Part1: Agilent RNA Quality Check:
Part2: Microarray - Before you start:
Part3: Microarray - After you got the result:
Part1: Agilent RNA Quality Check:
How much RNA do you need for quality check?
Answer: Please give us 3 µl of RNA samples in 0.5 tubes. (Only 1 µl is needed
to run the check, but we might need to rerun the sample in case it didn’t run well
the first time.)
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What’s the detectable range of RNA concentration for the RNA
quality check?
Answer: On Nano Chip: total RNA: 5-500 ng/µl; mRNA: 25-250 ng/µl.
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What to look for in the Agilent RNA Quality Check result?
Answer:
For information about the RNA Ladder we are using. Check here : http://www.ambion.com/techlib/spec/sp_7152.pdf
For total RNA:
RNA quality: the ratio for rRNA 28s/18s is a indication of RNA quality. The idea ratio
is 2, a low ratio is a indication of degradation of the total RNA. On the gel image and
the graph, the 28s and 18s should show up as 2 sharp bands.
RNA concentration: Agilent RNA quality check can give you an estimate of the RNA
concentration. If concentration is what you concerned about, double check it on a spec.
For mRNA:
rRNA contamination: the percentage of rRNA in your sample. The idea number is <5.
RNA concentration: Agilent RNA quality check can give you an estimate of the RNA
concentration. If concentration is what you concerned about, double check it on a spec
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Part2: Microarray - Before you start:
General:
What is DNA Microarray and how it helps with cancer
research?
Answer : Please check this ppt presentation.
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I’m a first time user,can I get some help on
experiment design?
Answer : Before submitting samples for microarray experiments, Duke
investigators are encouraged to make an appointment with Dr. Holly Dressman (668-1583 or dress002@mc.duke.edu) to discuss experimental
design and the types of microarray technologies that are available to the user through the
Duke Microarray Core Facility. It is important to begin a microarray experiment with a
proper question that is well defined with independent experimental verification.
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Why do you need replicas in experiment design?
Answer: Replication is important because it offers statistical power that
enables you to find real differences between experimental groups. With adequate
replication, "real" differences in levels of gene expression can be
distinguished from differences caused by random variation. Without replication, it is
difficult to know whether observed differences are real or random. Statistical precision
enables you to accurately characterize gene expression for a particular experimental unit.
With adequate replication, you get a more accurate “overall” picture of
expression. Without replication, you have more random variation, leading to a less
accurate picture and no way to fully characterize the uncertainty in the data.
Sources of variation:
| Biological Variation Between… |
Processing Variation Caused By… |
Strains |
Quality of the Experimental Sample |
Animals |
Labeling Effects |
Tissues |
Hybridization Effects |
Time |
Background Effects |
How many replicates are needed?
There is no simple guidance on the number of replicates needed. A minimum of four or
five replications for each experimental condition and/or time point is a good starting
point, however, more may be needed to achieve the goals of many experiments. Some general
guidance follows:
More replication is needed for… |
Less replication is needed for… |
| Finding small differences in genes expressed at modest levels
|
Finding gross patterns among highly expressed genes |
| Experiments using tissue samples |
Experiments using cell line samples |
| Experiments with no confirmatory testing |
Experiments incorporating confirmatory testing such as
Northern blots or Real-Time PCR |
Standard statistical methods support sample size calculations to determine how many
samples are needed to detect a specified difference between groups with a required level
of power. In concept, this can be done for microarray experiments too. However, sample
size calculations are based on a known level of variation between samples. For
microarrays, the reality is that:
(a) The expected level of variation is usually not well known in advance. Due to the
high cost of microarrays and the large number of samples needed to accurately assess
variance, it is usually not practical to follow the common statistical practice of
gathering “pilot” data for the purpose of estimating variability.
(b) Variation between samples can differ for different genes, so the ideal number of
replicates may differ as well. This makes it impossible to have a single rule that works
in general, without applying some simplifying assumptions.
Does pooling RNA count as replication?
NO!
A common practice involves pooling RNA from several experimental units (e.g. animals)
in an effort to achieve more representative results. While pooling RNA in a replicated
experiment may indeed improve statistical power and precision due to less variation across
samples, pooling RNA is not a substitute for replicating an experiment. For instance:
The practice of pooling RNA does not in itself provide a way to characterize random
variation in the experiment, so replication is still needed to distinguish
“real” differences.
