The software is provided without charge and can be downloaded from the Downloads page.
Yes, GenomeStudio is supported for Windows XP, Vista and Windows 7 (see Computing Requirements http://support.illumina.com/array/array_software/genomestudio/computing_requirements.ilmn).
As of July 2016, unique GenomeStudio Software 2011.1 license keys have been discontinued. License keys for each of the GenomeStudio 2011.1 modules are included in a text file with the software installer download on the Downloads page without charge.
With GenomeStudio software open, go to the Help menu and select About. The About screen includes GenomeStudio software version information.
The table below includes Illumina’s minimum hardware recommendations to run GenomeStudio software.
|CPU Speed||Intel Celeron Duo or faster|
|Memory Size||8 GB or more|
|Hard Drive||100 GB or larger|
|Video Display||1,280 x 1,024|
|Operating System||Windows XP, Vista, or Windows 7|
|Specific OS Requirements||Microsoft .NET Framework 3.5|
|Network Connection||1 GbE or faster|
You should consider density, physical spacing, and Minor Allele Frequency (MAF). Loci with high MAF (~ 0.5) may be more informative than rare polymorphisms for this type of analysis. The control set must match the test sample population (MAF). You must have control samples with minimal amounts of chromosomal aberrations.
Please refer to our technical note entitled “TOP/BOT” Strand and “A/B” Allele (PDF).
See Chapter 5 of the GenomeStudio 2008.1 Framework User Guide, available on iCom and in the GenomeStudio Portal.
The Diff Score is a transformation of the p-value that provides directionality to the p-value based on the difference between the average signal in the reference group vs. the comparison group. The formula is: DiffScore = 10*sgn(µcond-µref)*log10p; For a p-value of 0.05, DiffScore = ± 13; For a p-value of 0.01, DiffScore = ± 22; For a p-value of 0.001, DiffScore = ± 33 The p-value column is hidden by default. To display this column, use the Column Chooser.
Yes, Illumina data is compatible with Bioconductor, a collection of R packages developed by researchers around the world and distributed for free.
Filter the genes using the Detection p-value. Setting detection at .99 (p value <0.01) means that there is a 1% false positive rate.
Yes, please download the GenomeStudio 2011.1 installer from the Illumina website. It is sufficient to install the GenomeStudio Framework by clicking the respective box in the install wizard, which does not require a license key. It is not required to install the GenomeStudio Genotyping Module on the same computer on which the PC Module is installed. However, the polyploid workflow does require generating a genotyping project in the GenomeStudio Genotyping Module prior to taking the data to the PC module for polyploidy clustering.
No, the PC module is a standalone software which does not require a license key.
The PC Module has the same computing requirements as other GenomeStudio Microarray modules listed here.
Illumina does not provide recommendations for downstream analysis outside of GenomeStudio.
No, it is not possible to generate a new project in the PC Module directly from idats. The polyploid workflow requires to first generate a genotyping project in the GenomeStudio Genotyping Module from the idats. The genotyping project (.bsc) can then be opened in the PC Module for polyploidy clustering.
SNPs are only clustered for samples selected in the Samples Table (marked in blue). If no samples are selected in the Samples Table, SNPs are clustered for all samples in the Samples Table (except non-excluded samples). Thus, if you wish to cluster SNPs for all your non-excluded samples please make sure that no samples are selected in the Samples Table at the time of clustering (e.g. by clicking onto an area in the SNP graph).
Minimum Number of Points in a Cluster, Cluster Distance, and Maximum Number of Clusters in the SNP Table, which can be found in the Clustering Options dialog box.
No, you can also cluster by defining #clusters, if known based on the biology of your samples.
Cluster distance specifies the maximum distance that samples can be away from each other and still considered part of the same cluster. Increasing cluster distance will result in fewer clusters that are larger in size, while decreasing cluster distance will result in more clusters which are smaller in size. A cluster distance of 0.06 is typically a good starting point for initial clustering.
Data can be exported directly from the Samples Table, SNP Table, and Full Data Table for downstream analysis. Mark the columns and rows you wish to export and click the icon for "Export displayed data to file" to save selected table content in *.txt or *.csv format.
Yes, in the SNP graph, use the curser to draw a box around the samples you wish to manually edit, right-click and choose the cluster samples should be assigned to, or NC (no call) if you wish to remove samples from any clusters.
No, the PC Module performs cluster assignment, but does not call genotypes. This is because the assignment of genotypes polyploid species is highly dependent on the population and biology of the organism. Any downstream genotype assignment should be done with the biology and evolutionary history of the population taken into consideration.
No, a polyploid project (.pcm) can only be opened using the PC Module.
No, this is not an option in the PC Module.
This number can be any number different from 0, however we recommend that the Minimum Number of Points in Cluster is set to match the biology of your samples and size of your dataset. A general guideline is to set this number to 1-4% of the number of samples that are performing well in the data set.
No, you can use different algorithms and clustering options for different SNPs. The goal is to find optimal parameters for each SNP matching the biology of your samples.
OPTICS is an acronym for "Ordering Points to Identify Clustering Structure". It is a sub-algorithm of DBSCAN, developed to be more robust to changes in input parameters. This trait makes OPTICS more suited for initial clustering. DBSCAN is an acronym for "Density-based Spatial Clustering of Applications with Noise". This algorithm is more sensitive to initial input parameters such as cluster distance. DBSCAN is more suited for differentiating clusters that are very close together, and should typically applied to SNPs for which OPTICS does not yield satisfactory results.
No, the new settings will only be applied to any SNPs clustered after applying changes.
Samples can be evaluated and sorted by Poly Call Rate, Poly 10%, and Poly 50%. We recommend using the scatterplot function within the Samples Table to plot Poly 50% against Poly Call Rate to graphically visualize sample outliers.
Call Rate is carried over from the Samples Table in the GenomeStudio Genotyping Module in which the original genotyping project (.bsc) was created. Entries in the Call Rate column do not change when SNPs are clustered in the PC Module. In contrast, the Poly Call Rate is calculated from clustering SNPs in the PC Module and represents the percentage of SNPs for which a given sample was assigned to a cluster.
SNPs can be evaluated and sorted by Call Freq, # no calls, Poly 10%, and Poly 50%.
The PC Module is compatible with GenomeStudio Genotyping projects created from Infinium and GoldenGate genotyping assays run on the iScan/HiScan, BeadXpress and BeadArray Reader.
The GenomeStudio Polyploidy Clustering Module (PC Module) can identify clusters for samples where the standard diploid clustering algorithm is inappropriate or not useful, such as for polyploidy organisms like wheat and potato.