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ArrayTrack Tutorials
 

Tutorial Topic Tutorial Content Tutorial Slideshow
1. Comparing two groups (e.g., treated vs control groups).  REQUIRED
  • Statistical methods (t-test, permutation t-test, ANOVA) for group comparison.
  • Differentially Expressed Genes (DEGs) identification
  • Biological interpretation (individual gene analysis) using LIB
  • Pathway analysis (KEGG, PathArt, IPA, MetaCore, Key Molnet)
  • Gene Ontology analysis using GOFFA

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2.  Comparing multiple groups
  • e.g., multiple doses, time points

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3.  VennDiagram
  • Determine the common genes/pathways/functions shared by two or three gene lists (extended to cross-experiment and –platform comparison and systems biology)
  • Apply VennDiagram to the external files

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4.  Data exploring tools
  • Principal Component Analysis (PCA)
  • Hierarchical Cluster Analysis (HCA)
  • Apply HCA and PCA to the external files
  • Extensive features in HCA

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5.  Assessing gene expression profiles using BarChart
  • Access BarChart from the TOOL box
  • Access BarChart from the t-test result table
  • Access BarChart from ChipLib and other Libs
  • How to use BarChart for cross-experiment comparison • Assign group by color

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6.  GeneList - An important concept in ArrayTrack™
  • Create a gene list through data filtering and statistical analysis
  • Import/export a gene list
  • Conduct normalization filtered by a gene lists
  • Conduct statistical analysis (t-test/ANOVA, PCA, HCA and others) based on a gene list
  • Export a dataset by specifying the gene list (extended for cross-platform and cross-experiment comparison)
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7.  Normalization methods
  • For Affymetrix platform: MAS5, RMA, DChip, Plier, Plier+16
  • For other platforms: 7 methods (e.g., LOWESS)
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8.  How to create your own workspace
  • Copy/Paste/Duplicate an experiment

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9A  Import
  • Manual import and batch import

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9B  Export

  • Options of data exporting
  • Export a selected dataset with specifying a sub list of gene
  • Export multiple experiments and/or platforms using selected geneID types (e.g., RefSeq)

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10.  Other useful functions
  • Correlation matrix
  • IDConverter – converting one gene ID to another (e.g., from AffyID to AgilentID or GeneBank#, or LocusLinkID or vice verse)
  • ScatterPlot – pair-wise plot
  • JoinTable – Combine two tables
  • SplitTable – If a table contains multiple hybridization data in column with genes in row, the function split the table into individual tables with single hybridization data.
  • GetUniqueID – If a table contains duplicated IDs, the function pick out the unique IDs

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11.  Basic scripting for querying (raw and normalized) data and table
  • Query data from the database tree (How to use *) e.g., *EST, EST*, *EST*=EST
  • Query data in tables e.g., contain, like (%) and inlist

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12.  Using SAM through ArrayTrack™
  • One-class, two-class, multi-class survival
  • One-class time course, two-class time course

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13.  SimpleTox Format
  • For animal toxicology and toxicogenomics study, integrate microarray data with toxicological data.
  • Data are searchable for toxicological information and microarray information.
  • Batch import SimpleTox data including toxicological endpoints and microarray data.
  • Contains required/optional and customized fields, not limited to non-clinical study.

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