2) ratio of the normalized R value for the SNP divided by the expected normalized R value.
BAF (B allele Frequency) Copy Number values and their confidences Genotype of the subject SNP for the sample along with the score.

In GeneSpring, currently it is not possible to merge multiple experiments to create a single experiment.
Create another experiment using all these 150 samples from three different experiment by selecting the Choose Samples option in the data loading step.
Note: Once the data files are imported into GeneSpring GX to create an experiment, the data files are converted into samples and would be stored in the database. If the Choose files option is selected again, then the sample is created the second time which utilizes twice the space in the database.
Sample probe profile file in GeneSpring export format will be supported by GeneSpring.

The possible reason for "Error: -1" in copy number analysis could be the presence of "space" in the sample name.
Yes, it would affect the analysis. For example, running copy number analysis would not generate any output. Hence, please remove "space" from sample name for the successful experiment creation.

GeneSpring currently supports only RQ 1.2, RQ 2.1 , RQ 2.2 and RQ 2.3 formats of the ABIs 7900HT RT-PCR data as a Standard format.
However, to work with SuperArray qRT-PCR data, you need to create a custom single color technology using the path below:
GeneSpring GX Menu Bar → Annotations → Create Technology → Custom From File
You could then import the data by creating an experiment by selecting the Experiment Type as Generic Single Color. Please specify 'Detector' column from the file as the identifier column.

GeneSpring supports the creation of GPR technology ( Annotations → Create Technology → From .gpr file) only for the two color GPR data.
The two color .GPR file used to create the technology should contain the following columns - ID, F635 Median - B635, F532 Median - B532, and Flags.
In the absence of the above specified columns, the error would be seen.

Yes, .GPR files could be imported into GeneSpring.
Please find the details below:
Two color array:
A) Two color .GPR files from Agilent standard array could be imported by selecting the “Agilent two color” as the experiment type in the ‘New Experiment’ window for the standard workflow.
B) Two color .GPR files from custom array could be imported by following the steps below:

1. Create GPR technology: The technology could be created using one of the files from, Annotations menu Create Technology From .gpr file Follow the wizard.
2. After creating the technology, you would have to import all the files by creating an Experiment from the Project menu New Experiment Select Experiment Type as “ Generic Two Color”

Single color array:
To import single color .GPR files, please create a custom technology (Annotations  Create Technology custom from file) followed by experiment creation from the Project menu New Experiment Select Experiment Type as “ Generic Single Color”

Currently, the option to add samples to an existing experiment is unavailable. To add a new sample into an experiment, create a new experiment by including that sample with the rest of the samples.

Samples can only be deleted by deleting the experiments associated with them.
Experiments can be deleted using the path below: GeneSpring menu bar -> Search -> Experiments -> In the search wizard select the experiments to be deleted -> Select the ‘Delete’ icon Note: Once the sample is deleted from all the associated experiments, those experiments cannot be accessed.

After experiment creation, the sample information can be found in ‘Sample Inspector’.
Use right click on the sample name in ‘Experiment Navigator’ and select ‘Inspect Sample’ option to launch the inspector.
The Attributes, Parameters and Associated files information is shown in this window.

The Import NCBI GEO Experiment option is available only when an experiment is active under a Project. Open a Project followed by an Experiment in GeneSpring for the data import.

To transfer the data from one machine to another machine, export the data as Project zips from GeneSpring GX 10.x/11.x and import it into latest version of GeneSpring. This could be done from GeneSpring menu bar --> Project --> Export project zip/Import project.
Copying the data folder from one machine to another machine does not allow the data transfer.

GeneSpring supports the data files generated from BeadStudio in GeneSpring format to create standard Illumina single color experiment.
One could export the results from BeadStudio into a variety of formats compatible with other commercially available analysis tools.
To work with Illumina files in GeneSpring, export the files in GeneSpring format. This could be done from Analysis --> Report --> Custom Report --> GeneSpring format.

The error ""No such file or directory " would occur if the row header in the data file has "/".
Hence, please replace "/" with "_" or with any non-special character to import the data into GeneSpring.
This should help you to import the data into GeneSpring.

"The system cannot find the path specified " would occur if the row header in the data file has "\" .
Please replace "\" with "-" to load the data in GeneSpring and create an experiment.
With these changes Genespring would recognize the files and import it to create an experiment.

Following characters are considered as special characters in the tool: ! * # ; ? \ / : " < > |

The error could come up if the technology was earlier created on the fly due to loss of internet connections. This could result in difference in number of rows in the technology created on fly and the one present on the server.

Agilent single Color: Percentile Shift
Agilent Two Color: No Normalization in Genespring
Affymetrix Expression: RMA (Summarization method)
Affymetrix Exon Expression: RMA-16 (summarization method)
Illumina Single Color: Percentile Shift
Agilent miRNA: Percentile Shift

RMA is chosen as the default summarization in the guided work flow because it is more popularly used as the default option, by the micro array community.

RMA considers only Perfect Matches and hence uses positive signal intensities for probe level normalization.
By not considering mismatches it reduces the noise.

The 75th percentile is a more robust intensity value to normalize the data. With any tissue that you are analyzing, there are a certain percentage of genes that are not expressed. Even if a gene is not expressed, a probe matching to that gene will still report an intensity value. These intensity values will most likely fall into the lower percentile ranking on the array. These values are considered noise and are less reliable. So, taking an intensity value of a higher percentile like 75th is taking a median of only the probes with reliable intensity values (taking median of only genes that are expressed).

