Microarray Data Analysis Using BASE Danny Park MGH Microarray Core March 15, 2004.
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Transcript of Microarray Data Analysis Using BASE Danny Park MGH Microarray Core March 15, 2004.
Microarray Data Analysis Using BASE
Danny Park
MGH Microarray Core
March 15, 2004
You’ve got data!
What was I asking? – remember your experimental design
How 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 mutations
This 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 Excel TIGR Multi Experiment Viewer (TMEV) This tutorial’s focus: using BASE
Today’s Presentation
Demonstrate the most basic analysis techniques
Using 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
From Gary Churchill, Jackson Labs
Experimental Design – tech repl
A
B
From Gary Churchill, Jackson Labs
From Gary Churchill, Jackson Labs
Experimental Design – bio repl
Treatment
Biological Replicate
Technical Replicate
Dye
Array
A BA B
From Gary Churchill, Jackson Labs
From Gary Churchill, Jackson Labs
The Most Common Analysis
Filter out bad spots Adjust low intensities Normalize – correct for non-linearities
and dye inconsistencies Filter out dim spots Calculate average fold ratios and p-
values per gene Rank, sort, filter, squint, sift data Export to other software
BASE @ MGH
BASE is a microarray data storage and analysis package
BASE 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
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 defaults
Change your password and access defaults
BASE – My Account
Change your password and access defaults
Change your password and access defaults
BASE – My Account
Change your password and access defaults
Change your password and access defaults
BASE – My Account
Change your password and access defaults
Change your password and access defaults
Find your experiment
Find your experiment
Find your experiment
Find your experiment
Experiment view: Four Tabs
Experiment view: Four Tabs
Experiment view: Four Tabs
Experiment view: Four Tabs
Experiment view: Four Tabs
Experiment view: Four Tabs
Experiment view: Four Tabs
Experiment view: Four Tabs
Group slide data together
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.
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.
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.
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.
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.
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.
Group slide data together
Group slide data together
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.
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.
Group slide data together
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.
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.
Group slide data together
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.
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.
“Bad” spots are marked with a negative Flag value.
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“Bad” spots are marked with a negative Flag value.
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“Bad” spots are marked with a negative Flag value.
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“Bad” spots are marked with a negative Flag value.
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“Bad” spots are marked with a negative Flag value.
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“Bad” spots are marked with a negative Flag value.
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“Bad” spots are marked with a negative Flag value.
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“Bad” spots are marked with a negative Flag value.
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“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)
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)
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“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)
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)
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“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)
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)
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“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)
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)
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“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)
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)
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“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)
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)
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“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)
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)
Analysis: Filter Setup
“Bad” spots are marked with a negative Flag value.
“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)
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)
Analysis: Filter Setup
Naming the filter and the child data set are essential to reducing confusion later.
Naming the filter and the child data set are essential to reducing confusion later.
Analysis: Filter Setup
Naming the filter and the child data set are essential to reducing confusion later.
Naming the filter and the child data set are essential to reducing confusion later.
Analysis: Filter Setup
Naming the filter and the child data set are essential to reducing confusion later.
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: Limit-Int Setup
Analysis: Limit-Int Setup
Analysis: Limit-Int Setup
Analysis: Limit-Int Setup
Analysis: Limit-Int Setup
Analysis: Check job status
Analysis: Check job status
Analysis: Check job status
Analysis: Check job status
Analysis: Check job status
“All done” indicates the job is complete.
“All done” indicates the job is complete.
Analysis: Check job status
“All done” indicates the job is complete.
“All done” indicates the job is complete.
Analysis: Limit-Int Output
Analysis: Limit-Int Output
Analysis: Limit-Int Output
Analysis: Limit-Int Output
Analysis: Limit-Int Output
Analysis: Limit-Int Output
Analysis: Change data set name
Analysis: Change data set name
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: Change data set name
Analysis: Change data set name
Analysis: Change data set name
Analysis: Change data set name
Analysis: LOWESS Setup
Analysis: LOWESS Setup
Analysis: LOWESS Setup
Analysis: LOWESS Setup
Analysis: LOWESS Setup
Analysis: LOWESS Setup
Analysis: Check job status
Analysis: Check job status
Analysis: LOWESS Output
Analysis: LOWESS Output
Analysis: LOWESS Output
Change the name of this set to “Normalized Data” using the same steps as before.
