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'''Wiki for [http://linus.nci.nih.gov/BRB-ArrayTools.html BRB-ArrayTools] .'''
Shortcuts to some pages that may be useful to you!


== Features ==
{|
 
|style="width: 5%; border-width: 0px;"|[[File:Dna microarray45.png|link=Arraytools|BRB-ArrayTools]]||style="width: 20%; border-width: 0px;"|[[Arraytools|BRB-ArrayTools]]||style="width: 5%; border-width: 0px;"|[[File:linux48.png|link=Linux|Linux]]||style="width: 20%; border-width: 0px;"|[[Linux|Linux]]||style="width: 5%; border-width: 0px;"|[[File:R_logo48.png|link=R|R]]||style="width: 20%; border-width: 0px;"|[[R|R]]
=== Import from multiple data types ===
Expression data, Illumina methylation data, Copy number data (CGH-Tools), RNA-Seq count data processed through Galaxy web tool.
=== Sophisticated statistical analysis tools ===
Class comparison for differential expression, class prediction, graphical 2d and 3D interactive plots, gene set analysis, and more.
 
=== Comprehensive biological annotations ===
Gene ontology, pathways, protein domain, broad msigdb, lymphoid signatures, experimentally verified transcription factor targets, computationally predicted microRNA targets.
 
== Screenshots ==
 
==== [[File:ArrayTools GUI.png|100px]] BRB-ArrayTools graphical user interface ====
 
==== [[File:BRB_HeatmapDendrogram.png|100px]] Heatmap and dendrogram generated from the Pomeroy sample dataset. ====
 
==== [[File:BRB_3Dplot.png|100px]] Interactive MDS plot of samples from running the multidimensional scaling analysis on the Pomeroy dataset. ====
 
==== [[File:BRB_3Dplot2.png|100px]] Interactive 3D scatterplot of genes on the Pomeroy dataset.  ====
X-axis is from array 'Brain_MD_1', y-axis is 'Brain_MD_2' and z-axis is 'Brian_MD_3'.
 
==== [[File:BRB_Scatterplot.png|100px]] Interactive 2D scatterplot of samples with gene annotation from a selected gene using right click menu. ====
The right click menu gives an option to highlight up/down-regulated genes, export gene list, copy plot to clipboard, highlight genes in gene set, link genes among plots and change properties of the plot like title, point size, color of points, fold change threshold for up/down regulated genes.
 
==== [[File:VolcanoPlot.png|100px]] Interactive volcano plot from the output of running a class comparison tool.  ====
When you move mouse over a gene (point), the gene unique ID and/or symbol will be popped up.
 
==== [[File:QHeatmapScreenShot.png|100px]] Dynamic Heatmap Viewer ====
The screenshot was taken from running in Ubuntu OS. It has been incorporated in BRB-ArrayTools from version 4.4.0.
 
==== [[File:BRB_ClassComp.png|100px]] HTML output of running the class comparison analysis.  ====
 
==== [[File:BRB_sam.png|100px]] HTML output containing SAM plot from running the significance of microarray analysis.  ====
 
==== [[File:BRB_Prediction.png|100px]] HTML output of running the class prediction analysis.  ====
 
==== [[File:BRB_SRP.png|100px]] HTML output of running the survival risk analysis.  ====
 
==== [[File:BRB_samplesize.png|100px]] Result of sample size analysis.  ====
 
== FAQs  ==
 
=== General ===
 
==== How to install BRB-ArrayTools if you have 64-bit MS-Office? ====
There is no difference in terms of the installation.
 
==== After installation, I did not find the BRB-ArrayTools in Windows > Start > All Programs. ====
Check '''EXCEL'''. ArrayTools and CGHTools are under the Excel menu of Addon.
 
If you only see 'CGHTools' under the ADD-INS, it means you have skipped/ignored the screen of an instruction to the user. See the next item.
 
==== After open Excel, what options I need to do in Excel before using BRB-ArrayTools ====
Proceed the following no matter the BRB-ArrayTools' instruction to users is on screen or not.
 
(Office 2007)
Excel -> Home -> Options -> Trust Center -> Trust Center Settings -> Macro Settings -> Check 'Trust access to the VBA project object model' -> OK. Restart Excel.
 
(Office 2010 & 2013)
Excel -> File -> Options -> Trust Center -> Trust Center Settings -> Macro Settings -> Check 'Trust access to the VBA project object model' -> OK. Restart Excel.
 
Once Excel is restarted, it will ask to enter the email address you have registered with the BRB-ArrayTools. Then click the 'Activate' button. An Rserve app will be opened and sitting on the Windows' task bar. Do not worry about it. It will be used by BRB-ArrayTools and will be closed when the Excel is closed.
 
==== R installation directory ====
The default installation location for R software is OK. But if you use some other R packages like Rcpp, it is recommended to install R to C:\R folder.
 
<span style="color:#FF0000">'''Caution''': Do not open another instance of R when BRB-ArrayTools is working. This may make R packages installation/update impossible.</span>
 
==== R: Unable to install packages ====
If you see the following message
<pre>
Error in install.packages(update[instlib == l, "Package"], l, repos = repos,  :
  unable to install packages
</pre>
you want to check if you have a full privilege on R or R-x.x.x folder.
 
