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MSCL Analyst’s Toolbox . Instructors: Jennifer Barb, Zoila G. Rangel, Peter Munson Jan 2008. Mathematical and Statistical Computing Laboratory Division of Computational Bioscience. Course Outline. Day 1 MSCL Analyst’s Toolbox and JMP™ overview MSCL Toolbox Concepts

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mscl analyst s toolbox
MSCL Analyst’s Toolbox

Instructors:

Jennifer Barb, Zoila G. Rangel, Peter Munson

Jan 2008

Mathematical and Statistical Computing Laboratory

Division of Computational Bioscience

course outline
Course Outline

Day 1

  • MSCL Analyst’s Toolbox and JMP™ overview
  • MSCL Toolbox Concepts
  • JMP™fundamentals
  • Lunch
  • Affymetrix ExpressionConsole™, processing .cel files, exporting data
  • MSCL Toolbox Demo
    • Data input
    • Basic Analysis (Master File, Final File, Data normalization, QC, PCA, )
    • Gene selection, statistical tests (p-values, FDR)
    • Annotation

Day 2

  • Statistical Topics (PCA, Data normalization, FDR)
  • MSCL Analyst’sToolbox Demo (cont.)
    • Complex Analysis (2-way ANOVA, blocked ANOVA)
    • Data Visualization
topics not included
Topics not included
  • Exon Array Analysis -- coming soon!
  • SNP chip
  • Resequencing analysis, ChIP-Chip, copy number
  • 2-color or spotted cDNA array analysis
  • complete JMP tutorial
  • JMP on Mac, Linux
  • JMP scripting language
  • Data management commands in JMP:
      • Stack, Split, Concatenate, Sort
why use jmp
Why use JMP?
  • Interactive graphics facilitates data exploration, discovery of features
  • Powerful, > 2,00,000 rows by 100s of columns (currently, 2 GB limit)
  • Scripting language -- object oriented, allows matrix manipulation
  • Connects to database servers including NIHLIMS or local GCOS
  • JMP is also general purpose statistics pack
  • Good technical support for JMP from: (919) 677-8008 or www.jmp.com
  • No direct cost to individual NIH users* (centrally supported in most NIH ICs)
  • MSCL Analyst's Toolbox is FREE, adds tools for microarray studies
mscl analyst s toolbox features
MSCL Analyst’s Toolbox Features
  • Menu driven
  • Automated gene annotations
  • Web link-out**
  • Highly interactive, intuitive user interface
  • Analysis pipeline, based on years of experience
  • Familiar parametric analysis, e.g. ANOVA
  • Exploratory Data Analysis
  • Adaptable to new designs, analyses (e.g. Exon chips, SNP chips)
  • Powerful, handles largest Affy chips, probe-level analysis
  • Up to hundreds of chips at once
  • PC, Mac or Linux desktops
  • Support available through MSCL
mscl analyst s toolbox capabilities
MSCL Analyst’s Toolbox Capabilities
  • Connects to the central NIHLIMS database or local GCOS databases
  • Reads in Pivot Tables from Affymetrix EC™ or GCOS™
  • Visualizes Principal Components
  • Analyzes simple experiments (paired, unpaired T-tests)
  • Analyzes complex experiments (multiple treatments, time series, linear trends, slope changes between treatments)
  • Compensates for “batch” effects
  • Selects and annotates significant genes
  • Manages multiple gene lists (intersection, union, Venn diagrams)
  • Multivariate, Cluster, Discriminant, Neural net analysis
  • Uses dynamic visualization tools
how to obtain
How to obtain:
  • JMP
    • http://isdp.cit.nih.gov/downloads/stats.asp
    • Find your desktop support person at http://isdp.cit.nih.gov/information/contact_lookup_nih.asp
    • JMP technical support from (919) 677-8008
  • The MSCL Analyst's Toolbox
    • Download from http://affylims.cit.nih.gov
    • Help offered on collaborative basis by MSCL
    • Email questions to: munson@helix.nih.gov
mscl toolbox data pipeline
MSCL Toolbox Data Pipeline:

files

Xform

  • Input files or Fetch data
  • Transform and normalize
  • Principal Components Analysis
  • Create Master file, add treatment groups
  • Compute statistical test, get p-values
  • Correct for multiple comparisons or use FalseDiscoveryRate
  • Compute log fold-change
  • Visualize results
  • Select relevant genes