The following are the order of steps in GeneSpring for percentile shift normalization:
1.Transforms the signal values to the log base
2.Arranges the log transformed signal values in increasing order.
3.Computes the rank of the required percentile (Pth percentile).
4.Now if the rank is an integer, then the Pth percentile would be the number with rank R.
In another scenario, when the rank is not an integer then the tool calculates the value using certain steps. Once the value corresponding to the Pth percentile is obtained , this value is subtracted from the corresponding log transformed signal values. This would give the normalized intensity value.

Normalization could be performed only while creating an experiment. If you would like to change the normalization settings, you would have to create a new experiment.

The IterPLIER differs from PLIER in the aspect that it does not use all the probes for summarization. It selects only the good probes and iteratively discards the bad probes.

RMA16 summarization algorithm is referred to as the addition of value16 to the expression values. This is done to attain variance stabilization.

In order to establish a hierarchy of gene confidence levels, the sources of input transcript annotations are partitioned into three types. From the highest to the lowest confidence, the types are labeled as Core, Extended, and Full.
Core: Core list comprises 17,800 transcript clusters from RefSeq and full-length GenBank mRNAs.,
Extended: The Extended list comprises 129k transcript clusters including cDNA transcripts, syntenic rat and mouse mRNA, and Ensembl, microRNA, Mitomap, Vegagene and VegaPseudogene annotations.
Full: The full list comprises 262k transcript clusters including ab-initio predictions from Geneid, Genscan, GENSCAN Suboptimal, Exoniphy, RNAgene, SgpGene and TWINSCAN.

As part of the pre-processing step of experiment creation, thresholding is performed, due to which the raw values less than ‘1’ are threshold to 1. This is the default setup in GeneSpring, but the user has the choice to threshold the raw values to any value.
The option to transform the values to ‘0.01’ is unavailable in current GeneSpring version.

The threshold values cannot be specified as the value less than 1 in the standard experiment but, can be changed in a Generic experiment. The user could create the custom technology followed by Generic experiment creation to be able to change the threshold value.

While creating an experiment for two color data, GeneSpring allows you to load the data files and select the dye swapped arrays.
Ratio computation for two color data is done as follows:

Samples without dye swap:

Cy5(test) / Cy3(control)

Samples with dye swap:

Cy3(test) / Cy5(control)

If you have multiple endogenous controls, their 'Ct values' are averaged (arithmetic). That value is then subtracted from target Ct values for normalization.

The term raw signal values used in the context of Agilent Two Color data refers to the linear data after thresholding and summarization for the individual channels (cy3 and cy5).
Summarization is performed by computing the geometric mean.
The term Normalized signal value refers to the data after ratio computation, log transformation and Baseline Transformation.
In GeneSpring, the sequence of events involved in the processing of the Agilent two color text data files is: Thresholding → Summarization → dye swap → ratio computation → log transformation → Baseline Transformation.

In GeneSpring, the intensity values post the pre-processing steps are displayed in the log base 2 values. These values are further used for the analysis.

For Exon arrays, the background subtraction is done on a pool of probes having similar GC content (which is not the case with expression arrays). This typically results in probe sets having small expression values leading to an unreliable estimate of the variance. To offset this, an adhoc value of 16 is added to the expression values of all the probe sets.

The reason for adding 16 is that it is generally considered a low enough number that it will provide the required stabilization effect without changing suppressing true signal values. 8 and 32 are other options that are commonly used. usually values smaller than 16 are due to noise and you could have values 8 and 16 causing a fold change of 2, purely due to noise.

Statistical analysis results would not change based on the Baseline transformation to median of all samples as the actual deviation between the conditions for the particular entity would not change and therefore there would not be any change in the P-values across all the experiments based on the baseline transformation. Baseline transformation provides the user better visualization when comparing the relation between two groups without affecting the downstream analysis.

Please follow the steps to disable and to select the other normalization methods.
1. Disable the "Perform Quantile Normalization" option under ToolsOptionsAffymetrix Exon Summarization AlgorithmsExon PLIER/Iter PLIERUn-Check 'Perform Quantile Normalization'.
2. Create the Exon Expression experiment in GeneSpring.
3. After getting the data in, export 'All Entities' from the right clickExport entity list option.
4. Import it back in as a Generic Experiment. (i.e. create a custom technology using the exported data) Please
Note: when you are importing data back into GX11, it is already in log scale, so while creating the generic experiment you should explicitly select the option "Please select if your data is in log scale" so that log transformation is not performed on the data again.
5.Once you have your data as a custom experiment, you can perform any of the normalization methods available for Generic single color data.

Thresholding the data to 1 is convert the values which are less than 1 to 1. This is done because a values less than 1 would give large negative value after log transformation.
 Now, any entity with the value 1 after log transformation would give a value of 0 in GeneSpring. However, when we threshold the value to 0, it would not give any value after log tranformation and hence empty boxes would be observed.
So, if would like to filter entities with missing value , you could threshold to 0 and then, go to Utilities and select “Remove entities with missing value”.

Please follow the steps below to import the pre-normalized data:
Create a custom technology with the data file from:
GeneSpring Menu Bar → Annotations → Create Technology → Custom From File
Once the technology is created, please create a new experiment with those files to import into GeneSPring.
While creating an experiment, please choose the Experiment type as 'Generic Single color'.
In step 2 of 4, please check the option 'Please select if your data is in log scale' and the Normalization algorithm as 'None'.
In step 4 of 4, choose the option 'Do not perform baseline transformation'.
Now, the experiment is created with the pre-normalized data.

To use the same parameter values for subsequent experiments please follow the steps below:
In the Experiment Grouping Window --> Save the parameters by clicking on 'Save experiment parameters to file' icon

In the new experiment --> Experiment Grouping --> Click on 'Load experiment parameters from file' icon to import it.

Changing the parameter values in the experiment grouping window will not change the results of previous analysis.
The project hierarchy will separate the two analysis from each other.