# Open Windows Explorer (Win + e), go to C:\Program Files
# Right click the 'R' folder ('R' folder is a parent of 'R-x.x.x' folder, so selecting it is better than selecting 'R-x.x.x'), choose 'Properties'
# Click 'Security' > 'Advanced'
# Click 'Owner' and select from the list to make sure the current user is the owner.
# Click OK button multiple times to finish the change.
 
==== Error: package 'X' required by 'Y' could not be found ====
The 'X' and 'Y' could be anything from CRAN or Bioconductor repository. One direct way to tackle the error is to open an R gui and install the missing packages manually. For example, if 'X' is 'preprocessCore' (a package in Bioconductor).
<source lang="rsplus">
source("http://bioconductor.org/biocLite.R")
biocLite("preprocessCore")
</source>
 
If the missing package is from CRAN, we can use '''install.packages()''' function directly.
 
==== Can I upgrade R or install multiple versions of R? ====
Better not for upgrading. Installing multiple versions of R is OK provided you know some details described below.
 
Each version of BRB-ArrayTools has been tested with a certain version of R. So there maybe a compatibility problem with certain functions used in the code if you decide to upgrade R.
 
* BRB-ArrayTools (before v4.3.0) requires StatconnDCOM which means the following conditions have to be satisfied:
** R needs to registered in the Windows's registry (it should be done if you accept all default options when R was installed).
** The R package 'rscproxy' has to be installed under the library folder the registered R. It cannot be installed under user's Document's folder as other R's packages.
 
* BRB-ArrayTools (from v4.3.0) requires Rserve package. That means
** Rserve has to be installed. It does not have to be installed under R\library folder.
** Rserve.exe from Documents\R\win-library\X.Y\Rserve\libs\i386 and Documents\R\win-library\X.Y\Rserve\libs\x64 subfolder has to be copied to C:\Program Files\R\R-X.Y.Z\bin\i386 and R\bin\x64 folder where X is the major, Y is the minor and Z is the patch number of R version.
 
If you need to use the latest version of R for your own analysis, you can still make it. First, install the latest version of R as usual. Then install again the full-version of BRB-ArrayTools. This will possibly install another version of R and register it in the Windows's registry for BRB-ArrayTools to use. Now you can enjoy both versions of R as you want. The idea is when you install R, it will by default register R, but this behavior can break the setting for R to be used by BRB-ArrayTools. Once you install BRB-ArrayTools, it will install an R it needs and not erase any other versions of R you already have.
 
==== How to upgrade Bioconductor ====
For example, my bioc is 2.12 which was first installed when I use R 3.0.1. But bioc 2.13 is the current version when R 3.0.2 was used. When I need to install a new package from bioc, the new package may requires a new version of bioc package.
<pre>
source("http://bioconductor.org/biocLite.R")
biocLite("BiocUpgrade")
</pre>
This command will upgrade all currently installed bioc related packages. ''But it seems it will install lots of other bioc packages I don't need''.
 
==== My institute is using a proxy server. So how do I do with BRB-ArrayTools ====
See the [http://65.123.194.80/phpBB3/viewtopic.php?f=3&t=580 message] on BRB-ArrayTools message board. Essentially we need to create a Windows environment variable '''http_proxy''' with a value like
<pre>
http://myproxy:myport
OR
http_proxy=http://username:[email protected]
OR
http_proxy=http://username:[email protected]:81
</pre>
 
==== RExcel-statconnDCOM gave an error ====
 
Please upgrade BRB-ArrayTools to v4.3.x where Rserve has replaced statconnDCOM.
 
==== Rserve ====
 
Since version 4.3.0, BRB-ArrayTools started to use Rserve as a media for the communication between R and Excel. When Rserve is required, an R window will be pop up. This R window has a blue icon on the Windows' taskbar. If you accidentally close it, it will be automatically popped up when it is needed.
 
See my [[Rserve]] wiki page.
 
==== Biological replciates vs technical replicates ====
When the same type of organism is grown/treated under the same conditions. Or if you repeat the experiment, and keep everything the same, it is a '''biological replicate'''.
 
When the exact same sample (after all preparatory techniques) is analyzed multiple times, it is called the '''technical replicates'''.
 
=== Importing ===
==== GDS from [https://www.ncbi.nlm.nih.gov/geo/ GEO (Gene Expression Omnibus)] ====
* If there is a GDS number, use GEO importer to import data (eg GDS1348). Expression data, experiment description and gene identifiers will be created automatically. BRB-AT downloads GDSxxx.soft.gz file from [ftp://ftp.ncbi.nih.gov/pub/geo/DATA/SOFT/GDS/ this ftp]/[ftp://ftp.ncbi.nlm.nih.gov/pub/geosup/Series/retired_datasets retired dataset] and GPL files from [ftp://ftp.ncbi.nih.gov/pub/geo/DATA/annotation/platforms/ ftp]. The <GDSxxxx.soft> file can be used to create <Experiment Descriptor file.txt> and <GDS1348.txt> files for BRB-AT. Note that dataset with GDS number contains experiment info. Individual Experiment (GSMxxxx) does not have experiment info. We can browse all GDS datasets from this [ftp://ftp.ncbi.nlm.nih.gov/geo/datasets/ ftp link].
* The [https://www.ncbi.nlm.nih.gov/sites/GDSbrowser DataSet Browser] (GEO -> Series -> DataSets) provides a table of curated datasets sorting by the GDS number. Currently it has 3848 dataset records. Each GDS does not have its own website though and the latest GDS 5093 has a GSE number on 2014/8/13. Since each GDS also a GSE number, we can compare the importing results from BRB-ArrayTools.
** A GDS may be only a subset of GSE series. For instance, GDS 5091 has 7 samples but its GSE 47516 series contains GDS 5089, GDS 5090, GDS 5091.
** It is possible to view the 'Experiment descriptors' for GDS data without downloading the gene expression data. To see that, click the 'Sample subsets' tab in the GDS browser.
** A list of all GDS data can be found on [http://gbnci.abcc.ncifcrf.gov/geo/gds.php GEOmetadb website] (not sync with GEO).
 
