Microarray Data Analysis Using...

Transcript of Microarray Data Analysis Using...

Microarray Data Analysis Using BASE

Danny ParkMGH Microarray CoreMarch 15, 2004
You’ve got data!

What was I asking? – remember your experimental designHow do I analyze the data?– How do I find interesting stuff? – learn

some analysis tools– How do I trust the results? – statistics is

key
What was I asking?

Typically: “which genes changed expression levels when I did ____”Common ____:– Binary conditions: knock out, treatment, etc– Continuous scales: time courses, levels of

treatment, etc– Unordered discrete scales: multiple types of

treatment or mutationsThis tutorial’s focus: binary experiments
How do I analyze the data?

BASE – BioArray Software Environment– Data storage and distribution– Simple filtering, normalization, averaging,

and statistics– Export/Download results to other tools

MS ExcelTIGR Multi Experiment Viewer (TMEV)This tutorial’s focus: using BASE
Today’s Presentation

Demonstrate the most basic analysis techniquesUsing our most frequently used software (BASE)For the most common kind of experiments
Work Flow

Images & data files

scan, segment

uploadBASE

Labeled cDNA

Slides

QC & label

hybridize

RNA

analysis

Researcher
The Most Common experiment

Two-sample comparison w/N replicates– KO vs. WT– Treated vs. untreated– Diseased vs. normal– Etc

Question of interest: which genes are (most) differentially expressed?
Experimental Design – naïve

A B

From Gary Churchill, Jackson Labs

Experimental Design – tech repl

A B


Experimental Design – bio repl

Treatment

Biological Replicate

Technical Replicate

Dye

Array

A BA B


The Most Common Analysis

Filter out bad spotsAdjust low intensitiesNormalize – correct for non-linearitiesand dye inconsistenciesFilter out dim spotsCalculate average fold ratios and p-values per geneRank, sort, filter, squint, sift dataExport to other software
BASE @ MGH

BASE is a microarray data storage and analysis packageBASE resides on our web server– Data is stored at our facility– Computation is performed on our machines

All you need is a web browser– https://base.mgh.harvard.edu/– A Microarray Core technician will provide you with

a username, password, and experiment name

https://base.mgh.harvard.edu/
BASE – Login page
BASE – Login page
BASE – Login page
BASE – Login page
BASE – Logged in
BASE – Logged in
BASE – Sidebar

Reporters
BASE – Sidebar

Reporters
BASE – Sidebar

Array LIMS
BASE – Sidebar

Array LIMS
BASE – Sidebar

Biomaterials
BASE – Sidebar

Biomaterials
BASE – Sidebar

Hybridizations
BASE – Sidebar

Hybridizations
BASE – Sidebar

Analyze Data
BASE – Sidebar

Analyze Data
BASE – Sidebar

Users
BASE – Sidebar

Users
BASE – My Account

Change your password and access defaultsChange your password and access defaults
BASE – My Account

BASE – My Account

BASE – My Account

Find your experiment
Experiment view: Four Tabs
Group slide data together

Select the slides that measure the same thing. Later in analysis, they will be averaged together. In this experiment, all ten slides are replicates, so there is only one grouping.


Give your data set a descriptive name to distinguish it from other slide groupings. In this Myd88 knockout experiment, there is only one grouping, so a generic name is fine.

Analysis: Begin
Analysis: Begin
Analysis: Begin
Analysis: Begin
Analysis: Filter Setup

“Bad” spots are marked with a negative Flag value.




Oligos are annotated with species codes, but control spots are not. Set species to your two-letter code of choice (Mm, Hs, Dr, Pa, etc)


Naming the filter and the child data set are essential to reducing confusion later.

Analysis: Filter Run
Analysis: Quality Data
Analysis: Quality Data
Analysis: Unfiltered Data
Analysis: Filter Parameters
Analysis: Limit-Int Setup
Analysis: Check job status

“All done” indicates the job is complete.“All done” indicates the job is complete.

“All done” indicates the job is complete.“All done” indicates the job is complete.
Analysis: Limit-Int Output
Analysis: Change data set name

Change the name of this set to “Intensity limited Data”

Change the name of this set to “Intensity limited Data”
Analysis: LOWESS Setup
Analysis: LOWESS Output

Change the name of this set to “Normalized Data” using the same steps as before.


Set up the filter as indicated, hit Add/Update on the Gene filter, then hit Accept and select the resulting data set.

