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 Bcell-100.zip contains the file Bcell-100.exp, which is a geWorkbench data matrix format file containing 100 Bcell experiments using Affymetrix U95-Av2 chips. It contains the same data as the file "webmatrix2.exp" which has been used in the tutorials previously. The array groups have been given more descriptive names. The data has been processed using the Affymetrix MAS5 normalization routine. It comes from the lab of Dr. Ricardo Dalla-Favera at the Institute for Cancer Research at Columbia University. The 100 arrays represent B-cell experiments drawn from a variety of conditions, including cancerous and normal, germinal center and non-germinal center.


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.
  • cluster_tree_total_pearsons_84_markers.csv - Contains a list of 84 markers derived from hierarchical clustering of webmatrix2.
  • 640f84ClusterPearsonsSeqs.fasta - Contains FASTA sequences for 64 of the 84 markers in the list above.
  • cluster_tree_total_pearsons_64of84_markers.csv -Contains the marker set for the 64 sequences in the above set.

The following are from older examples being phased out.

  • ClusterTree38_Sequences.fasta -Contains sequences derived from hierarchical clustering (old example).
  • cluster_tree_12markers.csv -Contains a list of markers derived from hierarchical clustering (old example).

More about Bcell-100.exp

Among the different B-cell lines represented in Bcell-100.exp are the following, with their abbreviations as used in the dataset:

Cancerous

  1. CLL/P-CLL - B cell chronic lymphocytic leukemia (P indicates purified, otherwise not)
  2. BL - Burkitt lymphoma
  3. DLCL - diffuse large B cell lymphoma (DLBCL)
  4. DLCD - ?
  5. FL - follicular lymphoma
  6. HCL - hairy cell leukemia
  7. PEL - primary effusion lymphoma
  8. D - ?

Non-cancerous

  1. CB - cord blood
  2. CC - ?
  3. M - memory
  4. N - naive


Not used:

  1. MCL - mantle cell lymphoma
  2. MM - multiple myeloma

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.

webmatrix2_quantile_log2_dev1.2_mv0.exp is derived from the same original dataset as Bcell-100.exp described above. 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".