The concept of 'Multiple Interpretation Creation' will help you to follow different analysis steps in the same experiment.

The interpretation will have the information about the parameters included or excluded in the experiment and based on the interpretation selected the analysis will be done.

The parameters could be brought in from one experiment to the other by following the steps below:

1.In the 'Experiment grouping' window for Experiment 1 --> Select the 'Save Experiment parameters to file' icon (second icon) --> Save to the desired location.
2. In the 'Experiment grouping' window for Experiment 2 --> Select the 'Load Experiment parameters from file' icon (first icon)--> Select the parameter file saved from Experiment1 --> Parameters get imported into Experiment 2.

To see the gene expression in only one cell type, create an interpretation with the 'cell type' of interest and perform the further analysis.
Ex: Filter on expression, Statistical Analysis, Fold Change

The option of 'Add/Remove' samples is grayed out as it is not supported for a Generic single color or Generic two color experiment.

The maximum number of samples for which the correlation coefficient plot can be shown is 100. This is because it is a compute intensive operation.

In earlier versions of GeneSpring , only Cy3 channel values were being considered to show the correlation plot for two-color data. Currently we are considering the ratio between Cy3 and Cy5 channels. So, it is not an appropriate method of judging correlation between samples, since weightage needs to be given to both the channels. Hence, the correlation plot is unavailable in two-color Quality Control window in GeneSpring.

Filter on Parameters calculates the correlation between expression values and parameter values.
It requires a numerical parameter with which a profile is created and then correlated to profiles of the entities present in the selected Entity List.
The profile of the entities is based on their expression values accorded to them based on their interpretation.

With Affymetrix data, the Filter by Flags is not applicable if you are working with .CEL files and Summarization algorithm other than MAS 5.0.

With text files, please select the flag column during data import to use this feature.

The Filter by Flags functionality for Affymetrix data could be used when you are working with .CHP files. The CHP files contain the flag information.

If you are working with .CEL files then use MAS 5.0 summarization to generate the Flags.

There are two factors based on which the filtering is done here. The percentile cutoff and the filter criteria of in how many samples must a probe set have intensity value within the specified range. Together, these two factors will determine what kind of probe sets is eliminated.

Factor 1: Percentile cutoff

We try to set this percentile cutoff to only eliminate genes that are not expressed. What we are saying is that if an intensity value of a probe set is below the 20th percentile in that sample, the gene is probably not expressed in that sample. It is known that any given tissue, not all genes in the human genome is expressed. On average across different types of tissues, we can expect that 20% of the genes are not expressed. Therefore, you can expect that about 20% of the probe sets on any given genome-wide array (sample) have intensity values that represent noise (since they are not expressed).

Factor 2: Number of samples

If probe sets were filtered such that they must have values within the range (above 20th percentile) in all samples (or in both conditions), then there is a possibility of interesting genes being excluded. Thus, potentially interesting biological changes between experimental conditions could be missed. To decrease the chances of missing these changes, the stringency of the filter is set such that even if the gene is only expressed in one sample in the experiment, the probe set will pass the filter. But, this criterion could be changed by the user according to their interest.

Flags are attributes that denote the quality of the entities. Using these attribute values in GeneSpring we filter the genes.
These values are generated based on the feature quality on the chip, like signal saturation and signal uniformity.
The genes which are given low significant attribute in the data file would be marked as 'Absent' and high significant values would be marked as 'Present'.
These flags are generally specific to the technology or the array type used. Thus the experiment technology type, i.e., Agilent Single Color, Agilent Two color, Affymetrix Expression, Affymetrix Exon Expression, and Illumina Bead technology determine the flag notation.

This information can be viewed by selecting the Filter on Data files option under Quality Control.

 
This error indicates that some of the required library files are not present. To install the necessary library files, go to the app/msvc_redist folder in the GeneSpring installation directory and double-click the appropriate msvc_redist file for your system specifications:

• vcredist_x86 for a 32-bit system
• vcredist_x64 for a 64-bit system.

Accept the License Agreement by clicking Yes.
The missing libraries are installed. You need to restart GeneSpring for the changes to take effect.

Yes, genes in an experiment can be mapped to chromosomal location in Genome Browser of GeneSpring. The mapping is based on chromosome number, start and end locations.

Following are required for Genome Browser:
•Build information for the organism of your experiment – Build is information of the chromosomes present in the organism and their lengths
•Chromosome number, start and end position for the probes/genes in the technology of your experiment. - This information is required to show data in Genome Browser.

To run Genome Browser, please download the build for the organism of your experiment. To download a build go to “Annotations -> Annotation Manager -> List -> From server”. Select the Organism and build of your interest and download them and then try to run Genome Browser.

GeneSpring provides you with the option to create your organism and build in the tool.
 
Create Organism
•Go to “Annotations -> Annotations Manager -> Create”
•Select “New Organism”
•Enter Common name, Scientific name and Taxonomy ID
 
Create New Build
•Go to “Annotations -> Annotation Manager -> Click on the Organism of interest -> Create”
•Select “New Build”
•Enter a name, build source and browse for the file with chromosome name and length information.
•Click “ok”

Chromosome name and length without any header should be present in a file for creating a build. For example
chr1    24336437
chr2    35347543

GeneSpring supports .tsv,.txt and .gz files for a build creation.

You may contact GeneSpring support to obtain a file based update. After the file based update is obtained, please go to “Annotations -> Annotations Manager -> List -> From file -> Select the .update file”. It will list all the annotations present in the update file, select the interested ones and click update.

To delete an organism created from “Annotations -> Annotation Manager”, please go to the Annotations Manager -> Select the Organism -> Click Delete.