==== GSE from GEO ====
'''Note''':
* BRB-ArrayTools v4.5.0 provides a new tool to import GSE data using the Bioconductor GEOquery package. However, the data type GSE29135 is categorized as “Non-coding RNA profiling by array” instead of the [http://www2.warwick.ac.uk/fac/sci/moac/people/students/peter_cock/r/geo type] '''Expression profiling by array''' or '''gene expression array-based''', it was not considered as expression arrays.
* GSE series can be obtained from http://www.ncbi.nlm.nih.gov/geo/index.cgi and choose Browse Content|Series.
* Some GSE data has a GDS number too. For example GDS 2875 has a GSE 7810. To find the GDS number, we can use one of the following 2 ways:
** Click BioProject PRJNA 100031 -> Project Data, GEO DataSets Links 2 -> GDS 7810.
** Select gds in [http://gbnci.abcc.ncifcrf.gov/geo/gds.php GEOmetadb] page. Click Select Field 'GSE contains GSE7810' and hit the Search button. Some new data in GEO may not appear in the GEOmetadb website though.
 
The information provided below is for BRB-ArrayTools version up to v4.4.x.
 
You can go to GEOmetadb at http://gbnci.abcc.ncifcrf.gov/geo/ to extract sample information of your interest. This GEO microarray search tool makes access to metadata associated with NCBI GEO samples, platforms and datasets much more feasible.
Let us take [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29135 GSE29135] for example. Please try the following to extract sample information for this dataset:
# Go to http://gbnci.abcc.ncifcrf.gov/geo/ .
# Click on “GSE Search” link below "GEOmetadb Web Interface", and you will be directed to the GSE search page.
# Under "Select Filed:", select "GSE Acc" for the left drop-down list, type "29135" in the right box and then click on "search" button.
# Click on “25983” in the column “ID”. In the new page of “View GSE Details”, click on “Show GSM” button. This will show all the GEO GSM records of GSE29135 extracted from GEO.
# In this case, information of “GSM Acc” and “Title” from the table seems to be useful. To extract them, you can go click on “Display Options” and put only “GSM Acc” and “Title” fields in “Selected Fields” by removing the others using the left arrow button. Then click on “Change” button on the top right.
# Click on “Download Results” and save the .csv file. It contains three columns in this example, that is, ID, GSM Acc and Title. You may delete ID column manually since it is useless. Also, please replace the comma delimiter with the tab delimiter by using Notepad++ (a text editor for free downloading). By cleaning up the table and adding column names, the processed table should look like this:
<pre>
Experiment Names  Patient ID Stage    Subtype
GSM712531        101        IA        AD
GSM713230        107        Ib        AD
GSM713231        112        IA        Broncho-alveolar
GSM713236        175        IB        AD
GSM713237        147        IB        AD
…
</pre>
7. Save this table as .txt file. And this file can be used the experimental descriptor during importing.
If you are interested in other characteristics of the data set, you may go each GSM link and check  them out.
As for the gene information, please go to the platform GPL8179 page of GSE29135 at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL8179. You may take a look at  GPL8179_humanMI_V2_R0_XS0000124-MAP.txt.gz for information of your interest.
 
==== Other types from GEO ====
# If there is raw data, we can try to import them with data import wizard (eg GSE18170). We can use SOURCE to annotation data using 'Symbol' as the lookup key. Select 'Mouse' as the organism.
# If there is no raw data, we can use Serial matrix file with '''General Importer''' (eg GSE33403). Download GPL10481_family.soft.gz file and Extract it. Open the file in EXCEL. Copy the cells on rows from126 to 45346 and columns from A to I. Paste them to a new Workbook and save it in a tab-delimited format file called <SeriesMatrix.txt>. Download GSE33403_series_matrix.txt.gz file and extract it. Open it in EXCEL. Copy the data on rows from 75 to  45295 and columns from A to AN. Paste them to a new Workbook and save it in a tab-delimited format file called <GeneID.txt>.
 