PCA

Final

Master

data sources
Data sources:
  • NIHLIMS database via ODBC connection
  • Local GCOS database via ODBC connection
  • GCOS pivot table
  • EC pivot table (NEW support for this option)
  • Excel spread sheet
  • Text files
data input or data fetch
Data Input or data fetch

NIHLIMS database

Publish(MAS)

EC™ or

GCOS™

MAS5™

MSCL

Publish DB

<username/password>

Process DB

<experiment>

.dat files

.cel files

.chp files

.rpt files

DCEG/NCI

Publish DB

<username/password>

CCMD

Publish DB

Import

ODBC

access

archive(LM)

delete(LM)

assume ownership(LM)

Import(LM)

Export(LM)

client

workstation

Analyze (MAS)

.txt

client

files

Fluidics Platform

Scanner

DMT

A-SCAN

Partek

GeneSpring

gene expression data matrix

1

Genes

20,000

1

16

Samples

Gene Expression Data Matrix

Sample information

Expression

Matrix

Gene Annotations

annotations for each gene

1

Genes

20,000

Annotations for each gene
  • Probe Set ID
  • Genbank ID
  • Unigene ID, Title
  • Entrez Gene ID
  • Cytogenetic map location
  • Physical map location
  • HUGO gene symbol, synonyms
  • Functional relevance
  • Associated literature references ...
  • GO terms for molecular process, biological function or cellular component

Gene

Annotations

annotation files
Annotation Files:
  • Affymetrix annotations for each probeset have been downloaded and formatted for MSCL Toolbox, available at affylims.cit.nih.gov
  • Annotations are updated quarterly
  • Annotation tables may be JOINed by ProbeSetID
      • Probe Set ID
      • Gene Title
      • Gene Symbol
      • UnigeneID
      • Transcript ID
      • Ensembl
      • Entrez Gene
      • Representative Public ID
      • First SwissProt
      • Genome Alignment Chromosome
      • Genome Alignment Start Address
      • Genome Alignment Stop Address
      • Genome Alignment Strand
      • Chromosomal Location

Final

Annot.

Final-Annot

annotating genes
Annotating Genes

Netaffx, reformatted

Your data file

“JOIN” on ProbeSetID

information about the sample transposed into masterfile

1

Samples

16

Information about the Sample(transposed into MasterFile)
  • Clinical information (human)
  • Diagnosis
  • Demographic information
  • Treatment (in vivo, in vitro) in designed experiment
  • Tissue of origin
  • Cell culture, strain, passage
  • Sampling date/time
  • RNA preparation protocol
  • Operator/batch/lot/laboratory information
  • QC information (rawQ, scale factor, 3/5-actin, 3/5-GAPDH, etc)

Information about

each Sample

table formats
Table formats
  • JMP usually deals with a single Table, but…
  • TWO tables are needed for MSCL Analyst’s Toolbox:
  • 1. "Master File" layout
    • Each ROW represents a chip
    • Columns define treatment, replicate number, etc.
  • 2. "Final" layout
    • COLUMNs correspond to chips (rows in Master File)
    • Each ROW is a probe set, unique identifier is probe set ID
  • Tables are LINKED by “Shortnames” field in Master
linked table formats

