Functional Genomics
 

> Microarrays


NOTE:  We can work with most any spotted microarray from commercial vendors or collaborators. Contact the Functional Genomics lab (extension 4156) if you are interested in using arrays that are not listed below.

The spotted microarray services encompass the following:

Consultation
Functional Genomics laboratory staff will assist you in the design of an experiment BEFORE you bring samples for analysis. We will also provide instruction in the preparation of suitable RNA or DNA, the ordering process, microarray selection, experimental design and data analysis.

cDNA Library Management
Functional Genomics staff currently maintain cDNA clones from some mouse and human libraries. The original clones are replicated twice to produce two copies of each library; one copy is an archive set that is stored in a separate freezer, and the second copy is used as working stock from which PCR products are produced for arraying.

Microarray Production
Functional Genomics staff have designed and printed mouse and human microarrays on glass slides. Once printed, microarrays are relatively stable and may be used in experiments for up to a year. Current arrays contain a range of spot densities from 9,200 to over 18,000 genes.  For custom array services, click here.

Target Preparation
We currently use an indirect labeling procedure that reduces the amount of starting total RNA required for a gene expression experiment to approximately 10 micrograms per sample. We also provide RNA amplification, DNA labeling services and array-based comparative genomic hybridization (aCGH) services.

Hybridization
The Functional Genomics laboratory has determined suitable hybridization conditions for our microarrays via experiment and experience. Please contact the Functional Genomics lab for custom hybridization conditions for specific samples or arrays. 

Analysis
We provide a standard image analysis for Cy3 and Cy5 labeled arrays. Contact Functional Genomics staff if alternative dyes, special scanning requirements or other custom needs are required.  We upload the resulting data to a storage area network. You may retrieve the results of your experiment using our web-based retrieval tool  "SRM(Data Retrieval)".

Available Arrays (Chips)
To see the list of chips that are currently available, click here.  We can also accomodate most commercially prepared microarrays if they are printed on standard size (1x3 inch)microscope slides.  Please contact the Functional Genomics lab at extension 4156 for more information.

Updated Gene Annotations
Gene annotations for all standard chips prepared by the Functional Genomics lab are updated on a regular basis by our bioinformatics team.  View more information.

How to order

Hints on Experimental Design

There are as many ideas for microarray experiments as there are experimentalists, so it is difficult to provide general guidelines. It is perhaps best to simply remind the reader of the fundamental change in philosophy one must embrace to conduct biological experiments on this scale. Mark Schena stated it well in his book Microarray Biochip Technology: "Microarray experiments should begin with a question, but need not begin with a hypothesis. The distinction seems subtle, but again the difference is actually substantial. Starting with a question means that the focus, scope, and intent of a study have been formulated prior to undertaking an experiment. Starting with a hypothesis means that the study has been undertaken with an a priori understanding of what the outcome is likely to be. Because microarray analysis allows a totally unprecedented look at biological systems it is often impossible to formulate a hypothesis a priori because so little quantitative information is available about biological systems at the genomic level. Adhering to a query-based paradigm, but not necessarily requiring hypothesis research, provides a careful guide for microarray experimentation without quashing the discovery-oriented aspects of working with chips."

Some points to consider for gene expression experiments:

  1. The more tightly controlled the experiment the better. Studies in cell culture are preferable to tissue samples, if possible.  
  2. The act of sampling tissues will activate/inactivate gene expression (e.g. apoptosis-related genes). All samples should be treated identically where possible.  
  3. Consider all possible factors impacting gene expression in your experimental design. For example, the genes expressed in a liver sample will depend on such factors as when the animal was last fed.  
  4. Major insults to cells will change the expression of lots of genes. For example, irradiating cells will change the expression of hundreds of genes complicating the interpretation of the experiment.  