Set up the filter as indicated, hit Add/Update on the Gene filter, then hit Accept and select the resulting data set.
Analysis: Useful Data
MA Plots: Raw Myd88 Data
MA Plots: Quality Data
MA Plots: Int-limited Data
MA Plots: Normalized Data
MA Plots: Norm. Corr. Factor
MA Plots: Norm. Corr. Factor
MA Plots: Useful Data
Analysis: Fold Ratio Setup
Analysis: Fold Ratio Output
Analysis: Change list name

Change the name of this list as indicated here.

Analysis: Fold Ratio Graphs
Analysis: t-test Setup
Analysis: t-test Output

Change the name of this set to “myd88 p-value” using the same steps as before.

Analysis: t-test Graphs
Analysis: Experiment Explorer
Analysis: Experiment Explorer
EExplore: Single Gene View
EExplore: Gene List View

Fill out the table as indicated, then hit Add/Update.

Fill out the table as indicated, then hit Add/Update.
EExplore: NCBI Links
EExplore: Gene List ViewThis additional row will restrict hits to P values of 5% or less.

This additional row will restrict hits to P values of 5% or less.
EExplore: Gene List ViewThis additional row will restrict hits to P values of 5% or less.

This additional row will restrict hits to P values of 5% or less.

Open MS Excel and tell it to open the file you downloaded (typically called base.tsv).

Have Fun!

The rest of the analysis is largely driven by your biological understanding of the genes indicated in these lists. We cannot help much in the interpretation of this data.Don’t forget to go back to the raw data sets and repeat this entire analysis for any other slide groupings.
AcknowledgementsMGH Microarray CoreGlenn ShortJocelyn BurkeNajib El MessadiJason FrietasZhiyong Ren

MGH Microarray CoreGlenn ShortJocelyn BurkeNajib El MessadiJason FrietasZhiyong Ren

MGH Lipid Metabolism UnitMason FreemanHarry Bjorkbacka

MGH Lipid Metabolism UnitMason FreemanHarry Bjorkbacka

LUND (Sweden) Dept. Theoretical Physics & Dept. OncologyCarl TroeinLao H. SaalJohan Vallon-ChristerssonSofia GruvbergerÅke BorgCarsten Peterson

LUND (Sweden) Dept. Theoretical Physics & Dept. OncologyCarl TroeinLao H. SaalJohan Vallon-ChristerssonSofia GruvbergerÅke BorgCarsten Peterson