Pooling RNA can distort results if, for example, a particular experimental unit is
problematic and contributes a misleading expression pattern that skews the results.
Pooling RNA precludes the investigator from observing potentially interesting patterns
in behavior across different animals or other experimental units.
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How should I prepare my samples?
A number of RNA isolation methods are available to
generate high-quality RNA for use in microarray experiments. We suggest using the Qiagen
RNeasy kits for total RNA and the Qiagen Oligotex kits to isolate polyA+ RNA. Isolating
polyA+ RNA is not required, but can produce consistent results because the isolation acts
as a clean up step to remove residual DNA and protein contamination that may be present in
varying amounts in total RNA samples. Trizol may also be used for RNA isolation, however
it is strongly recommended that during the extraction, do not remove any of the biphase
layer (could introduce protein contaminants) and then clean up the RNA with the Qiagen
RNeasy columns.
And here's a couple of tips about working with RNA:
- When working with RNA, remember to protect the
RNA at all stages, and in particular take the following precautions and quality assurance
steps:
- Autoclaving WILL NOT kill RNases,
since they are quite stable, so use only RNase & DNase free tubes and aerosol filtered
pipette tips.
- Use only RNase free H2O in all
reactions. Use commercial sources if possible.- Wear powder free latex gloves, and change
gloves often (powder can hurt the microarray images)
- Use RNaseZap (Ambion) to clean the
workbench and pipetters before setting up reactions- Try to obtain the freshest sample
possible from tissues and cell cultures
- Keep tissue samples in liquid
nitrogen or dry ice immediately after surgical removal and keep on wet ice until then, and
store at -80C.
- Process only small pieces of tissue
(a few 100 milligrams) for fast homogenization- Spin down homogenized mixture and extract
only the clear upper layer for further processing, to eliminate unwanted components when
using Trizol.
- Avoid over-drying the final RNA
pellet, since RNA is difficult to dissolve.
- Redissolve RNA pellet in RNase free
H2O at 60-70 C for 10 minutes.
- Check RNA quality by running out on
an agarose gel, and look for two strong, not smeared ribosomal bands (28S and 5S), with
the upper band brighter than the lower. However, the Microarray facility will always
check the quality of RNA submitted on an Agilent Bioanalyzer before proceeding with probe
preparation.
- OD the samples and look for
A260/A280 ratios of: for Total RNA: ratio 1.5-1.8, and for mRNA: ratio > 1.8-1.9 (above
2.0 is excellent). note: If these ratios are not attained: attempt additional
cleanup with the Qiagen RNeasy kit, or repeat extraction using a new sample.
- Always store RNA at -80C; for long
term storage (> 6 months) suspend RNA in 70% ethanol and store at -80C.
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For Spotted Microarray:
What is spotted DNA microarray?
Answer : In this approach, distinct DNA fragments (cDNA or oligonucleotides) are
attached as an array of distinct spots on a suitably treated glass microscope slide via a
mechanical robotic spotting process. Two distinct probe DNA or mRNA mixtures - the
reference and the test sample - are given fluorescent red and green labels and are
combined in solution and applied to the array. The relative amounts of red and green
fluorescence at each spot provide a measurement of the relative numbers of red and green
labeled fragments attached at the spot, and thus of the relative numbers of fragments in
the reference and test samples. The two-color system requires a compatible pair of dyes.
The most commonly used are the Cy5 (Red) and Cy3 (green) fluorescent dyes. These dyes are
relatively bright, stable, and they fluoresce when dry, so that the hybridized arrays can
be fluorescently imaged in a dry state. On the other hand, these are patented, proprietary
dyes, and their cost accounts for more than half of the cost of a spotted microarray
experiment.