What You Provide the Functional Genomics Laboratory

  1. You identify the microarrays (chips) containing genes of interest for your studies either by
    • clicking here to download an Excel spreadsheet containing the complete list of each chip in stock in the Hartwell Center (simply click on the download button next to each listing) or
    • querying HCNetDat database for specific IMAGE clone ID numbers or keywords (simply click on the library name hyperlink for access to the database). Examine the listing for each chip and choose which of the chips suit your experimental requirements.
  2. You place an order using the Hartwell Center SRM online ordering system.
  3. For comparative genomic hybridization experiments, you prepare genomic DNA.  Please contact the Functional Genomics lab for information on suggested purification procedures for DNA.   For gene expression experiments, you prepare total RNA preparations from Reference and Test samples. We do not require isolation of polyA+ mRNA! Please bring only total RNA from your Reference and Test samples. High purity RNA is a critical component of a successful cDNA microarray analysis. We require that RNA be isolated using Trizol or RNAstat. It is further recommended that RNA samples be cleaned up by treating with Ambion DNAse and purified using the Qiagen RNAeasy kit. Many protocols are available for the preparation of total RNA from various cell and tissues sources. The main consideration is the rapid and complete inactivation of ribonucleases. Protocols for RNA isolation should take into account seemingly mundane factors such as incubator temperature, CO2 concentration, growth media, buffer components, hormones and other additives, reagent lot numbers, rotor temperatures, and the like. For comparative analyses, it is essential that the "Reference" and "Test" biological specimens be processed in an identical fashion. Sample artifacts can become substantial when analyzing thousands of genes in a single experiment. We require a minimum of 10 micrograms of total RNA for the Reference sample and 10 micrograms for the Test sample for each microarray. RNA samples must be completely free of ethanol and phenol and must be re-suspended in water to a concentration of 2ug/uL.
  4. You bring the samples to the Functional Genomics laboratory in the Hartwell Center (room DT1008).  

What We Provide

  1. We will use a small portion of your RNA sample for analysis on an Agilent Bioanalyzer "Lab on a Chip" system to recheck the RNA quality. If your RNA is degraded or otherwise unsuitable for application to an array we will notify you immediately.
  2. We will dye-label your Reference and Test RNA (or DNA) samples with Cy3 and Cy5.
  3. We will hybridize your dye-labeled target DNAs to your selected microarray.
  4. We will conduct the image analysis needed to accurately quantitate the level of expression of each gene in the microarray.
  5. We will upload your expression data to our storage area network.

What You Get

  1. We archive all microarray images and initial data analysis files. These are available for re-analysis if needed.
  2. You retrieve the results of your expression experiment by using your Web browser and pointing to "SRM(Data Retrieval)". 
  3. Your data is proteted by username and password and is available only to you.  
  4. You may easily download the data file for use in programs such as Excel and Spotfire for data analysis. You may also download the image file. 
  5. You may also consult with Bioinformatics staff for additional assistance in the analysis and interpretation of your expression data (x2385). 

Ordering with SRM

SRM is the Hartwell Center web based ordering and tracking tool that stands for Shared Resource Management . Please use this system when placing orders.

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Quality assurance

RNA Quality

To obtain high quality data from your gene chip experiment, it is essential to start with high quality total RNA. If RNA is degraded or otherwise unsuitable for microarray application, investigators will be notified immediately.

Spectrophotometric Analysis:
A small amount of your sample will be assayed with a Spectromax Plus or Nanodrop spectrophotometer. We require a concentration of greater than 1.5 mg/mL. The OD 260/280 is calculated to estimate the purity of the RNA. A ratio close to 2.00 indicates a high percentage of ribonucleotide.

Electrophoretic Analysis:
To assess the integrity of your total RNA, we will test it with the Agilent Technologies 2100 Bioanalyzer Lab-on-a-chip system. This assay is similar to gel electrophoresis in concept, but it is cleaner, more efficient, and only requires a very small amount of sample.  Additional information about the Agilent Bioanalyzer can be found here.

Chip Production

  1. Before printing, purified PCR products are analyzed using agarose gels to check yield and product size.
  2. Hybridization controls are printed in each subarray of each chip.
  3. A chip from each print run is stained with SYBR Green or hybridized to dye-labeled random oligos to determine spot quality and to detect any printing problems.
  4. A chip from each print run is tested for quality with control RNA samples that are labeled and hybridized using our standard conditions.
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DATA ANALYSIS/TROUBLESHOOTING

Microarray experiments generate an enormous data stream, placing bioinformatics at the core of the microarray industry. The Hartwell Center's bioinformatics section and high performance computing facility provides the substantial computational resources needed.