==== Multiple chips (hgu133a and hgu133b) ====
GSE4922 contains two different array platforms (hgu133a and hgu133b). Starting from ArrayTools v4.1 our software does not support the importing of multi-chips any more. Therefore you cannot directly import all the data into BRB-ArrayTools to create one project with two different chips. However, you could import the data into ArrayTools as two different projects and output the normalized data for each project. Then you can manually combine the two output data files and re-import into BRB-ArrayTools as one project. Here is what you can do,
# Use Data Import Wizard to import the CEL files for hgu133a and hgu133b chips separately to create two projects.
# Open each project and then use the "Export 1-color data to R" plug-in (click on "ArrayTools -> Plugins -> Export 1 color data to R") to output your normalized data file along with the GeneId file.
# Under Excel, combine the normalized output files ("NORMALIZEDLOGINTENSITY.txt") from two projects. Add sample names in the first row and Probe Set Ids in the first column. Save this combined data file. Then combine the two "GENEID.txt" files manually to create one Gene ID file.
# Open Excel, Click on "ArrayTools -> Import data -> General format importer" to import the combined data file. Select your data as "Single-channel", "Affymetrix probeset-summary data". For the chip type, because your data contain probe sets from both hgu133a and hgu133b, almost all of which were included in the hgu133plus2 chip, you can just pick the hgu133plus2 as your chip type. Alternatively, if you do not wish to do this, you can check "I would like to use my own gene identifiers file rather than the one from bioconductor" and use the combined Gene ID file (done in step 3) for annotation.
# At the filter and normalization step, it is VERY IMPORTANT that you need to uncheck all the spot filter and normalization options, because your "raw" data file comes from already normalized data in two different projects. You do not want to re-run normalization. You can keep the options in "Gene filter" tab.
# At the end you can run annotation as your choice.
 
==== PrimeView importing failed on v4.3.0 beta1 (R 2.14.x) ====
# Go to http://www.bioconductor.org/packages/2.11/data/annotation/html/primeviewcdf.html and click on the link for the windows binary package "primeviewcdf_2.11.0.zip" and download the zipped package.
# Unzip the downloaded package and put the entire package folder "primeviewcdf" under your R2.14.2 library folder (default C:\Program Files\R\R-2.14.2\library).
 
However, you cannot run Affymetrix annotation using bioconductor annotation packages at the end of importing, because the annotation package for primeview array is not available at bioconductor. Another commonly use annotation database, SOURCE, has also been down these days. Instead you need to import your own annotation into BRB-ArrayTools. Here is what you can do,
# Download the primeview annotation file in CSV format from Affymetrix website (https://www.affymetrix.com/user/login.jsp?toURL=/support/file_download.affx?onloadforward=/analysis/downloads/na32/ivt/PrimeView.na32.annot.csv.zip).
# Open the CSV format file in Excel and then save it as a tab-delimited .txt file.
# Import your data in CEL file format into BRB-ArrayTools through Data Import Wizard. During importing, you need to check the option "Import your own identifiers file to annotate your data" at the "Probe Set Id options" page, and then Click on "OK". At the next dialog form you need to select the radio button "The identifiers are stored in a separate file" and browse for the tab-delimited file you just saved. The head line # for this file is 25. Then you need to select the corresponding gene identifiers column headers. You need to check the box "Annotate the project with these gene ids, instead of using the data from SOURCE database" before proceeding to the next page.
 
==== Affymetrix miRNA 2.0 or 3.0 ====
For Affymetrix miRNA 2.0 array [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL14613 GPL14613], eg GSE43592 (not for 3.0 array, [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL16384 GPL16384] search GEO by keywords miRNA 3_0, since there is no cdf package), you can import the data in CEL file format into BRB-ArrayTools through the CEL file importer (from Data Import Wizard). For miRNA 2.0 and 3.0 arrays, an alternative way is to use the '''Affymetrix expression console''' software to pre-process/normalize the CEL file data and obtain a tab-delimited probe-set summary data file to be imported into BRB-ArrayTools using the General format importer. The Affymetrix expression console software can be downloaded at the [http://www.affymetrix.com/estore/browse/level_seven_software_products_only.jsp?navMode=34000&productId=131414&navAction=jump&aId=productsNav#1_1 Affymetrix website]. Unlike what we do for the regular gene expression chips, '''BRB-ArrayTools currently does not support the generation of annotation information based on the microRNA ID''' (so gene set analysis cannot be run).
 
For now, the CSV format annotation file provided by Affymetrix can be opened in Excel and then saved as a tab-delimited .txt file, which can be used as a "Gene Identifiers" file for BRB-ArrayTools. When you import your data file into BRB, you can choose to "use your own gene ID file for annotation" and select the "Transcript Id (Array Design)" as the microRNA Id column header. Although we do not directly provide any annotation tools for miRNA data, if you run some particular analyses such as class comparison, there will be a hyperlink associated with the microRNA Id in your html output result file. By clicking on this link, you can be directed to the miRBase website with the annotation information associated with this particular microRNA Id.
 
==== Agilent miRNA ====
The arrays in the GSE41874 series were scanned by an Agilent scanner and data were extracted by the
feature extraction software, therefore the raw data files in this series are in the exactly
same format as the Agilent dual-channel .txt files. You can use Data Import Wizard and
choose "Agilent dual-channel data" to import the data into BRB-ArrayTools. However, you need to
select the following options:
 
# At the GeneID dialog form page, select the "GeneName" as the miroRNA ID, and select "None" as the Gene Symbol
# At the spot filtering step, use dye swap for all the arrays, as Cy5 was used as the reference for all arrays
# Also, please bear in mind that only some analysis tools can be used for this set of data, because annotation cannot be conducted on microRNA array data in BRB-ArrayTools. For instance, you can run class comparison and clustering with this data set, but cannot perform gene set enrichment analysis.
Although annotation is not provided, at the end of class comparison, the significant microRNAs can be
hyperlinked to the mirBase if you want to see detailed annotation of any particular microRNAs.
 