Yes, you can select a specific region in a chromosome in either of the following ways:
 
a. Enter the region of interest in the chromosomal coordinates
b. Browse through the chromosome : Below are the options to browse through the chromosome in Genome Browser:

1. Use zoom function from tool bar
2. Use double click to zoom in and shift+double click to zoom out.
3. Use shift + mouse drag to zoom in.

Yes, data from a specific region can be exported from Genome Browser in following two ways:

1. From spreadsheet:  Follow the steps below for the same:

• Select the region of interest
• Go to Spreadsheet
• Right-click on the spreadsheet and select Export as entity list/ Export as text.

2. From Data Track :  Right-click on track for export options.

To find a specific Gene or probe in Genome Browser, go to spreadsheet and use “Find” option. The selected entity will be highlighted in the spreadsheet as well as the tracks.

Data from different experiments can be plotted on Genome Browser. To view the data, drag and drop the entity lists of interest on Genome Browser, it will be added as a track and can be viewed along with the other existing tracks.

Yes, it is possible to view list associated values (p-value, Fold change, etc) on Genome Browser. Please follow the steps below:
 
• Right-click on the track of interest
• Go to Edit track properties
• The list associated value columns are visible as check boxes in the Edit track properties Dialog. Select the required data and it will be added in the same track as one more feature. Click ok.
 
List associated values are also shown in the spreadsheet.

Yes, it is possible to view raw data on Genome Browser using the steps below:

• Launch Genome Browser
• Drag and Drop the experiment
• Select the interpretation and samples or conditions
• Click ok
• Right-click on the data track
• Select “Edit track properties”
• Select “Raw” in region view
• Click ok

The mapping of probes in Genome Browser is done using chromosome number and location. The chromosome number is expected to be in alphanumeric (chr1) or only numeric characters. If the format is alphanumeric then all the alphabets should be lowercase. The error could occur if the chromosome number has uppercase in them.

The Genome Browser is launched on the organism of your experiment. Check the organism of your experiment to ensure that it is the same as the organism of the build.
 
To check the organism of an experiment, right-click on the experiment name and select “Inspect Technology”. You have the option to change the organism in the Technology Inspector window.

Yes, the builds will continue to work. The builds from previous version will be called as “Segments”.

Yes, you may export images in the following two ways:

1. Right-click on the track of interest -> Export as -> Image. This will export individual track.
2. Go to the Tool bar in Genome Browser -> Select “Export selected track as image” -> Select the tracks of interest -> Specific a folder to save images. This feature enables you to export one or more than one track together.

To change the sequence of tracks go to the “Reorder” icon in the icon bar. Following this, select the track of interest and arrange it in the order of preference using up or down arrow.

Merge icon is used to bring different tracks together. This option is highlighted when two data tracks are selected and both tracks have only one feature enabled.

Data distribution over all chromosomes can be obtained by editing track properties from Right-click operations. Go to Edit track properties -> Chromosome View -> Select feature of interest.
This will show the data for the selected chromosome in Genome browser area. To view all the chromosomes together, go to “Chromosome tab” on the left of Genome Browser.
Similar is the case if you wish to view data for a particular feature for the whole genome. Right-click on the track of interest and select Edit track properties. Go to Genome View and select the required feature and click ok. It will enable this feature in Genome View.

Yes, annotation information present in a file can be imported in GeneSpring. You may use any of the following methods:

1. Drag and Drop a file on Genome Browser: To use this feature, follow the steps below:

• Launch Genome Browser
• Drag and drop the file of interest
• Provide a name to the feature and select a template
• In the subsequent step, define the data type and the column types for each of the columns.

2. Add annotations from annotation manager: To use this feature, follow the steps below:

• Go to “Annotations -> Annotations Manager"
• Select the Organism and build
• Right-click on the build
• Select the annotation type of interest
• Import the file.

Please refer to GeneSpring manual for details on supported file formats.

To export a list of probes to eArray, right-click on the chosen entity list in the Experiment Navigator and select Export to eArray. This enables you to export 'Genomic Coordinates' or 'GenBank Accession' data depending on the experiment type (Expression, Target Enrichment, or RNA Enrichment).

Yes, you need to have an account and associated log in information for the eArray portal in order to submit a probe list.

Yes, it is possible to export either all or a selection of entities displayed in a pathway to eArray. To export the list, right-click the Pathway Viewer and select Export to eArray. In the Export to eArray dialog, choose whether you want to export all entities or only the selected entities and the experiment type (Expression or RNA Enrichment). When exporting pathway entities to eArray, only 'GenBank Accession' data can be exported.

The Export to eArray functionality in GeneSpring allows you to export a maximum of 10,000 genomic coordinates or GenBank Accession numbers.

In order to perform pathway analysis on any of your entity lists or selected entities in GeneSpring 12.0 you require:

• A license for the Pathway Architect module (please contact GeneSpring technical support at informatics_support [at] agilent [dot] com for more details)
• Generic and organism specific interaction databases for analysis with non-GPML pathways (available to download for a number of organisms in GeneSpring from Tools > Annotations > Update Pathway Interactions)
• Metabolite and organism specific BridgeDb databases (available to download for supported organisms in GeneSpring from Tools > Annotations > Update BridgeDb)
• And most importantly pathways. GeneSpring supports pathways from the WikiPathways portal, which you can download directly in GeneSpring from Tools > Import Pathways from WikiPathways. You can also download pathways from BioCyc directly in GeneSpring from Tools > Import Pathways from BioCyc. In addition you can import pathways in the GPML, BioPAX (Level 2 and 3), and Text format.