The probe typically consists of red fluorescently labeled mRNA (or, more commonly, the
corresponding cDNA produced by in vitro reverse transcription) extracted from a test
sample, and a green fluorescently labeled cDNA from a reference sample. These labeled
probes are mixed in solution and hybridized to the array. Unbound probe is washed away,
and the result is scanned by a fluorescent imaging system to yield red ( upregulated),
green (downregulated) and yellow (no difference) intensity measurements from each spot on
the array. The ratio of these red and green intensities - suitably normalized - provides a
measure of the change in mRNA levels between the test and reference populations, and thus
of relative levels of gene expression in the test and reference sample. Compared to
traditional techniques, this procedure is analogous to simultaneously carrying out
thousands of Northern blots. Type of sample comparisons and experimental design used in
for data analysis include direct and indirect comparisons, these are briefly mentioned
below.
i . Direct comparisons include the basic comparative measurement for comparison of two
samples. A reference sample is tissue or a cell line that is an "normal" state,
and the test sample if from the same type of cells in a diseased or otherwise altered
state. In this case, the red/green ratio provides a direct comparison of the expression in
the normal and altered cells for each gene on the array.
ii. Another type of comparison includes the indirect sample comparison. To make all
direct comparisons between N samples requires on the order of NxN comparisons, which gets
large quickly. Instead, to compare or characterize many test samples, it is convenient to
compare each one to a universal reference sample. This can be any mix of DNAs that
reliably and repeatably light up most spots on the array (so that the red/green ratio is
meaningful at each spot), and is available in large enough quantities to use the same
batch for many experiments. Convenient reference samples can be made for mixes of RNAs
from several specific cell lines or tissues. In this approach, all test samples are
hybridized to the reference sample, and compared to each other only indirectly using the
results of their experimental comparisons to the reference.
Also check the spotted array part in this powerpoint
presentation.
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What spotted Microarrys are available in the
center? Can I get a genelist for available arrays?
Answer: Please to go our spotted array page (http://mgm.duke.edu/genome/dna_micro/core/spotted.htm), where you can
find the table of available arrays. You can download the genelist for all available arrays
there.
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What’s the price for all the spotted Microarrays?
Answer: Please go to our spotted array page (http://mgm.duke.edu/genome/dna_micro/core/spotted.htm) , where you can
find a price table which contains price for all the service we have.
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How much RNA is needed to run a spotted Microarray?
Answer: 10-25 ug for total RNA in 10 µl RNase-free water, or 1-3 ug of mRNA in
10 µl RNase-free water. We also need to do Agilent RNA quality check before labeling and
hyb. So please also provide us same samples, sample concentration 3ul in seperate tubes.
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What should I put in the submission form for cy5 and
cy3 samples?
Answer: Generally you’ll put your samples on one channel (usually cy5) and
put reference RNA on the other channel (usually cy3). The relative intensity signals are
presented as a ratio cy5/cy3 in the result file. For Human, Mouse and Rat we have
universal reference RNA from Stratagene. For other organisms you have to provide your own
reference RNA.
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For Affymetrix Microarray:
What is Affymetrix GeneChip array?
Answer: The Affymetrix GeneChip system provides an approach to comparatively
analyze genome wide patterns of gene expression using a technology that incorporates
miniaturized, high density arrays of 25mer oligonucleotide probes. The probe arrays are
manufactured by Affymetrix's proprietary, light directed chemical synthesis process, which
generates high density arrays of oligonucleotides that possess a predefined position on
the array. These arrays are used to monitor gene expression for thousand of transcripts. A
transcript is represented as a probe set. A probe set is made up of probe pairs comprised
of a perfect match (PM) and a mismatch (MM) probe cells. This probe pairing strategy
identifies and minimizes the effects of non specific hybridization and background signal.
The intensities of each probe pair are used to determine the expression measurement. This
measurement is calculated for each probe set and is described in the form of qualitative
and quantitative values using the Microarray Analysis Suite, version 5.0.
Briefly, target preparation involves starting with at least 10 micrograms of total RNA
or 2 micrograms of poly A mRNA from tissue or cells. An invitro transcription reaction is
then performed to produce a biotin-labeled cRNA from the cDNA. The cRNA is fragmented
before hybridization and a hybridization cocktail is prepared that contains the fragmented
cRNA, probe array controls, BSA and herring sperm DNA. The cRNA is hybridized to the
oligonucleotide probes on the array for 16 hours at 45 C. Immediately following
hybridization, the hybridized probe arrays undergo an automated washing and staining
protocol on the fluidic station and then scanned on the Hewlett Packard GeneArray scanner
where patterns of hybridization are detected. The hybridization data are colleced as light
emitted from the fluorescent reporter groups already incorporated into the target, which
is now bound to the probe array. Probes that perfectly match the target generally produce
stronger signals than those that have mismatches. The scanner acquires an image of each of
the probe cells and the computer workstation automatically overlays two scanned images and
averages the intensities of each probe cell for the greatest array sensitivity. Data
generated from the scan is then analyzed using the Microarray Analysis Suite, version 5.0.