Most microarray images are analyzed using Genepix Pro.  GenePix Results data are saved as GPR files, which are in Axon Text File (ATF) format. A Results file contains general information about image acquisition and analysis, as well as the data extracted from each individual feature. Any user-defined feature data contained in a GAL file read by GenePix Pro 4.1 will be included in the output GPR file. For the description of columns in the GPR file, click here

Data are uploaded to a storage area network and can be retrieved by SJCRH investigators using SRM(Data Retrieval).

Hartwell Center computing hardware supports microarray applications, proteomics, structural biology, and other research activities.

Tools for viewing and analysis of array data including Spotfire are available to SJCRH investigators.

For additional information regarding the use of these applications and databases, contact bioinformatics at x2385. Click here for information on training classes offered in the Hartwell Center's Computer Graphics/Training facility located on the Plaza level of the Danny Thomas Research Tower. Individual research groups may also schedule smaller group sessions.

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INSTRUMENTATION

QArray2 arrayer (Genetix)

Additional Equipment:

  • Genemachines HiGro for cell growth
  • ScanArray5000 (Perkin Elmer) and Genepix 4000B (Axon Instruments) scanners to acquire data 
  • Spectramax plus and Nanodrop spectrophotometers
  • Genemachines HybStation and Ventana Discovery slide processors

Biorobot 8000 (Qiagen)

FEES

Please see general fees page.

PROTOCOLS

  • M004.10 - Reverse Transcription and Amino-allyl Labeling of RNA
  • M005.7 - Array Hybridization
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FAQ's

This is a list of frequently asked questions (FAQs) from users of our Functional Genomics (cDNA microarray) services. If you have read the FAQs and still have unanswered questions, don't hesitate to contact our staff at extension 4156.

OVERVIEW

What is a microarray?

A basic microarray consists of numerous elements (spots) of DNA that can be used to determine the levels of mRNA expression in samples of interest. The DNA for each element represents a gene of interest and is a target for the mRNA encoded by that gene. Each spot has a unique DNA sequence, thus each spot will hybridize only to its complementary DNA strand. This basic principle is the same as used in Southern and Northern blots. While blot analysis techniques are performed using one target at a time, the power of microarray technology lies in its ability to allow the researcher to study thousands of targets in a single experiment.

How are microarrays made?

There are two basic fabrication methods:

  1. DNA targets are synthesized separately using PCR for cDNAs or chemical synthesis for oligonucleotides. Using robotics systems, the DNA is spotted onto a substrate. The Functional Genomics lab prints PCR products prepared from cDNA libraries or oligonucleotides. The PCR-amplified fragments of individual cDNA clones (~500bp-2000bp)  or oligonucleotides are spotted (printed) onto coated glass microscope slides using quill-type printing pins. This method is comparatively cheap and flexible.  Some related technologies use an ink-jet like printer to spray targets on the substrate (Agilent, Rosetta).
  2. DNA oligonucleotides are synthesized directly on the substrate using UV-masks and photo-activated chemistry (Affymetrix; ~25 bp).

What are the differences between different types of microarrays?

The different types each have their own characteristics with their own strengths and weaknesses to each technology. For example, the Affymetrix technology is relatively expensive and fairly inflexible in that these microarrays are designed and produced commercially by Affymetrix using photolithography methods. While custom microarrays can be made, the cost is extremely high and production time can be long. This technology is very robust, reproducible, and allows the detection of SNPs and other small features in the DNA. Currently, the Affymetrix system is not a co-hybridization system therefore; only one sample is hybridized to one GeneChip. Each sample produces absolute intensity values rather than ratio values. It is thus very important to normalize between the results from the test and reference GeneChips.