==== Gene ST 1.1 (or other than 1.0), Exon ST, or Affymetrix .cel files without cdf packages from Bioconductor ====
 
You will need to install Affymetrix Expression Console. Here is the link of Affymetrix Expression Console download website.
http://www.affymetrix.com/browse/level_seven_software_products_only.jsp?productId=131414&categoryId=35623#1_1
 
Here is the link where you could download Affymetrix Expression Console (64bit).
 
http://www.affymetrix.com/products_services/software/download/expression_console/expression_console_download_terms.affx?v=Release1.2.1.64bit
 
Take the mouse Gene 1.1 ST-array as an example on how to use the Expreesion console to convert .cel files into .txt files and then import .txt files into ArrayTools.
 
# Before downloading the Affymetrix expression console, you need to register at Affymetrix website. After downloading and installing the software, open Affymetrix expression console, name the profile and set a library path by clicking "Edit -> Set library path";
# After you download and install the software, please open it and then download both the '''library file''' and '''annotation file''' for mogene 1.1 ST-array in the software(File->Download Library Files and File->Download Annotation Files). 
# After you download both files, you could click on "File" -> "New study" to open the Affymetrix study window. Click on "Add intensity files" to browse for the CEL files of your interest. Click on "Run analysis".
# When the analysis is done, click on "Export" -> "Export Probe Set Results(pivot table) to TXT" to export a tab-delimited file, which is ready to be imported into BRB-ArrayTools.
# Go to the library path folder and open a file called "xxxx.annot.csv" in Excel. Save this file in tab-delimited .txt format as an annotation file for later use.
# You could start to use BRB-ArrayTools '''General Importer''' to read the summarization .txt file into ArrayTools. By default, the output expression values from Affymetrix Expression Console is already log 2 transformed. Please turn off all spot filters and normalization during importing in ArrayTools because RMA is already done by Affymetrix Expression Console.
# At the Gene ID dialog form, select "Gene Ids are stored in a separate file" and browse for the annotation file you created in step 5. Check the option "Annotate the project with these gene ids, instead of using the data from SOURCE database".
 
==== DNA Methylation ====
Staring from ArrayTools v4.3, the Illumina methylation data can be imported using the Data import wizard. Currently the following three chip types are supported: 1)  ''IlluminaHumanMethylation27k''; 2) ''IlluminaHumanMethylation450k'' and 3) ''GGHumanMethCancerPanelv1''.
 
The raw data file is a tab-delimited .txt file outputted from either ''BeadStudio/GenomeStudio'' software. It is required to have the following columns: 1) TargetID column and 2) The AVG_Beta column for each array. The beta value represents the proportion of methylated signal intensities among all intensities (methylated and unmethylated intensities) in each probe.
 
In addition, the file could contain columns for the signal intensity data of unmethylated and methylated probes, such as Signal_A and Signal_B, Signal_CY3 and Signal_CY5, or Signal_Red and Signal_Grn, for all samples.
 
The following 2 tables show the first sample and its first 3 probes.
<pre>
TargetID CAF549.AVG_Beta CAF549.Signal_A CAF549.Signal_B CAF549.Detection.Pval
cg00000292 0.303514376996805 5886 2565 3.68e-38
cg00002426 0.338360655737705 3027 1548 3.68e-38
cg00003994 0.0923276983094928 4886 497 3.68e-38
</pre>
and
<pre>
TargetID    08-132.AVG_Beta  08-132.Signal_A  08-132.Signal_B
cg00000029        0.6157420        2564.3650        4269.426
cg00000108        0.9355133        684.8924        11386.490
cg00000109        0.8333406        992.8285        5464.431
</pre>
 
The software continues to ask the user whether he/she wishes to use the '''lumi''' package to normalize the data. If the user answers “Yes” to the question, data will be quantile color balance-adjusted, quantile normalized and then converted to the M values (log2 ratios of methylated over unmethylated normalized signal intensities) using functions in the '''lumi''' package, otherwise data will be converted to log2(beta/(1-beta)) values.
 
If the raw data file does not contain the signal intensities of methylated and unmethylated probes, or if the chip type is ''Golden Gate'' based, data will be read in using the '''methylumi''' package, and will be converted to log2(beta/(1-beta)) values. No matter what chip type it is, or whether normalization has been applied, the processed data will be treated equivalent to log2 ratio data. 
 
For Illumina methylation data, there are 3 different options of annotation: 1) Annotate probes with the user’s own gene identifiers file; 2) SOURCE annotation and 3) Annotate probes with the annotation package available at Bioconductor. For options 1) and 2) the user is required to browse for their gene identifiers file, or specify the Gene identifier columns present alongside with the raw data file.
 
The first plot below shows the histogram of beta from one dataset. The second plot shows the relationship of beta vs M (M = log2(beta/(1-beta))).
 
[[File:Methybetahist.png|200px]] [[File:Methybetavsm.png|200px]]
 
In GEO, [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19711 GSE19711] contains an ovarian cancer data on 540 whole blood samples (Illumina Infinium 27k Human DNA methylation Beadchip v1.2) and [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42861 GSE42861] contains rheumatoid arthrotis data on 691 subjects (Illumina HumanMethylation450 BeadChip).
 
==== RNA-Seq RPKM/FPKM ====
ArrayTools -> Import Data -> Data Import Wizard -> RNA-Seq Data from Galaxy.
 