If you downloaded any Interaction Databases in a previous version of GeneSpring, we recommend that you update them. All the Interaction Databases have been updated to include more entities and relations along with updated annotations for existing entities and relations. Obsolete entities and relations were removed. From GeneSpring 12.0 onwards, Interaction Databases are updated on a regular basis to remain up-to-date with scientific findings published through PubMed. Once such an update becomes available you will be notified the next time you start GeneSpring.

Existing pathways will not be affected during the update. Once the Interaction Databases are updated, the Update Pathways dialog will allow you to update your existing pathways by removing obsolete entities or relations and updating entities in case the name was changed.

If you are planning to use non-GPML pathways, you should have enough disk space for downloading the Interaction Databases. You can check the amount of disk space required from Annotations > Update Pathway Interactions > From Agilent Server. The amount of disk space required will be approximately three times mentioned in the update window. For example, around 7 GB of space will be required for the Human Interaction Database.

From GeneSpring 12.0 onwards, BridgeDb databases are used to match pathway entities with entities in the experiment when a direct match based on the same annotation is not possible. The BridgeDb algorithm allows GeneSpring to map entities if only differing annotations (e.g. Entrez Gene ID, Unigene ID) are available.

In the absence of a BridgeDb database for your organism, please contact technical support at informatics_support [at] agilent [dot] com.

To import pathways from WikiPathways, follow these steps:

• Go to Tools > Import pathways from WikiPathways
• Select the organism for which you wish to download the pathways
• The drop-down list consists of the organisms for which pathways are available for download from the WikiPathways portal (www.wikipathways.org)

If you have downloaded pathways from WikiPathways in the GPML format outside GeneSpring, then you can import these pathways by following these steps:

• Go to Tools > Import pathways from file > GPML
• Browse for the pathway files and select WikiPathways as Provider
• Select the associated organism using Set Organism

All imported pathways are stored in a central pathway database that can be searched via Search > Pathways.

To import pathways from BioCyc (www.biocyc.org) in GeneSpring, follow these steps:

• Go to Tools > Import Pathways from BioCyc > From Agilent Server.
• Select the desired organisms in the Automatic Software Update dialog that opens. Click Update.
• An Information dialog informs you of the size requirements for downloading all the pathways for the selected organisms. Click OK.
• Another Information dialog confirms when the download is complete. Click OK.

If you are not able to import pathways from the Agilent Server (for example because of an internet connectivity issue), you can request GeneSpring support to email you an update file for the organisms of your choice and select Tools > Import Pathways from BioCyc > From Update File... instead. You have to save this file to your computer and point to it in the Please Select A .update File dialog. The remaining steps are the same as described above.
 
All imported pathways are stored in a central pathway database that can be searched via Search > Pathways.

GeneSpring supports the import of pathways from the WikiPathways portal (directly in GeneSpring or as GPML files that were previously downloaded from the portal, also see Q1. How can I import pathways from WikiPathways in GeneSpring?). You can also import pathways from BioCyc directly in GeneSpring (see Q2. How can I import pathways from BioCyc in GeneSpring?). In addition, you can import pathway files in the BioPAX (Level 2 and Level 3, *.owl) , GPML (*.gpml), and Text (*.txt) format.

Every time you update an Interaction Database in GeneSpring, the Update Pathways dialog opens automatically. This dialog allows you to choose which of the pathways that you previously imported into GeneSpring (non-GPML format only) you would like to update or delete based on the new information recorded in the updated Interaction Database. For each pathway the Update Pathways dialog displays updated entities and obsolete entities. If you want to update pathways at a later date, you can return to the Update Pathways dialog through Annotations > Update Pathways.

Yes, deleting a pathway in the Update Pathway dialog will delete the pathway from any experiment it is saved in, as it is permanently deleted from the GeneSpring database.

When importing pathways in the GPML format, GeneSpring identifies duplicate pathways based on pathway name, organism and pathway provider. If duplicate pathways are found, the Resolve Duplicates dialog gives you the choice to

• rename any of the pathways identified as duplicate and import them,
• overwrite the existing pathway with the new pathway,
• ignore duplicate pathways and not import them at all.

Only GPML and BioPax Level 3 pathways can be imported into GeneSpring without the organism’s Interaction Database. However, to import and work with any other file format, the common as well as the organism specific Interaction Databases are required.

To download KEGG pathways, please go to GeneSpring Tools -> Import Pathways from KEGG ->From Agilent server.

No, KEGG pathways can only be imported into GeneSpring from the Agilent server or .update file.

Single Experiment Analysis provides an option to select the pathway source in Step 1 of the wizard-driven workflow. Select “KEGG” to limit your analysis to KEGG pathways.

To be able to work with KEGG pathways:
a. you should be working with GeneSpring 13.0 and
b. you should be a licensed user of KEGG.

A pathway node in KEGG pathway is grayed out if that entity is absent in the organism of your experiment.

Some nodes in KEGG pathways may represent multiple entities. For example, different isoforms of the protein, subunits of proteins, members of the same gene family, etc. . All entities under the node get selected when you select the node on the pathways.
Mouse over the node of interest to view all the entities under the node in the tooltip. You can also select the node to filter the heatmap below to limit it to only the entities represented by the node. Specific entities under the node can then be selected from the heatmap.

The annotation information on pathway nodes can be found in the Entity Properties dialog.
Double-click on the node to open the corresponding dialog.

Yes, you can select the desired annotations by using the “Properties Filter” drop-down icon in the Entity Properties dialog.

The annotation types in bold are the annotations that are supported for mapping pathway entities of the respective experiment type in GeneSpring.