Master File -- one row per chip

Final File -- one row per probe set

Linked Table Formats
naming convention for final file columns prefixes
Naming Convention for Final File Columns (prefixes)
  • Data type: AD-, SG-, PA-
  • Data transform: L-, Lmed-, GL-, S10-
  • Statistical results: p-, FDR-, mean-, SFC-
  • Column Naming Tips:
    • Avoid punctuation, hyphen, period, slash, etc.
    • Avoid spaces, use underscore “_” instead
    • Shorter is better
    • Toolbox utility available for trimming column names

Column Name

ITEM_NAME

SG-33NH

SG-33TH

S10-33NH

S10-33TH

PA-33NH

PA-33TH

SFC-7

SFC-11

p-slope&cent2

FDR slope&cent2

data pipeline
Data Pipeline:

files

Xform

  • Input files or Fetch data
  • Transform and normalize
  • Principal Components Analysis
  • Create Master file, add treatment groups
  • Compute statistical test, get p-values
  • Correct for multiple comparisons or use FalseDiscoveryRate
  • Compute log fold-change
  • Visualize results
  • Select relevant genes

PCA

Final

Master

data pipeline24
Data Pipeline:

files

Xform

  • Input files or Fetch data
  • Transform and normalize
  • Principal Components Analysis
  • Create Master file, add treatment groups
  • Compute statistical test, get p-values
  • Correct for multiple comparisons or use FalseDiscoveryRate
  • Compute log fold-change
  • Visualize results
  • Select relevant genes

PCA

Final

Master

data pipeline26
Data Pipeline:

files

Xform

  • Input files or Fetch data
  • Transform and normalize
  • Principal Components Analysis
  • Create Master file, add treatment groups
  • Compute statistical test, get p-values
  • Correct for multiple comparisons or use FalseDiscoveryRate
  • Compute log fold-change
  • Visualize results
  • Select relevant genes

PCA

Final

Master

analysis scripts
Analysis Scripts
  • ANOVA1
  • T-test, unequal variance
  • Paired t-test
  • Consistency test
  • ANOVA1 with blocking
  • ANOVA2 with interaction terms (unbalanced data allowed)
  • ANOVA2 with blocking
  • Linear regression
  • ANCOVA with blocking (balanced data case)
  • ANCOVA2 with blocking (balanced data case)
  • Other tests are easily added (requires scripting)
data pipeline28
Data Pipeline:

files

Xform

  • Input files or Fetch data
  • Transform and normalize
  • Principal Components Analysis
  • Create Master file, add treatment groups
  • Compute statistical test, get p-values
  • Correct for multiple comparisons or use FalseDiscoveryRate
  • Compute log fold-change
  • Visualize results
  • Select relevant genes

PCA

Final

Master

log foldchange lfc
Log(FoldChange)=“LFC”

FoldChange = treated / control

Log(FoldChange) = Log(treated / control)

= Log(treated) - Log(control)

Rule of Thumb for Base10 Logarithms:

Log10(2-fold change) = 0.3

Log10(10-fold change) = 1

Log10(0.1-fold change) = -1

data pipeline30
Data Pipeline:

files

Xform

  • Input files or Fetch data
  • Transform and normalize
  • Principal Components Analysis
  • Create Master file, add treatment groups
  • Compute statistical test, get p-values
  • Correct for multiple comparisons or use FalseDiscoveryRate
  • Compute log fold-change
  • Visualize results
  • Select relevant genes

PCA

Final

Master

volcano plot

Significance of change

Magnitude of change, Log Scale

Volcano Plot

Selection

Regions

interpreting gene lists
Interpreting Gene Lists

Final

Annot.

Filter

(FDR<10%)

Ingenuity™,

GeneGo™

GeneList

Significant Terms

go scan gene ontology annotations
GO-SCAN- Gene Ontology Annotations
  • Gene Ontology for Significant Collection of Annotations: GO-SCAN is a bioinformatics
  • tool that selects and presents relevant Gene Ontology (GO) annotations for a gene "hit"
  • list from an Affymetrix microarray experiment. http://goscan.cit.nih.gov/