* http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49378
 
==== RNA-Seq raw count ====
ArrayTools -> Import Data -> RNA-Seq count data importer. If we choose the format of one text file, the whole flow is similar '''General Importer'''. However, the spot filter and normalization options will be grayed out in the 'Refilter, normalization and subset the data' dialog.
 
* http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE45419 Breast cancer data. 32 samples. Raw count & fastq data are available. BioProject says the Project Type is '''Transcriptome or Gene expression'''. Samples are from 4 categories that can be identified from the first column in the 'Experiment descriptors' of the ArrayTools project.
 
=== Annotation ===
==== SOURCE at stanford is down ====
During the period of time when SOURCE website is down, our users will not be able to import annotations from SOURCE database. The bioconductor annotation packages will still work for users having Affymetrix or Illumina array data. For non-Affymetrix and non-Illumina chip users who are creating new projects, here are a couple of alternative solutions,
 
* If the user has an existing annotated project with an identical chip type to the project he/she is creating, he/she can import the annotations from the existing project. This can be done by clicking on 'ArrayTools -> Utilities -> Annotate the data -> Import annotations from an existing project';
 
* If the user has an annotation file available, during the process of importing, the user can choose to import annotations from this file. At the step of selecting Gene Identifiers, the user can browse for the Gene Identifiers file and check the option 'Annotate the project with these gene ids, instead of using the data from SOURCE database';
 
* If the user does not have an annotation file, for most commonly used commercial chips, the annotation files can be downloaded from GEO database at NCBI. For instance, the annotation file for the Agilent-014850 Whole Human Genome Microarray chip can be downloaded at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL4133 by clicking on the 'Download full table' button. This downloaded annotation file can then be imported into BRB-ArrayTools following step 2).
 
==== Gene ST array annotation using aroma.affymetrix ====
The aroma.affymetrix can handle all single-channel Affymetrix chip types (they have a few multi-channel ones not supported), so my guess is that it is already supported.  What's required for nearly all aroma analysis, is to have a CDF annotation file that defines the units and unit groups, e.g. probe sets of transcripts and exons, SNPs and so on.
When Affymetrix is not providing a CDF, the challenge is to either find a custom CDF (e.g. BrainArray and GeneAnnot) or to create a one from the other types of annotation data they or Bioconductor provide, e.g. http://aroma-project.org/howtos.
 
==== Annotation with Bioconductor package ====
The tool search gene symbol, accession number, UGCluster and Entrez ID columns. See <AnnotationGenes.bas> for the source code.
 
==== Genes with multiple ids (such as “NR_024445,BC041041,AK093927”) ====
Only the first id was used in gene annotation.
 
==== An Example of a Gene Annotation ====
{| class="wikitable"
|-
| CloneID || 50188
|-
| LLID (=Entrez ID or GeneID) || 6047
|-
| ProbeID || AB000468_at
|-
| Symbol || [http://en.wikipedia.org/wiki/RNF4 RNF4]
|-
| UGCluster || Hs.66394
|-
|-
| RefSeq (=accession number) || NM_000844
|| [[File:tai-chi48.png|link=Tai_Chi|Tai Chi]] || [[Tai_Chi|Tai Chi]] || [[File:heart48.png|link=Health|Health]] || [[Health|Health]] || [[File:raspberry48.png|link=Raspberry|Raspberry Pi]]  || [[Raspberry|Raspberry Pi]]
|-
|-
| GenBank Accession || M97935
|| [[File:docker48.png|link=Docker|Docker]]
|| [[Docker|Docker]]
|| [[File:recipe48.png|link=Recipes|Recipes]]
|| [[Recipes|Recipes]]
|| [[File:statistics48.png|link=Statistics|Statistics]]
|| [[Statistics|Statistics]]
|-
|-
| GO || cellular component|nucleus|TAS|GO:0005634//cellular component|nucleus|IEA|GO:0005634
|| [[File:ubuntulogo48.png|link=Ubuntu|Ubuntu]]
|| [[Ubuntu|Ubuntu]]
|| [[File:vblogo48.png|link=Virtualbox|Virtualbox]]
|| [[Virtualbox|Virtualbox]]
|| [[File:beaglebone48.png|link=Beaglebone|Beaglebone]]
|| [[Beaglebone|Beaglebone]]
|}
|}