MGH Molecular Biology Bioinformatics GroupChuck CooperXiaowei Wang

Harvard School of Public Health BiostatisticsXiaoman Li

MGH Molecular Biology Bioinformatics GroupChuck CooperXiaowei Wang

Harvard School of Public Health BiostatisticsXiaoman Li

Microarray Data Analysis Using BASEYou’ve got data!What was I asking?How do I analyze the data?Today’s PresentationWork FlowThe Most Common experimentExperimental Design – naïveExperimental Design – tech replExperimental Design – bio replThe Most Common AnalysisBASE @ MGHBASE – Login pageBASE – Login pageBASE – Login pageBASE – Login pageBASE – Logged inBASE – Logged inBASE – SidebarBASE – SidebarBASE – SidebarBASE – SidebarBASE – SidebarBASE – SidebarBASE – SidebarBASE – SidebarBASE – SidebarBASE – SidebarBASE – SidebarBASE – SidebarBASE – My AccountBASE – My AccountBASE – My AccountBASE – My AccountFind your experimentFind your experimentFind your experimentFind your experimentExperiment view: Four TabsExperiment view: Four TabsExperiment view: Four TabsExperiment view: Four TabsExperiment view: Four TabsExperiment view: Four TabsExperiment view: Four TabsExperiment view: Four TabsGroup slide data togetherGroup slide data togetherGroup slide data togetherGroup slide data togetherGroup slide data togetherGroup slide data togetherGroup slide data togetherGroup slide data togetherAnalysis: BeginAnalysis: BeginAnalysis: BeginAnalysis: BeginAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter SetupAnalysis: Filter RunAnalysis: Quality DataAnalysis: Quality DataAnalysis: Unfiltered DataAnalysis: Filter ParametersAnalysis: Limit-Int SetupAnalysis: Limit-Int SetupAnalysis: Limit-Int SetupAnalysis: Limit-Int SetupAnalysis: Limit-Int SetupAnalysis: Limit-Int SetupAnalysis: Check job statusAnalysis: Check job statusAnalysis: Check job statusAnalysis: Check job statusAnalysis: Check job statusAnalysis: Check job statusAnalysis: Limit-Int OutputAnalysis: Limit-Int OutputAnalysis: Limit-Int OutputAnalysis: Limit-Int OutputAnalysis: Limit-Int OutputAnalysis: Limit-Int OutputAnalysis: Change data set nameAnalysis: Change data set nameAnalysis: Change data set nameAnalysis: Change data set nameAnalysis: Change data set nameAnalysis: Change data set nameAnalysis: Change data set nameAnalysis: LOWESS SetupAnalysis: LOWESS SetupAnalysis: LOWESS SetupAnalysis: LOWESS SetupAnalysis: LOWESS SetupAnalysis: LOWESS SetupAnalysis: Check job statusAnalysis: Check job statusAnalysis: LOWESS OutputAnalysis: LOWESS OutputAnalysis: LOWESS OutputAnalysis: Change data set nameAnalysis: Change data set nameAnalysis: Filter SetupAnalysis: Useful DataAnalysis: Useful DataMA Plots: Raw Myd88 DataMA Plots: Raw Myd88 DataMA Plots: Raw Myd88 DataMA Plots: Raw Myd88 DataMA Plots: Quality DataMA Plots: Quality DataMA Plots: Quality DataMA Plots: Quality DataMA Plots: Quality DataMA Plots: Quality DataMA Plots: Int-limited DataMA Plots: Int-limited DataMA Plots: Int-limited DataMA Plots: Int-limited DataMA Plots: Int-limited DataMA Plots: Int-limited DataMA Plots: Normalized DataMA Plots: Normalized DataMA Plots: Normalized DataMA Plots: Normalized DataMA Plots: Normalized DataMA Plots: Normalized DataMA Plots: Norm. Corr. FactorMA Plots: Norm. Corr. FactorMA Plots: Useful DataMA Plots: Useful DataMA Plots: Useful DataMA Plots: Useful DataMA Plots: Useful DataMA Plots: Useful DataAnalysis: Useful DataAnalysis: Useful DataAnalysis: Fold Ratio SetupAnalysis: Fold Ratio SetupAnalysis: Fold Ratio SetupAnalysis: Fold Ratio SetupAnalysis: Fold Ratio OutputAnalysis: Fold Ratio OutputAnalysis: Fold Ratio OutputAnalysis: Fold Ratio OutputAnalysis: Fold Ratio OutputAnalysis: Fold Ratio OutputAnalysis: Fold Ratio OutputAnalysis: Fold Ratio OutputAnalysis: Change list nameAnalysis: Change list nameAnalysis: Change list nameAnalysis: Change list nameAnalysis: Change list nameAnalysis: Change list nameAnalysis: Fold Ratio GraphsAnalysis: Fold Ratio GraphsAnalysis: Fold Ratio GraphsAnalysis: Fold Ratio GraphsAnalysis: Fold Ratio GraphsAnalysis: Fold Ratio GraphsAnalysis: t-test SetupAnalysis: t-test SetupAnalysis: t-test SetupAnalysis: t-test SetupAnalysis: t-test OutputAnalysis: t-test OutputAnalysis: t-test OutputAnalysis: t-test OutputAnalysis: t-test OutputAnalysis: t-test OutputAnalysis: Change list nameAnalysis: Change list nameAnalysis: Change list nameAnalysis: t-test GraphsAnalysis: t-test GraphsAnalysis: t-test GraphsAnalysis: t-test GraphsAnalysis: t-test GraphsAnalysis: t-test GraphsAnalysis: Experiment ExplorerAnalysis: Experiment ExplorerEExplore: Single Gene ViewEExplore: Single Gene ViewEExplore: Single Gene ViewEExplore: Single Gene ViewEExplore: Single Gene ViewEExplore: Single Gene ViewEExplore: Gene List ViewEExplore: Gene List ViewEExplore: Gene List ViewEExplore: Gene List ViewEExplore: Gene List ViewEExplore: Gene List ViewEExplore: Gene List ViewEExplore: Gene List ViewEExplore: Gene List ViewEExplore: Gene List ViewEExplore: Gene List ViewEExplore: Gene List ViewEExplore: NCBI LinksEExplore: Gene List ViewEExplore: Gene List ViewEExplore: Single Gene ViewEExplore: Single Gene ViewEExplore: Single Gene ViewEExplore: Single Gene ViewEExplore: Single Gene ViewEExplore: Single Gene ViewEExplore: Gene List ViewEExplore: Gene List ViewEExplore: Gene List ViewHave Fun!Acknowledgements

Microarray Data Analysis Using...

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