Spotting DNA on glass microscope slides is relatively inexpensive and very flexible. The spotting process itself is however, inherently variable. Co-hybridizing a reference and test sample on the same microarray minimizes this variability. To distinguish the test from the reference sample, each sample is labeled with a different fluorescent dye. This technology is thus often referred to as "two color" microarray analysis.  Most microarrays produced by spotting on glass slides use cDNAs or oligonucleotides as the spotted material. Using cDNAs poses some technical issues, for example: because the cDNA is a long sequence (usually approximately 500bp-2000bp) it is impossible to discern between genes that are more than 80% similar. Thus, SNPs cannot be detected. Spotting oligonucleotides on glass slides can avoid some of the above limitations.

PRODUCT RELATED

What arrays are available in the Functional Genomics lab in the Hartwell Center?

For a description of the specifics of each of the microarrays currently available for use by St Jude researchers, click here.

How do I view a list of genes represented on Hartwell Center cDNA microarray chips?

Click here, under “available arrays and clones” click on the chip name and follow the links to the clone list.   You may also use HCNetDat to query the contents of each chip.

How much does a cDNA array experiment cost?

A complete gene expression experiment for a RNA sample pair involving RNA quality control checks, fluorescent labeling and hybridization onto one glass slide will range from approximately $120-$180 depending on the chip selected. These are reagent costs only and are based on arrays containing approximately 9200-19,000 elements. Arrays with a higher number of elements (higher density) will cost a bit more.

SPECIAL SERVICES AND CUSTOM ARRAYS

Do you provide custom array services?

Yes. Although we have printed several "standard" mouse and human chips that contain gene sets that will provide a broad view of the mouse and human genome, we also provide custom array services.  Click here for more information.

PROTOCOL RELATED

What processes are involved in performing microarray experiments in the Functional Genomics lab?

There are five major steps:

  1. Preparing and spotting DNA onto a substrate (this is performed in the Hartwell Center).
  2. Nucleic acid sample isolation (RNA for gene expression experiments or DNA for array-based comparative genomic hybridization (aCGH) or other applications) is performed by the investigator. The investigator must isolate nucleic acid samples from both a reference and test sample. It is important to realize that the RNA from tissues or any heterogeneous cells may lead to results that reflect changes in the composition of the sample rather than in changes due to the experimental hypothesis.
  3. cDNA synthesis and labeling (this is performed in the Hartwell Center). This involves a single round of linear amplification, performing a reverse transcriptase reaction (for RNA samples) or Klenow reaction (for DNA samples) and subsequently incorporating dye that has been linked to a DNA nucleotide. The reference sample is labeled with one fluorescent dye (usually Cy3) while the test sample is labeled with another fluorescent dye (usually Cy5).  Since two dyes are used to distinguish the test from the reference sample, this method is often referred to as "two color" microarray analysis.
  4. Hybridization of the labeled probes to spotted DNA (this is performed in the Hartwell Center). The labeled test and reference samples are mixed, placed on the array and allowed to hybridize overnight. The hybridization solution is then removed and the microarray is washed.
  5. Detection, imaging and analysis. Once the microarray has been washed, it is scanned to detect and quantitate the amount of probe bound to the DNA target on the microarray. During scanning, lasers are used to excite the fluorescent dyes. The photons emitted are captured and quantitated and an image of the microarray is produced. The image is analyzed to locate spot boundaries, calculate local background, etc. The Hartwell Center performs the detection, imaging and initial analysis. Investigators can use software tools provided by the Hartwell Center (including Spotfire) to further analyze their data.

How long does it take to complete one experiment?

Depending on the number of samples in queue in the lab, one experiment usually takes 5 days to complete. Some of these days must be consecutive days for an overnight hybridization, etc.

SERVICE RELATED

Can you help me design experiments with microarrays?

Good experimental design is essential for obtaining meaningful microarray results. For help, call Deanna Naeve at extension 4847 or Dr. Michael Wang at extension 4224 to arrange a meeting. We will discuss with you with all the options available and recommend the best fit for your needs.

What do I need to do to start a cDNA gene expression microarray experiment?

