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EGAN tutorial: Loading experiment results

EGAN tutorial: Loading experiment results. October, 2009 Jesse Paquette UCSF Helen Diller Family Comprehensive Cancer Center jesse.paquette@cc.ucsf.edu. Preamble. This document has many slides with multi-step animations Best viewed in Slide Show mode

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EGAN tutorial: Loading experiment results

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  1. EGAN tutorial:Loading experiment results October, 2009 Jesse Paquette UCSF Helen Diller Family Comprehensive Cancer Center jesse.paquette@cc.ucsf.edu

  2. Preamble • This document has many slides with multi-step animations • Best viewed in Slide Show mode • The EGAN graphical user interface is evolving • Icons may change • Menus may change • Button/widget placement may change • This document probably won’t change as quickly • Please contact the developers if you notice major discrepancies between this and EGAN

  3. Loading experiment results: An overview EGAN is designed to help you interpret the results of exploratory assays EGAN does not actually do the multivariate statistical analysis for your experiment It picks up where many useful analysis programs stop: at the gene list If the entities measured in an assay can be mapped to genes, the results can be loaded in EGAN Expression microarrays MS/MS peptide identifications Genome-wide SNP/CNV assays Next-gen sequencing DNA methylation assays ChIP chips

  4. Loading experiment results: An overview EGAN works best when you load results for all entities measured in the assay i.e., don’t apply a p-value cutoff on the results before loading into EGAN Just because a gene missed the cutoff at p < 0.001, there’s still a good chance that it is a significant hit Especially if it is related to other top hit genes EGAN will allow you to adjust the statistic/p-value cutoff dynamically Then you can directly observe how networks/enrichment scores change with different cutoff values Of course you can still load post-cutoff experiment results If that’s all you have…

  5. Loading experiment results into EGAN

  6. Loading experiment results into EGAN:The file format Tab-delimited text Easy to create in Excel from existing result files Header line required Header of statistic (second) column will become the experiment name in EGAN Three columns 1) Entity ID i.e. probe set ID, UniProt ID, refSNP ID, etc. You can use any IDs that can be mapped to Entrez Gene IDs EGAN provides a wide variety of mapping file options HUGO Gene Symbol, AffymetrixAgilent/Illumina IDs, GenBank, Ensembl, UniProt, etc. EGAN expects that all entity IDs are the same type 2) Statistic (fold-change, regression coefficient, log-odds ratio, etc.) EGAN visualization schemes are best when the statistic column is centered around 0 Ratio and fold-change data can be 0-centered by logarithm 3) P-value (unadjusted, adjusted or q-value)

  7. Loading experiment results into EGAN:An example Header line: the statistic (second) column header should be descriptive Each row represents the analysis result for one entity in the experiment Three columns: ID, statistic, p-value

  8. Loading experiment results into EGAN:An example Save as tab-delimited text

  9. Loading experiment results into EGAN:An example • Download or construct an experiment result file • This example will use two pre-made experiment result files (download these files to follow along) • Affymetrix (expression) predictors of Herceptin resistance in HER2 over-expressing breast cancer cell lines • aCGH (copy number) predictors of Herceptin resistance in HER2 over-expressing breast cancer cell lines • …and one custom mapping file • Launch EGAN H. sapiens

  10. Loading experiment results into EGAN:An example Click “Browse…” Click “Browse…” This experiment result file uses Affymetrix HG-U133A probe set identifiers. Select “Affymetrix HG-U133A” from the drop-down menu. Enrichment calculations in EGAN are dependent on how we define the background population of genes. In this case we only want genes to be in the background if they are present in all experiment results. Select “intersection” from the drop-down list. For simplicity’s sake, we’re not going to cover items 3-5 right now. Click “Add Experiment”. Select your experiment and click “Specify empirical data set” Select the aCGH experiment and click “Specify empirical data set” Now both experiment results are ready to be loaded. There’s one more thing to consider before launching EGAN...click on “5) Gene Nodes”. Select the mapping file and click “Specify mapping file” For the aCGH clones we have a custom mapping file. Click “Browse…” We want to load a new experiment The expression results are ready to be loaded. Let’s load the aCGH results. Click “New Data Set”. Click “Add Experiment” Click on “6) Experiments” Finally, click “Finish – Launch EGAN”

  11. Loading gene-gene edges into EGAN: An example Whenever you change the network configuration by adding or removing files, you will be given the option to save the new configuration to a tab-delimited text file. If you choose to save a .config file, next time you will only need to specify that file (item 3 in the Launch EGAN Wizard).

  12. Loading gene-gene edges into EGAN: An example Your experiments are now accessible in EGAN: as columns in the Entrez GeneNode Table and as rows in the Experiments Table.

  13. Questions/comments? • Visit http://groups.google.com/group/ucsf-egan for downloads, documentation and discussion • Requires an account with Google Groups

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