From GeneSpring 12.0 onwards, Single Experiment Analysis (SEA) replaces the Find Significant Pathways (FSP) workflow step available in earlier versions. Compared to FSP, SEA is enhanced with some of the features that were introduced to enable Multi-Omic Analysis (MOA). SEA identifies matching pathways for the entities of one experiment, compared to two experiments in an MOA. But unlike in the previous FSP workflow, you can now choose a differing organism for pathway analysis from the organism associated with your chosen experiment and specify an experiment interpretation as well as preferred annotations. In addition, the new curated pathways options (WikiPathways and pathways in .gpml format) as well as the BioPAX, Hand created, NLP and MeSH options can also be selected as pathway sources for pathway analysis.

The Find Significant Pathways feature has been replaced with Single Experiment Analysis. Please refer to Q1. What is Single Experiment Analysis? for more details.

GeneSpring uses a so-called “column mark” for annotations during custom technology creation. If column marks were inappropriately assigned at that time then you may encounter this issue. Please refer to section 3.2.2 Update Technology Annotations in the GeneSpring user manual for more information.
If the column marks were selected correctly and your pathway analysis still results in no matching pathways, please contact GeneSpring support at informatics_support [at] agilent [dot] com for assistance.

Yes, you can change the p-value cut-off after saving the results of the analysis in the form of a pathway list at the end of the Single Experiment workflow. Filters are available for both p-value and number of matching entities in a filter panel, which is located under pathway list panel in the left bottom corner of the Pathway View of an open pathway list.

Yes, in Step 1 of 4 of the Single Experiment Analysis workflow, you can select what kinds of pathways (available for the chosen organism) are queried during Pathway Analysis depending on whether you would like to include only Curated pathways, or Literature Derived Networks, or both. You can even narrow down your selection based on the respective sources (WikiPathways, BioCyc, BioPAX, GPML, Hand created, and Legacy for Curated pathways; NLP and MeSH terms for Literature Derived Networks).

In GeneSpring 12.x, pathways that were imported or created in earlier versions of GeneSpring are referred to as Legacy pathways. This includes a set of 21 pathways that are packaged with your GeneSpring installation.

One of the features of Pathway Analysis in GeneSpring is that experiment data associated with matching entities between the pathway and the chosen entity list is displayed in the form of Heatstrips next to the entities in the pathway viewer. By selecting an interpretation, Heatstrips will display the data according to the experimental conditions specified in the selected interpretation.

A maximum of two experiments can be selected for Multi-Omic Analysis.

For running the Multi-Omic Analysis workflow you require:

• The two selected experiments present in the same project
• Pathways and/or Literature Derived Networks for the chosen pathway organism
• BridgeDb databases for metabolites and all the relevant organisms
• Annotations for the entities in the experiment
• Interaction Databases for all the relevant organisms, if you want to include non-GPML pathways in the analysis

Yes, you can custom save selected pathways in Step 3 of 4 of the Multi-Omic Analysis workflow. The selected pathways are saved as a pathway list in a new MOA experiment, which is saved in the same project as the two input experiments.

The result of an MOA workflow is an MOA experiment, which is saved in open project. An MOA experiment contains the input entity lists that you selected during the MOA workflow and an object referred to as Pathway List. A Pathway List resulting from an MOA workflow contains all the pathways (that were previously imported into GeneSpring) of the selected pathway type and organism that were chosen in Step 1 of 4 of the MOA workflow. When you complete the MOA workflow, the Pathway List opens in the GeneSpring Desktop in the Pathway View.

The Pathway View consists of:

• the Pathway View Toolbar – this toolbar contains additional icons to the main menu that are specific to the functionality of the Pathway View, for example changing an interpretation or entity list.
• the Pathway List Panel -a table illustrating the number of matching entities with the chosen entity lists and associated p-values (not available for Metabolomics experiments). You can select the pathway you would like to visualize in the Pathway Viewer here.
• the Pathway Viewer – the selected pathway (from the pathway list panel) is displayed in this area; experimental data associated with the matching entities is displayed here in the form of Heatstrips.
• the Filter Panel – using this panel you can filter the list of pathways in the pathway list panel by the number of matches with the chosen entity lists and associated p-values.
• the Heatmap – this table lists all the pathway entities and the experimental data for matching entities with the selected pathway in a Heatmap fashion. There is a separate table for each of the two input experiments.

Use the Filter Panel options to identify significant pathways for the chosen entity lists.

You can export a pathway list table in three different formats: Image, HTML, Text. Right-click the pathway list table at the top left of the Pathway View and select the desired option from the Export As submenu. Please note that exporting the table as an Image, or HTML only exports the visible pathway list panel area, while exporting it as a Text file exports the contents of the pathway list panel as a table.

You can create a Venn Diagram to illustrate common pathways. Select Pathway List from the Venn Diagram icon drop-down list   in the main toolbar, or select View > Venn Diagram > Pathway List from the main menu.

GeneSpring applies Homologene translation (for genes) for matching experiment entities with pathway entities when the selected pathway organism is different from the experiment organism.

There could be two reasons for this result:

1. GeneSpring could neither find direct matches (same annotation available for both experiment entities and pathway entities) nor indirect matches using the BridgeDb algorithm to map differing annotations.
   • To inspect available entities in your experiment, right-click the input entity list in the Experiment Navigator and select Inspect List. The Entity List Inspector that opens contains an additional column for each available annotation.
   • To inspect annotations for the pathway entities, right-click the pathway list in the Experiment Navigator and select Inspect Pathway List. Double-click the row corresponding to the pathway of interest in the Pathways spreadsheet to open a Pathway Inspector. Available annotations are listed in separate columns.
      