Design your experiment thoughtfully, read current literature and pay special attention to controls and a statistically acceptable number of data points.For gene expression studies, cDNA microarray technology is best suited for analysis of mutants (knockout or conditional), or transcriptional studies where a fraction of the total gene pool is likely to exhibit changes significant changes. Isolate your nucleic acid samples with utmost care. The quality of sample you bring in is directly proportional to the quality of data you get back. Take standard precautions with RNA - use RNAse inhibitors, use fresh plastic ware, wear gloves, transport your RNA on dry ice and store at –70C.

How much DNA or RNA sample do I need to submit for cDNA microarray analysis?

The amounts of DNA or RNA sample needed varies according to the service.  Please contact the Functional Genomics staff at extension 4156.

How do I prepare my RNA for gene expression microarray analysis?

High purity RNA is a critical component of a successful cDNA microarray analysis. We require that RNA be isolated using Trizol or RNAstat. It is further recommended that RNA samples be cleaned up by treating with Ambion DNAse and purified using the Qiagen RNAeasy kit.  Resuspend RNA in RNase-DNase free water at a concentration of 2 micrograms/microliter.  For applications other than gene expression, please contact the Functional Genomics staff at extension 4156.

For gene expression experiments, d o I bring in poly A RNA or just total RNA?

We prefer that you bring total RNA. Using the high yield amino-allyl based labeling methods in our laboratory, we consistently get good results with total RNA obviating the need for purifying mRNA from total RNA.

Can I prepare RNA from tissues?

Yes. Both RNA-STAT and TRIzol methods permit efficient isolation of RNA from tissues.

How many replicate arrays should I do?

For spotted arrays, we recommend 3-5 replicates but some people do as many as 10. Whatever you do, don't do just one. You may also want to do reverse labeling where the dyes used to label reference and test samples are reversed. Keep in mind that doing 10 replicates isn’t nearly as effective as doing 5 replicates with the original set of RNA samples and another 5 with freshly isolated RNA samples (biological replicates).

If I want to compare several test samples to the same reference sample, do I need to submit more than one reference sample?

Yes, you must submit a reference sample for every test sample. For two color microarray analysis, the reference sample is labeled with a fluorescent dye (usually Cy3) and the test sample is labeled with a different dye (usually Cy5). The two samples are then mixed and placed on one microarray chip. This mixing of samples can greatly increase the accuracy of results by eliminating artifacts arising from chip-to-chip variation.

Can you describe the procedure involved in my experiment after I leave the samples
with you?

Your samples are catalogued and subjected to a series of quality control checks.

We first measure the optical density of your samples at 260 and 280 nm to confirm the concentration of your samples. It is important that your samples are submitted at the required concentration (2ug/uL) in order to obtain accurate quality control results. Samples submitted with concentration values ranging far from the required concentration will be returned to the investigator.

If the RNA samples have adequate concentrations, they are subjected to an RNA quality control assessment using the Agilent Bioanalyzer 2100 (“lab-on-a-chip ” system). This ensures that samples are not degraded. Further information about the chemistry behind this procedure is available at http://www.chem.agilent.com/scripts/generic.asp?lPage=1563&indcol=N&prodcol=Y.
More information about the software used to analyze Agilent results is available at http://www.chem.agilent.com/Scripts/Generic.ASP?lPage=2721&indcol=Y&prodcol=Y.

If the samples do not pass this step of quality control (QC), the experiment is terminated and you are charged for the quality analyses. If samples pass this QC step, they are subjected to a labeling protocol.  Following this, the labeled samples are spectrophotometrically analyzed to determine the extent of labeling. If the samples do not label according to expectations, the experiment will be terminated and you will be charged for the analyses performed. If your samples pass labeling QC, they will be hybridized overnight, washed and scanned using a dual wavelength scanner. The resulting image will be analyzed using microarray image analysis software and a data file generated.

DATA ANALYSIS RELATED

How do I get my data?

Your data (image as well as numerical data) will be archived in the Hartwell Center archives where it can be retrieved by you using SRM(Data Retrieval)
Contact Bioinformatics (extension 2385) if you do not have a SRM(Data Retrieval) username and password.

Why ratios and co-hybridizations?