Also check the affymetrix array part in this powerpoint
presentation.
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What’s the price for all Affymetrix arrays?
Answer: Duke investigators must purchase arrays and bring to facility when
submitting samples. To determine the costs for probe synthesis, hybridization, and
analysis of Affymetrix arrays, please contact Holly
Dressman . (Based on the volume of use, Duke investigators receive a considerable
discount on the price of Affymetrix GeneChip arrays.)
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What Affymetrix Microarrys are available? Where to get
genelist for available arrays?
Answer: Go to www.affymetrix.com
to view the various genechips available. For gene lists, go to “Additional
Support” under each chip to download genelists.
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How much RNA do I need to prepare for Affymetrix
Microarray?
Answer: 5-10 ug of total RNA in 10 µl RNase-free water; 1-3 ug of mRNA in 10
µl RNase-free water; 15 ug of fragmented RNA in 40 µl. For total RNA we also do Agilent
RNA quality check, so please also bring 3ul aliquots in seperate tubes.
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Microarray - After you got the result:
What options do I have for data analysis after I receive
the result?
Answer:
Do analysis yourself. We can help you with any “Supported Analysis Software”
( check our analysis page http://mgm.duke.edu/genome/dna_micro/core/analysis.htm')
Ask us to do analysis for you. Please make an appointment with Dr. Holly Dressman
(668-1583 or dress002@mc.duke.edu )
You also can try the bioinformatics core: http://www.dbsr.duke.edu/
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What are those numbers in the summary file I
received for spotted array result?
scan date: the date your arrays were scanned.
Genome ID: the system we use to track individual hybridizations. Every sample should
have a distinct genome ID.
Array: the array you are using. e.g. MO30K means it's Mouse array; the oglios are from
Operon; the size is 30K genes.
Sample: sample name. cy5 sample name vs cy3 sample name
635 Signal/Background: the signal to background ratio for the cy5/635 channel. should
expect this number to be above 2.
532 signal/background: the signal to background ratio for the cy3/532 channel. should
expect this number to be above 2.
635 background: the average (mean of median) background intensity for cy5 channel,
should expect this number to below 200, most time below 100.
532 background: the average (mean of median) background intensity for cy3 channel,
should expect this number to below 200, most time below 100.
635 signal/noise: the median of signal to noise ratio for cy5 channel, should expect
this number to above 2, higher than 5 means the cy5 sample hybridized very well.
532 signal/noise: the median of signal to noise ratio for cy3 channel, should expect
this number to above 2, higher than 5 means the cy3 sample hybridized very well.
PMT 635: the laser power we used to scan the cy5 channel, usually 400-700.
PMT 532: the laser power we used to scan the cy3 channel, usually 400-700.
F635 Median: the median foreground intensity for cy5 channel, usually 300 and up.
F532 Median: the median foreground intensity for cy3 channel, usually 300 and up.
not found: the percentage of not found features -- the percentage of spots didn't get
hybridized. Depend on samples you have and which array you are working on. If it's below
25%, means alomst all the genes on that array were detected in your samples (can be from
either the cy5 sample or cy3 sample, or both.)
cy5 RNA concentration: the start Cy5 sample concentration we tested on Nanodrop.
cy3 RNA concentration: the start Cy3 sample concentration we tested on Nanodrop.
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What are the result files for spotted array? What
each column in .gpr files mean?
Answer: Data acquisition is performed using the Axon GenePix Pro 4000A
interface. Axon GenePix scanner refers to spots on an array as a feature. There are two
dyes used in the hybridization, Cy5 and Cy3. Cy5 is scanned at a wavelength of 635 and
fluoresces the color red. Cy 3 is scanned at wavelength 532 and fluoresces green. The Axon
GenePix software refers to the intensities of the spots by the wavelength at which they
are scanned. The Duke Microarray Facility calculates all ratios as intensity of Cy5 signal
(red) / Intensity of signal Cy3 (green). If a ratio is equal to 2, then the expression of
the feature was twice as high in the Cy5 labeled sample when compared to the Cy3 labeled
sample. The same type of logic holds true when the intensity of the Cy3 signal is greater
than the intensity of the Cy5. The ratio would be represented as a number less than 1.