2. There are no matching entities between the input entity list and the pathways.
   • To see if there are any matching entities with an open pathway for this experiment, look at the corresponding Heatmap table. If that table contains data for any of the listed pathway entities then at least one of the entity lists in your experiment has matching entities with this pathway.
   • To see if another entity list in your experiment has matching entities with an open pathway, simply click on that entity list in the Experiment Navigator. Matching entities will appear highlighted by a light blue border in the Pathway Viewer. Or, to visualize matching entities more prominently, you can select a different entity list using the Choose another Entity List icon from the Pathway View Toolbar. Any matching entities between the open pathway and the new entity list will appear colored in yellow by default. However, the resulting changes from changing the entity list is not reflected in the pathway list panel and is not saved when closing the Pathway View for this pathway list.

Grey cells indicate missing values. The Heatmap table in the Pathway View shows lists all the pathway entities of the same type as that of the input experiment. However, data values are only shown for matching entities with the input experiment.

Yes, you can view data from a different group of conditions by clicking the Choose another Interpretation icon and selecting another interpretation. Please note that this selection and the associated changes in the Pathway Viewer and the Heatmap table are not saved when the pathway list is closed.

GeneSpring provides an option to view a Profile Plot of your genes of interest in a pathway. To use this feature, select the genes of interest either from the pathway viewer or the Heatmap table and then click on the Launch Profile Plot icon from the Pathway View Toolbar. A continuous (numerical) or non-continuous (categorical) plot is displayed in a new window based on the interpretation selected during the pathway analysis workflow.

By default, the Heatstrips displayed in the Pathway Viewer and in the Heatmap table are normalized signal values. To view raw signal values instead, follow these steps:

1. Right-click over the Pathway Viewer
2. Select Display Settings
3. In the Data tab of the Pathway Properties Dialog that opens, select Raw Signal Values from the Data Chooser drop-down list
4. Click OK

The Heatstrips in the Pathway Viewer and the Heatmap table now display the raw signal values for matching entities between the pathway and the experiment.
 

The height of a Heatstrip represents an entity’s signal/abundance value at the various experimental conditions.

Yes, you can still perform NLP Network Discovery if you create your own Interaction Database by importing pathway files (.owl) for that organism. Follow the steps below to create your organism and import relevant pathway files:

1. Create new pathway organism : Annotations > Create Pathway Organism.
2. Import BioPAX (Level 2) pathways: Go to Tools > Import Pathway from File > BioPAX
3. Select the pathway organism you created from the organism drop-down list in Step 2 of 2 of the Import BioPAX Files process.

You can now perform NLP Network Discovery in relation to your organism.

The entities and relations from WikiPathways do not add to GeneSpring’s Interaction Databases. Hence, these cannot be used for NLP Network Discovery.

Yes, GeneSpring allows you to run NLP Network Discovery on entities that were selected in the Pathway Viewer or the Heatmap table of an open pathway list. This workflow will result in a new pathway. The identified interactions will not be added to the existing pathway. To use this feature, follow these steps:

1. Select the pathway entities of interest in the Pathway Viewer
2. Right-click over the Pathway Viewer
3. Select NLP Network Discovery

When adding a new entity to a pathway with the Add entity icon, either while creating a new pathway or during one of the NLP Networks workflows, the only required property is 'Synonym'. GeneSpring uses this property to search the appropriate Interaction Databases for a match

If the entity already exists in one of the Interaction Databases, GeneSpring prevents you from adding the entity through this process. To add such an entity to the pathway, drag the symbol that represents the desired entity type in the Entity Legend into the Pathway Viewer and type the same term in the Search dialog that opens. Select the appropriate entity from the search results and click OK.

If GeneSpring does not find a match for the 'Synonym' property that you provided you can continue creating this new entity by adding as many properties as possible. For example, Entrez Gene ID, Unigene ID, and other annotations are particularly useful, as they are used for matching during Single Experiment or Multi-Omic Analysis and any of the NLP Networks workflows. The 'Synonym' property is not used for this purpose.

Yes, you can query such pathways. They are identified as Hand created pathways in Step 1 of 4 of an SEA or MOA and can be selected under Curated pathways.

No, it is not possible to make any modifications to an entity after it was added to the Interaction Database.

To find out if an entity is already present in an Interaction Database, drag the symbol that represents the desired entity type in the Entity Legend into the Pathway Viewer and type the term by which this entity is most commonly referred to in the Search dialog that opens. The search results will display all the matching entities GeneSpring found in the Interaction Databases.

If the search result contains the entity you would like to add to the pathway, select the corresponding row and click OK.

If the entity of interest is not present in the search result, leave the Search dialog and use the Add entity icon in the Pathway View Toolbar to create the entity with the information you have about this new entity.

The Color by Venn feature is used to differentiate entities in an open Profile Plot, Scatter Plot, or Cy3 vs Cy5 Plot based on the presence of these entities in the different regions of a Venn Diagram.

The Color by Venn option is available for Profile Plots, Scatter Plots, and Cy3 vs Cy5 Plots.

The Profile Plot will not change if none of the entities that it contains are present in the selected Venn Diagram.

To undo the effect of Color by Venn, relaunch the respective plot and its rendering will return to the original status.

Yes, the Color by Venn option will also work in this situation.

No, GeneSpring provides you with a list of all the open Venn Diagrams, from which you can choose only one for applying the Color by Venn option to any of your open Profile Plots, Scatter Plots, or Cy3 vs Cy5 Plots.

For version 12.5, the database management system for storing GeneSpring data (e.g. experiments, analysis results, annotations, pathway-related databases) was changed from MySQL to PostgreSQL. Therefore, all the existing data has to be migrated from the MySQL database to the PostgreSQL database before you can start working with GeneSpring again. Depending on the size of your data (for example if you have previously downloaded interaction databases of multiple organisms), this process can take several hours.