[[File:AT multi Genbank.png|300px]]
=== Analysis ===
==== Function analysis using [http://david.abcc.ncifcrf.gov DAVID] ====
See a tutorial from http://nihlibrary.ors.nih.gov/bioinfo/Microarray/Problem1.html
==== Best parameter or analysis to choose ====
Ask your local help desk.
==== For affy cel files, GCRMA has a memory problem and MAS5 is way too slow ====
It is a known problem for earlier versions of BRB-ArrayTools. The reason is statconnDCOM can only use 32-bit R. Since BRB-ArrayTools v4.3.0, a new engine 'Rserve' was adopted which can make use 64-bit R if the Windows OS is 64-bit. Therefore the memory issue for using GCRMA should be alleviated. (Update) The 64-bit OS still does not solve the memory problem; see a post and a workaround [https://groups.google.com/forum/#!topic/rgcb-omrf-microarray-data-analysis-workshop/35s4yMZ2vuU here] from google forum.
BRB-ArrayTools uses justGCRMA() function in 'gcrma' package for GCRMA option and justMAS() function in 'simpleaffy' package for MAS5 option.
==== GO ====
# Gene annotation worksheet is used in Utilities -> Create genelist -> GO description.
# Bioconductor's GO package is used when we run gene set (gene ongology) class comparison.
==== Two types of gene set analyses ====
* Tradition -- H1: set of genes differentially expressed among defined classes of samples. For example, the classes might represent samples from patients who respond to a treatment versus samples for patients who do not respond.
* Interaction analysis (compare enrichment in 2 groups of samples) -- H1: set of genes differentially expressed among classes is different for 2 pre-defined groups of samples. The groups might represent patients with different stages of disease.
=== R packages ===
==== Affy related packages ====
* GCRMA: install cdf, '''probe''', .db packages
* MAS5: install cdf, .db
==== Common download issue ====
Try to download/install manually in R console.
* '''lumi'''
<pre>
source("http://bioconductor.org/biocLite.R")
biocLite("lumi", ask=F)
library(lumi)
</pre>
* '''GO.db'''
<pre>
source("http://bioconductor.org/biocLite.R")
biocLite("GO.db", ask=F)
</pre>
* '''rtiff'''
<pre>
install.packages('rtiff',repos='http://cran.r-project.org')
library('rtiff')
</pre>
==== C:/Program Files/R/R-3.2.0/lib is not writable ====
The problem is caused by running another R session somewhere at the same time when BRB-ArrayTools is running.
[[File:RPackageWriting.png|100px]]
=== Users without Admin Privilege ===
# log in as the administrator and set up BRB-ArrayTools in Excel. Plus, I had to enter my email address for activation.
# log in as standard user and click the Go button for Manage Excel add-ins. Since BRB-ArrayTools add-in was still not showing up in the dialog box, I had to manually add it by clicking on the Browse button.
=== Foreign langauge users ===
==== Microsoft Office ====
Below are some of the recommendations we typical make to foreign language users:
1: Please, make sure that the regional language settings on your machine to the "English". You can do so by going to the Control Panel ->  Regional and Language Options and choose English.
2: From the Start  Programs  Microsoft office  Microsoft office tools -> ->"Microsoft Office language settings" and please make sure that the "primary editing language" is "English".  If the "Primary editing language" is not "English", please change it to "English" and then re-boot your machine.
If we don't want to change the setting to "English". The trick was to: in Excel Add-Ins, look for the add-ins among folders (in the German version: Durchsuchen) and to folder programs v 64 bit. Then it finds ArrayTools there, go to subfolder Excel and there it finds the Add-in. Otherwise it was invisible.
In the administrator system, allow British English keyboard,
And in Excel Options -> Advanced -> Change decimal to dot . and thousands to comma.
==== R ====
We have a report that R packages cannot be installed. If we answer 'yes' to the following question,
<pre>
--------------
Question
--------------
Would you like to create a personal library
'C:\Users\<U+C591><U+C0C1><U+D654>\Documents/R/win-library/3.1' to install packages into?
</pre>
we will get an error message:
<pre>
  unable to create 'C:\Users\<U+C591><U+C0C1><U+D654>\Documents/R/win-library/3.1'.
In addition: Warning messages:
In dir.create(userdir, recursive = TRUE) :
  cannot create dir 'C:\Users\<U+C591><U+C0C1><U+D654>', reason 'Invalid argument'.
</pre>
A similar report can be found on [https://stat.ethz.ch/pipermail/r-help/2014-December/424471.html R help mailing list].
See also [https://codepoints.net/U+C591 this] and [http://en.wikipedia.org/wiki/Hangul Wikipedia] for Korean char.
=== Quirks ===
* Do not place the project in a very deep path. Or you may get an error
<pre>
reads "Error in 'exportToR' function" and then reads "Data was not successfully exported to R. Plug-in script is now aborting." 
</pre>
* Do not include special characters (single/double quote, percent sign, etc), in the project name, output name, column header in the experiment descriptor worksheet. The special characters include * ? < > | = + ~ @ # $ % ^ & |. It is defined in <PublicFunctionProcedure.bas/CheckSpecialCharactersReturnBoolean>
* Do not sort the experiment descriptor worksheet.
* R's ''impute'' package tends to crash R when the number of genes is small.
* R's ''pamr'' package failed when the number of genes is only one. The error message is
<pre>
Error in rep(1, p) : invalid 'times' argument
</pre>
It is a bug in pamr.train() -> nsc().
* Write the R file used in plugins in a ''conventional'' format.
* Bioconductor package 'affxparser' does not work on Windows XP. The alternative is to use Affymetrix Expression Console to pre-process your ST arrays data and then import the .txt file that are outputted from Affymetrix Expression Console into ArrayTools by using the general format importer.
* Sometimes we need to delete the parameter file (under $ProjectFolder\BinaryData\DataParam) to solve a problem. For example, two projects were opened at the same time, or an analysis was broken during execution.
=== Run time errors ===
This is a collection of run-time errors from users' report or testings.
* error 1004: make sure the specified folder exists or file can be accessed.
* error 91: 'block variable not set'. It is rscproxy is not installed correctly. This should not happen again since rcom is no longer used.