For each array experiment that is completed, five files are generated. Each file will
be named identical except for the extension. The naming convention is as follows:
Project ID number_Genome ID number_slidenumber_slidelot_chip
type_Cy5sample_Cy3sample (i.e. 0089_477_001_01_HO21K_ko_wt.*)
| Extension |
Description |
Comments |
| *.TIFF (635nm and 532nm) |
Image file, picture of scanned array |
Can be viewed in Photoshop and Powerpoint |
| *.GPR |
Tab- deliminated text file with the raw data, see table below
for content. |
Can be opened in Excel to manipulate |
| *.JPG |
Shows the array image with both channels overlaid |
Can open in any operating system |
| *.GPS |
Gene Pix Settings File, acquition, analysis and display
settings are saved as binary GenePix settings files. Settings are organized into several
different categories (acquisition, display, and analysis) all of which are saved together
in the GPS file. This file contains block and feature geometry, and can be used to apply a
grid template to an image. |
Used with the Axon GenePix software |
The data analysis out put file is the *.GPR file. A description of each column in the
GPR file are listed below:(info from http://www.axon.com/gn_GPR_Format_History.html)
| Column Title |
Description |
| Block |
the block number of the feature. |
| Column |
the column number of the feature. |
| Row |
the row number of the feature. |
| Name |
the name of the feature derived from the Array List (up to 40
characters long, contained in quotation marks). |
| ID |
the unique identifier of the feature derived from the Array
List (up to 40 characters long, contained in quotation marks). |
| X |
the X-coordinate in µm of the center of the
feature-indicator associated with the feature, where (0,0) is the top left of the image. |
| Y |
the Y-coordinate in µm of the center of the
feature-indicator associated with the feature, where (0,0) is the top left of the image. |
| Dia . |
the diameter in µm of the feature-indicator. |
| F635 Median |
median feature pixel intensity at wavelength #1 (635 nm). |
| F635 Mean |
mean feature pixel intensity at wavelength #1 (635 nm). |
| F635 SD |
the standard deviation of the feature pixel intensity at
wavelength #1 (635 nm). |
| F635 CV |
the coefficient of variation of feature pixel intensity. |
| B635 |
the actual background value used for the feature in GenePix
Pro calculations (as opposed to B635 Median, for example, which is the local median
background.) This column is required because GenePix Pro 5.0 has global and negative
control background subtraction methods. If you choose a non-local method, B635 is
different to B635 Median |
| B635 Median |
the median feature background intensity at wavelength #1 (635
nm). |
| B635 Mean |
the mean feature background intensity at wavelength #1 (635
nm). |
| B635 SD |
the standard deviation of the feature background intensity at
wavelength #1 (635 nm). |
| B635 CV |
the coefficient of variation of background pixel intensity. |
| % > B635 + 1 SD |
the percentage of feature pixels with intensities more than
one standard deviation above the background pixel intensity, at wavelength #1 (635 nm). |
| % > B635 + 2 SD |
the percentage of feature pixels with intensities more than
two standard deviations above the background pixel intensity, at wavelength #1 (635 nm). |
| F635 % Sat. |
the percentage of feature pixels at wavelength #1 that are
saturated. |
| F532 Median |
median feature pixel intensity at wavelength #2 (532 nm). |
| F532 Mean |
mean feature pixel intensity at wavelength #2 (532 nm). |
| F532 SD |
the standard deviation of the feature intensity at wavelength
#2 (532 nm). |
| F532 CV |
the coefficient of variation of feature pixel intensity. |
| B532 |
the actual background value used for the feature in GenePix
Pro calculations (as opposed to B532 Median, for example, which is the local median
background.) This column is required because GenePix Pro 5.0 has global and negative
control background subtraction methods. If you choose a non-local method, B532 is
different to B532 Median |
| B532 Median |
the median feature background intensity at wavelength #2 (532
nm). |
| B532 Mean |
the mean feature background intensity at wavelength #2 (532
nm). |
| B532 SD |
the standard deviation of the feature background intensity at
wavelength #2 (532 nm). |
| B532 CV |
the coefficient of variation of background pixel intensity. |
| % > B532 + 1 SD |
the percentage of feature pixels with intensities more than
