Tutorial Data

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Tutorial data files

All data sets used in the tutorials are available from the download area of our site.

The file "tutorial_data.zip" contains the following files:

  • cardiogenomics.med.harvard.edu/ -Contains 10 individual MAS5/GCOS format data files.
  • webmatrix2_quantile_log2_dev1.2_mv0.exp -A geWorkbench "exp" format matrix file containing filtered, normalized data. This data originally derives from the file "webmatrix.exp", but one group of columns has been rearranged so that each condition (phenotype) is kept in one block (webmatrix2.exp).
  • NM_024426-Wilms.fasta -A Genbank nucleotide seqeuence file.
  • NP_077744-Wilms.fasta -A Genbank protein seqeuence file.
  • H1H5_HistoneDB_NHGRI.fasta -Contains H1 and H5 histone sequences from the NHGRI.
  • ClusterTree38_Sequences.fasta -Contains sequences derived from hierarchical clustering.
  • cluster_tree_12markers.csv -Contains a list of markers derived from hierarchical clustering.


About the cardiogenomics microarray dataset

These example MAS5 format data files were obtained from the following site at Harvard University:

http://cardiogenomics.med.harvard.edu/project-detail?project_id=229

A number of MAS5 format data files are available there.

The specific project is the "Belgium Dataset of Aortic Stenosis, Congestive Cardiomyopathy and Normal LV Function", and the data is downloadable from:

http://cardiogenomics.med.harvard.edu/groups/proj1/pages/download_Hs-belgium.html

An abstract describing the study that produced them is also available, at:

http://cardiogenomics.med.harvard.edu/groups/proj2/pages/Hs-belgium_home.html


Generation of the "webmatrix2_quantile_log2_dev1.2_mv0.exp" dataset.

The file "webmatrix2.exp", available in the Download area, contains results from 100 Affymetrix HG-U95Av2 chips containing B-cell samples from numerous different disease states (phenotypes). 12600 markers are represented. For use in the tutorials we normalized and filtered the data. The steps shown below are just an example of how filtering and normalization can be used, and each dataset should be handled according to the type of analysis being undertaken and its goals.

The dataset was created by the following steps:

  1. Normalization: Quantile normalization.
  2. Normalization: Log2 transformation.
  3. Filtering: Deviation filter with Deviation bound of 1.2.
  4. Filtering: Missing values filter with maximum number of missing arrays of 0.
  5. Finally, for convenience, the first marker, which is used to identify the type chip being used, was added back (it is filtered out above). This merely removes the needed to identify the chip type manually on loading.

The result of performing these steps is available as the file "webmatrix2_quantile_log2_dev1.2_mv0.exp", found in the tutorial data Download file "tutorial_data.zip".