The technique that allows the spotting technology to sidestep the issue of variability in spotting and other concerns is the use of co-hybridizations. For example, for gene expression experiments the main concept is to use relative RNA expression levels instead of absolute expression levels. To accomplish this, two separate RNA samples are used: a "test" and a "reference". Each RNA is labeled with a different fluorescent dye, the two samples are then mixed and hybridized at the same time to the microarray. When the microarray is scanned, the number of photons in the experimental dye's spectrum is compared to the number of photons in the reference dye's spectrum. Many variations in spot size, probe concentration, and other issues (e.g. secondary structure, melting temperature, and target characteristics) are cancelled out in this manner.

There is currently much debate about how to use and normalize these ratios, and even exactly which numbers to use for the ratios. The actual number used to calculate the ratios is derived from the intensities of the pixels that make up the DNA spot. Once these pixel intensities are adjusted for background there are many ways to extract a single number to use in ratios. Some investigators use the median pixel value, some use the mean, and some researchers throw out all of the saturated pixels and then take the mean.

Once you've decided how you want to extract a single value from the pixel intensities you can now measure your ratio and determine if your genes of interest are being expressed more or less relative to your reference sample. Some researchers take the log of these ratios, as they will then have the nice property of being centered around zero with positive numbers indicating induction of a gene and negative numbers indicating repression of a gene, relative to the control sample. Keep in mind that there are still a host of issues when it comes to normalizing these values and comparing values between different microarrays.

What do I do with my data? How do I analyze data?

Two color microarray data will be made available to you as a tab delimited text file (.gpr format; stands for gene pix results). This format is compatible with several gene expression modules. The Hartwell Center provides Spotfire Decisionsite software for Functional Genomics, a data mining and visualization tool, for processing and visualization of your microarray data.  The bioinformatics team of the Hartwell Center are also available to aid in data analysis.

How can you help me with data analysis?

Your local support provider (LSP) can help you install Spotfire Decisionsite for Functional Genomics on your laboratory desktop.   A tutorial on how to use Spotfire is included.  Functional Genomics staff will process your initial data files for you.  We are always available if you need additional help. We are also conducting regularly scheduled training sessions for Spotfire.

What software is better suited for my data?

We provide Spotfire for two color microarray data, but you are free to use any data analysis tool you choose.

How do I download Spotfire software?

You may contact your local support provider (LSP) or access all microarray analysis software available to St Jude researchers via the Hartwell center website. In order to download Spotfire, click on the link below and follow the instructions. Please ensure that you install Spotfire on the best possible machine in your lab. In order to get the best out of this powerful data-mining tool, you must use up-to-date operating systems, service packs and browser versions on your PC. download spotfire.

What is normalization? Do I need to normalize?

Because "two color" arrays involve the use of two independent samples that might vary slightly in concentration and two separate labeling reactions which might have proceeded at different efficiencies, the overall brightness of the signal from one sample is often brighter than that from the other. If this is not corrected for, the data will be skewed to indicate that the sample, which had more RNA or better labeling, had higher expression levels (on average) in every spot. Normalization refers to the correction. In most cases cDNA microarray data needs to be normalized before it can be correctly interpreted. Look for the normalization values provided on your .gpr data file.

There are at least three different methods that have been used for normalizing arrays:

  • Measure the total intensity of the two colors, and use the overall ratio as a correction factor. The correction factor is applied to each ratio. This is known as global normalization. This method is based on the assumption that the average gene expression ratio on your array is 1. If your experimental manipulation is expected to cause more than 10-20% of all genes to change expression level in one direction, this method will not be reliable. The advantage of this method is that you can perform it on any array.
  • Use the expression ratios of exogenously spiked control nucleic acids. The spiked nucleic acids are unrelated to the experimental nucleic acid samples, such as spiking with plant RNAs into human experimental RNAs. This procedure requires that arrays include a number of complementary control cDNAs. Equal amounts of these nucleic acids are then added ('spiked') into both reference and test experimental samples. The correction factor is calculated as in the previous method, but only the control spots are used in the calculation. We are currently using this method for those samples that generate arrays that cannot be reliably normalized using the global approach. We carry out this normalization based on Arabidopsis thaliana control spots (three genes each spotted several times on the array).
  • Use housekeeping genes that are presumed not to change as controls. This is an extension of the procedure many people use when doing quantitative Northern blots - actin or GADPH are commonly used in that application. Obviously this method is only as good as your confidence that the genes you selected really don't change expression level, and for this reason most people don't use this method. We do not recommend this method with any degree of confidence.