The information dialog guiding you through the update and migration process provides estimated size requirements and informs you if the available space in the GeneSpring installation directory is not sufficient. PostgreSQL migration involves copying the entire MySQL folder. The MySQL folder will remain untouched after migration. This means, if the MySQL folder occupies x GB space, you will need at least twice that amount (2x) plus some extra space, which varies, but is typically around 10% of the size of the original MySQL folder (10% of x). Therefore the total space requirement is approximately 2.1x.

There are a number of reasons why the PostgreSQL database would have failed to startup, which can depend on your system specifications:
 
1) All supported systems (Windows, Mac, or Linux): The GeneSpring PostgreSQL database uses a fixed port to run (port 5435). If any other application on your computer is using the same port at the time you started GeneSpring, the PostgreSQL database will not have been able to startup. You can resolve this issue by opening the following file in the GeneSpring installation directory in a plain text editor (like Wordpad):
GS_Installdir/app/PostgreSQL/data/postgresql.conf
In the file, use the Find function to go to the following phrase: "port = 5435" and change this number to 543x, where x is greater than 5. Save the file and launch GeneSpring again.

Note: Not all applications use fixed ports, but might randomly choose a free port to run. Or you might install another application that uses the same port as GeneSpring’s PostgreSQL database. Therefore, this issue can occur again at a later time, even if you have changed the port once. If this is the case, just repeat the instructions here to change the port again.
 
2) Mac or Linux machines: You might not have the required permissions to start the PostgreSQL database. For these types of machines, PostgreSQL requires the ‘700 file permission’. You can manually change the permission settings using the chmod command. In the Command Prompt, point to the ‘app’ folder in the GeneSpring installation directory and execute the following command: ‘chmod-R 700 PostgreSQL’. This will set the permissions for you to have read, write to, and execute permissions for the PostgreSQL folder. This process only has to be executed once. If this does not resolve the issue, try changing the port for the PostgreSQL database as described in 1).
 
3) Linux 64-bit operating systems only: In addition to the standard libraries, the PostgreSQL database requires the “ia32-libs” package to startup. Contact your system administrator to install the package or contact GeneSpring support. This process only has to be executed once. If this does not resolve the issue, try changing the port for the PostgreSQL database as described in 1).
 
If none of these options resolve the issue, please contact GeneSpring support for further assistance.

To transfer data from one installation of GeneSpring to another, any of the following methods could be used:
a) Project Export and Import: You may export individual projects from one installation of GeneSpring ( Project -> Export Project) and import in another ( Project -> Import Project).
b) Use Backup and Restore: If you wish to transfer all projects together, backup and restore function can be used. These functions are available under Tools in GeneSpring.

Yes, you can import projects that were exported from older versions of GeneSpring into GeneSpring 12.x.

Data from one installation of GeneSpring 12.x to another can be transferred. However, to access them, GeneSpring 12.x installation should be activated with the required license modules.

The default repository path in GeneSpring is <GeneSpring Installation Directory/app/>.

GeneSpring stores metadata in MySQL/PostgreSQL (depending on version 12 or later) database and files in data files folder that contains gxuser, gxmanager and gxworkgroup.
 
Access to data is provided by a combination of MySQL/PostgreSQL database and files.

Yes, GeneSpring provides you with a feature to select the data storage location of your choice. In GeneSpring 12.x, to make the required changes, go to “Tools -> Change Repository”. Specify a location of your choice in Repository path.
 
If you are working with GeneSpring 11.5.1 or earlier version then, go to “Tools -> Options -> Miscellaneous -> Repository path”.

Changing repository path would have the following effects:

1. If you are working with GeneSpring 11.5.1 or earlier version, change in repository would only store the data files in new storage location and not the database itself. Database is located in original GeneSpring installation directory. Movement of database is possible in GeneSpring 12.0 and later versions.
2. You will be able to access previous projects, provided the previous repository folders are present in their original locations.
3. All the new data files will be stored in the new repository path.

Please note: Database entries are always made in MySQL database. This is vital for access to data and its recovery (if required). Hence, it is highly recommended to not remove any folder from GeneSpring installation directory or the folders from new location.
 

Yes, GeneSpring 12.x provides the option to move MySQL database as well while changing the repository path. While trying to change the repository, user is prompted with a message to confirm if a change in MySQL database is also required.

In GeneSpring 12.0, the repository path information is shown in “Old repository path” section. To view the information, go to “Tools -> Change Repository”.

Experiment creation and all the following analysis requires a temporary folder (by default, this is created in GeneSpring installation directory  at  <GeneSpring Installation Directory>/app/tmp). It doesn’t change with change in Repository path. Hence, it is required to have some free space in the drive with GeneSpring installation. A lack of space in default directory could result in failure of experiment creation.

No, you also need to copy the MySQL Database. Copying folders is not advised. Please use “Export-Import or Backup-Restore functionality for the access to projects.

Yes, you could transfer entire data using Backup and Restore functionality. Follow the steps below for the same:
a) Go to Tools -> Backup repository -> Specify a location for tar file.
b) Go to Tools -> Restore Backup -> Select the .tar file created in previous step.

Following should be considered before trying Backup and Restore of data:
a) This function should be used across the same version of GeneSpring.
b) .tar file should be created on a file system without a size limitation. Do not use a FAT32 file system if the app folder size is greater than 4 GB.

It is recommended to consult GeneSpring Support (informatics_support [at] agilent [dot] com) before OS upgrade.
 
Backup and Restore will solve this issue. However, since there is no original filesystem to go back after your OS is upgraded, we strongly recommend to also perform the following:
 
a) Export important individual projects.
b) Keep a copy of the following:
           i) "app" folder from GeneSpring installation directory.
           ii) All previous repository data folders, if any.