Change the name of this set to “Normalized Data” using the same steps as before.
Analysis: Change data set name
Change the name of this set to “Normalized Data” using the same steps as before.
Change the name of this set to “Normalized Data” using the same steps as before.
Analysis: Change data set name
Change the name of this set to “Normalized Data” using the same steps as before.
Change the name of this set to “Normalized Data” using the same steps as before.
Analysis: Filter Setup
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
Analysis: Useful Data
MA Plots: Raw Myd88 Data
MA Plots: Raw Myd88 Data
MA Plots: Raw Myd88 Data
MA Plots: Raw Myd88 Data
MA Plots: Quality Data
MA Plots: Quality Data
MA Plots: Quality Data
MA Plots: Quality Data
MA Plots: Quality Data
MA Plots: Quality Data
MA Plots: Int-limited Data
MA Plots: Int-limited Data
MA Plots: Int-limited Data
MA Plots: Int-limited Data
MA Plots: Int-limited Data
MA Plots: Int-limited Data
MA Plots: Normalized Data
MA Plots: Normalized Data
MA Plots: Normalized Data
MA Plots: Normalized Data
MA Plots: Normalized Data
MA Plots: Normalized Data
MA Plots: Norm. Corr. Factor
MA Plots: Norm. Corr. Factor
MA Plots: Useful Data
MA Plots: Useful Data
MA Plots: Useful Data
MA Plots: Useful Data
MA Plots: Useful Data
MA Plots: Useful Data
Analysis: Useful Data
Analysis: Useful Data
Analysis: Fold Ratio Setup
Analysis: Fold Ratio Setup
Analysis: Fold Ratio Setup
Analysis: Fold Ratio Setup
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Fold Ratio Output
Analysis: Change list name
Analysis: Change list name
Analysis: Change list name
Change the name of this list as indicated here.
Change the name of this list as indicated here.
Analysis: Change list name
Change the name of this list as indicated here.
Change the name of this list as indicated here.
Analysis: Change list name
Analysis: Change list name
Analysis: Fold Ratio Graphs
Analysis: Fold Ratio Graphs
Analysis: Fold Ratio Graphs
Analysis: Fold Ratio Graphs
Analysis: Fold Ratio Graphs
Analysis: Fold Ratio Graphs
Analysis: t-test Setup
Analysis: t-test Setup
Analysis: t-test Setup
Analysis: t-test Setup
Analysis: t-test Output
Analysis: t-test Output
Analysis: t-test Output
Analysis: t-test Output
Analysis: t-test Output
Analysis: t-test Output
Analysis: Change list name
Change the name of this set to “myd88 p-value” using the same steps as before.
Change the name of this set to “myd88 p-value” using the same steps as before.
Analysis: Change list name
Change the name of this set to “myd88 p-value” using the same steps as before.
Change the name of this set to “myd88 p-value” using the same steps as before.
Analysis: Change list name
Change the name of this set to “myd88 p-value” using the same steps as before.
Change the name of this set to “myd88 p-value” using the same steps as before.
Analysis: t-test Graphs
Analysis: t-test Graphs
Analysis: t-test Graphs
Analysis: t-test Graphs
Analysis: t-test Graphs
Analysis: t-test Graphs
Analysis: Experiment Explorer
Analysis: Experiment Explorer
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List 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: Gene List View
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List View
EExplore: Gene List View
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.
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Single Gene View
EExplore: Gene List View
EExplore: Gene List View
Open MS Excel and tell it to open the file you downloaded (typically called base.tsv).
Open MS Excel and tell it to open the file you downloaded (typically called base.tsv).
EExplore: Gene List View
Open MS Excel and tell it to open the file you downloaded (typically called base.tsv).
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.
Acknowledgements
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 Microarray CoreGlenn ShortJocelyn BurkeNajib El MessadiJason FrietasZhiyong Ren
MGH Microarray CoreGlenn ShortJocelyn BurkeNajib El MessadiJason FrietasZhiyong Ren
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