How do I know when a change in gene expression is significant?

This is a difficult question to answer, and one that an increasing number of statisticians are investigating. Determining significance is more reliable with a high number of replicate measurements. In addition, some genes can show a large variance in expression level on cDNA microarrays, and this variability can be related to the state of the sample (i.e., it is biological in nature) or due to differences in sample handling.

Is the data statistically significant? How many replicate sets are required to reach that stage?

It is important to keep in mind that analyzing array data for 'changed genes' is basically a game of deciding whether false positives or false negatives are more costly. It is difficult to provide a meaningful cutoff such as "2-fold changes are significant", because other factors must be considered such as how confident you are in the individual measurements that determine a ratio. Since the goal of most users is to find candidate genes which can then be followed up, a better procedure is to rank genes with the assistance of some kind of confidence measure, add a good dose of biological knowledge, and proceed from there.

What does clustering mean?

Clustering is a means of studying and identifying patterns of gene expression and grouping genes into expression classes across multiple experiments. We will show you how to use Spotfire to cluster your data based on hierarchical or K means algorithms. An excellent explanation of basic concepts of clustering can be found in the following reference:

Quackenbush J. Computational analysis of microarray data. Nat Rev Genet. 2001 Jun; 2(6):418-27.

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CHIPS

Spotted Arrays (Chips)

NOTE:  We can work with most any spotted microarray from commercial vendors or collaborators.  Contact the Functional Genomics lab (extension 4156) if you are interested in using arrays that are not listed below.

Organism Chip Name Number of Features Library Information & Source Chip Type Downloads
Human human CpG 12K 12,796 (12,192 human clones + 604 controls) human CpG 12K library Sanger Institute clones, printed by UHN cDNA Chip gene array list

link to UHN database
Human RPCI human 6K BAC 12,862 (6,379 human clones printed in duplicate + 104 controls) Human 6K RPCI-11 Roswell Park Cancer Institute BAC Chip gene array list
Human RPCI human 19K BAC 38,944 (19,426 human clones printed in duplicate + 92 controls) Human 19K Roswell Park Cancer Institute BAC Contact the Functional Genomics lab for information
Human HGc10K 9,704 (9,182 human clones + 522 controls) Incyte Human Unigene 1, formerly called Human Unigem v2.0 cDNA 1) Chip gene array list
2) Sequence files
Mouse RPCI mouse 6.5K BAC 19,584 (6,528 mouse clones printed in triplicate) Mouse 6.5K RPCI-23/-24 Roswell Park Cancer Institute BAC Chip contents list
Mouse mouse CpG island 7.3k 7,680 (7,296 mouse clones + 384 controls) mouse CpG 7.3K library Sanger Institute clones, printed by UHN cDNA Chip gene array list

link to UHN database
Mouse MGC20K (replaces retired M20K) 19,067 (18,317 mouse clones + 750 controls) combination of M2 & M4 libraries cDNA Chip gene array list
Mouse MEEBO   38,467 (35,302 mouse oligos + 3,165 controls) Illumina, printed by Washington University 70mer oligos Chip gene array list
Mouse RET13K 12,765 (12,243 mouse clones + 522 controls) BMAP
Retinal
Library Dyer/Cepko lab		 cDNA Chip gene array list
Mouse M3 15,769 (15,247 mouse clones + 522 controls) NIA 15K mouse cDNA clone set cDNA Chip gene array list
microRNA (mouse, human and rat) miR10

4800 (1200 probes printed in quadruplicate on 1 slide)

Exiqon miRCURY LNA array probe set version 10.0

 oligo Chip gene array list
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