one standard deviation above the background pixel intensity, at wavelength #2 (532 nm). |
| % > B532 + 2 SD |
the percentage of feature pixels with intensities more than
two standard deviations above the background pixel intensity, at wavelength #2 (532 nm). |
| F532 % Sat. |
the percentage of feature pixels at wavelength #2 that are
saturated. |
| Ratio of Medians |
the ratio of the median intensities of each feature for each
wavelength, with the median background subtracted. |
| Ratio of Means |
the ratio of the arithmetic mean intensities of each feature
for each wavelength, with the median background subtracted. |
| Median of Ratios |
the median of pixel-by-pixel ratios of pixel intensities,
with the median background subtracted. |
| Mean of Ratios |
the arithmetic mean of the pixel-by-pixel ratios of pixel
intensities, with the median background subtracted. |
| Ratios SD |
the standard deviation of pixel intensity ratios. |
| Rgn Ratio |
the regression ratio. |
| Rgn R² |
the coefficient of determination for the current regression
value. |
| F Pixels |
the total number of feature pixels. |
| B Pixels |
the total number of background pixels. |
| Circularity |
a measure of circularity from 0 to 100, using a metric based
on the variance of the distance of each boundary pixel to the centroid of the feature: 100
is most circular, 0 is most non-circular. Circular features always have a circularity of
100, square features always have a circularity of 79 (= p/4*100). |
| Sum of Medians |
the sum of the median intensities for each wavelength, with
the median background subtracted. |
| Sum of Means |
the sum of the arithmetic mean intensities for each
wavelength, with the median background subtracted. |
| Log Ratio |
log (base 2) transform of the ratio of the medians. |
| F635 Median – B635 |
the median feature pixel intensity at wavelength #1 with the
median background subtracted. |
| F532 Median – B532 |
the median feature pixel intensity at wavelength #2 with the
median background subtracted. |
| F635 Mean – B635 |
the mean feature pixel intensity at wavelength #1 with the
median background subtracted. |
| F532 Mean – B532 |
the mean feature pixel intensity at wavelength #2 with the
median background subtracted. |
| F635 Total Intensity |
the sum of all pixel intensities in the feature. |
| F532 Total Intensity |
the sum of all pixel intensities in the feature. |
| SNR 635 |
the signal-to-noise ratio of the feature,
calculated as (F635 Mean - B635 Mean) / B635 SD. |
| SNR 532 |
the signal-to-noise ratio of the feature, calculated as (F635
Mean - B635 Mean) / B635 SD. |
| Flags |
the type of flag associated with a feature. |
| Normalize |
Arial'>a Arial'> flag column describing if the feature
was used to calculate the normalization factors (1 for used, 0 for not used). |
| Autoflag |
reports whether or not a feature has been flagged from the
Flag Features dialog box. It applies to good and bad flags only. |
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What are those result files for Affymetrix array?
Which one should I use for which analysis program?
Answer: For each array experiment that is performed using the Affymetrix
GeneChip arrays, six files are generated (*.DAT, *.CEL, *.CHP, *.EXP, *.RPT, *.txt). Each
file will be named identical except for the extension. The naming convention is as
follows:
Project ID number_Genome ID number_chip type_sample name (i.e. 0089_1212_HU95A_wt.*
In the case of pairwise comparisons in the Affymetrix Microarray Suite v5.0, the
comparison files will follow the following naming convention:
Sample_base_Sample_exp.txt
The types of extensions are as follows:
| Extension |
Description |
Comments |
| *.DAT |
Scanned image of the GeneChip array |
Can only be opened in Microarray Analysis Suite |
| *.CEL |
Cell intensity file that calculates the average intensities
for each cell and assigns it to an x,y coordinate position |
Can be opened in Excel to manipulate |
| *.CHP |
Contains analysis output |
Can only be opened in Microarray Analysis Suite |
| *.EXP |
Contains experimental information |
Can only be opened in Microarray Analysis Suite |
| *.RPT |
Contains quality control information about the chip |
Can be opened in Excel to manipulate |
| *.txt |
Contains analysis output |
Can be opened in Excel to manipulate |
All data analyses will be given as *.txt files. A description of the Microarray
Analysis Suite 5.0 is provided here.
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