* error 76: write permission, administrative privileges.
* error 75: write permission
* error 13: type mismatch. Special characters in files. Delete e.g. BinaryData\DataParam\ClassComparison.txt and run the class comparison again.
* error 9: subscription out of range. Variable name used in dialog is changed.
* error 5: invalid procedure call or argument.
* error '-2147319779' or '-2147221500': rscproxy package is not installed. This should not happen again since rcom is no longer used.
== Citing ==
* [http://www.citeulike.org/search/all?q=arraytools citeulike]
* [http://scholar.google.com/scholar?hl=en&lr=&scoring=r&q=BRB+ArrayTools&as_ylo=1900&btnG=Search google scholar]
== Plugins Developers ==
* Experiment descriptor is a data frame with numerical or character data type (no factor). So we shall take extra care for cell with NA (numerical data type) or blank (character data type) value.
* Gene identifier is a data frame with factor data type.
== Support ==
=== Send an email to [email protected] ===
Please provide enough information to us so we can understand the problem.
* If a bug report file was generated, be sure to send it to us.
* If the question is like 'what method or parameters should be choose to run my analysis', please consult other experienced people near you.
* Since the software depends on a couple factors like Windows operation system, MS-Office, R. Please provide us more detailed information about the software background including BRB-ArrayTools.
* When sending screenshots to us, please provide all error screenshots. If you only provide any random of them, it will create a misleading to us.
=== Check BRB-ArrayTools message board ===
https://secure.emmes.com/brbmessages/index.php
== MISC ==
=== [http://www.illumina.com/gsp/genomestudiohelp/default.htm Illumina Genome Studio] Manual ===
=== GEO ===
* [http://www.ncbi.nlm.nih.gov/geo/browse/?view=platforms&search=illumina&display=20&zsort=samples Illumina]. For example, the txt file <GSE13040_nonorm_nobkgd.txt> from [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13040 GSE13040] (Illumina MouseRef-8 v2.0 expression beadchip) is close but not the one BRB-ArrayTools requires. We can modify the header to satisfy AT's requirement.
=== Affymetrix SNP arrays and cnt file for copy number analysis ===
To use the ‘Platform special importer’ for Affymetrix SNP arrays, the user should run the Copy Number Analysis Tool (CNAT) software, and output the *.CNT files in a batch process, where one *.CNT file is produced for each SNP array that was performed.  The *.CNT output files should all be placed in one data folder, to be read by CGHTools.  The “ProbeSet”, “Chromosome”, “Position” and “Log2Ratio” data columns will be automatically extracted from each *.CNT file.
See also [http://doc.goldenhelix.com/SVS/latest/platform_notes.html#creating-cnt-files-using-the-affymetrix-cnat-batch-analysis-tool goldenhelix.com] for more about creating CNT files using the Affymetrix CNAT Batch Analysis Tool.
[http://www.affymetrix.com/support/technical/byproduct.affx?product=cnat Affymetrix] website contains some info about Chromosome Copy Number Analysis Tool (CNAT) software. [http://www.affymetrix.com/estore/partners_programs/programs/developer/whitepapers/automating_workflows.affx This site] provides links to command line tools to process 10K, 100K, and 500K (no SNP 5 or SNP 6) data from CHP file to CNT file. In fact, the tool download page [http://www.affymetrix.com/estore/partners_programs/programs/developer/tools/devnettools.affx here] even provides sample output for download.
We may obtain raw files of copy number data from [http://www.ncbi.nlm.nih.gov/geo/browse/ GEO] website by searching 'affymetrix' and '10k' under 'Platforms' tab as keywords.
Another approach is to use the [http://www.genome.umin.jp/CNAG_DLpage/files/CNAGdownload_list.html Copy Number Analyzer for Affymetrix GeneChip (CNAG)] software and then process the data file to obtain data files in tab-delimited .txt format, which can be imported into BRB-CGHTools through the '''General Importer'''.
=== CGHTools ===
The CGHTools has several tools (segmentation, gain/loss, Gistic, pathway).
Once segmentation has been run, it is OK to jump to gain/loss, Gistic or pathway analysis. These 3 analyses have no mutual dependencies.
The CGHTools manual said when inferred integer copy number is imported at the importing step, the pathway enrichment analysis can be conducted without segmentation being performed.
[[File:CGHTools Segmentation.png|200px]]
[[File:CGHTools GainLoss.png|200px]]
[[File:CGHTools Gistic.png|200px]]
[[File:CGHTools Pathway.png|200px]]
We can find some Copy number data from GEO. For example, the [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE46452 GSE46452] has the ''Experiment type'' '''Genome variation profiling by genome tiling array''' while [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26689 GSE26689] has an experiment type '''Genome variation profiling by array'''. [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE5013 GSE5013] from the [http://www.nature.com/nature/journal/v444/n7118/full/nature05329.html paper] has an experiment type '''Genome variation profiling by SNP array; SNP genotyping by SNP array'''. And [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11960 GSE11960] has an experiment type '''Genome variation profiling by SNP array'''. [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE35873 GSE35873] has a type '''Genome variation profiling by SNP array; Genome binding/occupancy profiling by SNP array'''.


Copy number variation and gene expression are related in ''[http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3441862/#!po=50.0000 Identification of genes with a correlation between copy number and expression in gastric cancer]'' where CGH data is in [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE33428 GSE33428] and gene expression data is in [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE33335 GSE33335]. Another study is in [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10744 GSE10744].
MC Li


[http://watson.nci.nih.gov/~sdavis/tutorials/CSHL2010/TCGA.html Some tutorial] created by Sean Davis.
-----

Latest revision as of 19:51, 6 July 2022

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