500K Data Analysis Workflow using BRLMM

Transcription

1 500K Data Analysis Workflow using BRLMM I. INTRODUCTION TO BRLMM ANALYSIS TOOL... 2 II. INSTALLATION AND SET-UP... 2 III. HARDWARE REQUIREMENTS... 3 IV. BRLMM ANALYSIS TOOL WORKFLOW... 3 V. RESULTS/OUTPUT FILES... 7 VI. ADDITIONAL INFORMATION AND SUPPORT... 8 For research use only. Not for use in diagnostic procedures. Trademarks Affymetrix,, GeneChip, HuSNP, GenFlex, Flying Objective, CustomExpress, CustomSeq, NetAffx, Tools To Take You As Far As Your Vision, The Way Ahead, Powered by Affymetrix, GeneChip-compatible, and Command Console are trademarks of Affymetrix, Inc. Copyright 2006 Affymetrix, Inc. All Rights Reserved.

2 I. INTRODUCTION TO BRLMM ANALYSIS TOOL The Affymetrix BRLMM Analysis Tool software package implements the BRLMM genotype calling algorithm for Affymetrix genotyping arrays such as the GeneChip Human Mapping 500K Array Set. BRLMM (pronounced B-realm ) is an evolution of the RLMM genotype calling algorithm (Rabbee, N. and Speed, TP. Bioinformatics Jan 1;22(1):7-12). BRLMM performs a multiplechip analysis fitting probe effects to increase precision on signal estimates for the two alleles of each SNP, followed by a Bayesian classification approach to make genotype calls. The details of the model and typical performance are described in full in a white paper ( BRLMM improves overall performance (call rates and accuracy) and equalizes the performance on homozygous and heterozygous genotypes. It provides a simple-to-use Graphical User Interface (GUI) to run the BRLMM method on Microsoft Windows. The general workflow is described in Figure 1. Figure 1 BRLMM Analysis Tool General Workflow II. INSTALLATION AND SET-UP The installer can be downloaded from: After installing the BRLMM Analysis Tool, launch the tool from Start/Programs/Affymetrix/BRLMM Analysis Tool. To uninstall, go to control panel, add or remove Programs. The following input files that are required to run BRLMM Analysis Tool. Download and install the appropriate library file(s) and chromosome X SNP files(s) ( The default location for library files is the Affymetrix Library folder (c:\program

3 Files\Affymetrix\GeneChip\Affy_Data\Library). Place the chromosome X file(s) in the Library directory. There are separate chromosome X SNP files for each array type, Nsp and Sty (e.g. Mapping250K_Sty.chrx). For 100K: Note: This version has been tested on the 500K, 500K EA, and 100K commercial Mapping arrays. III. HARDWARE REQUIREMENTS Hardware Requirements: The recommended computer requirements are 3.6 GHz Intel Pentium 4 Processor with 2 GB Ram and 250 GB local disc storage. Such a machine can process 100 CELs in 1-2 hours. Details on these requirements are as follows: Processor speed: There is no strict limit on processor speed, the faster the processor the faster the analysis. For decent performance we recommend a 3.6 GHz Intel Pentium 4 processor. Memory: BRLMM performs a multiple chip analysis and requires substantial memory (RAM). Ideally it will try to run the entire job in the available memory, if not enough memory is available to run the whole job at once it will break the analysis into smaller pieces that will fit in memory at the cost of reading CEL files multiple times. Quitting other programs will also help. As a benchmark, processing 100 Mapping 500K CELs requires about 1G of RAM, when added to the typical 0.5-1G of RAM required by a typical operating system this means a minimum requirement of 2G of RAM for analyzing 100 CELs. Storage: Note that while it is possible to run BRLMM on CEL files that are located on a network drive, it can be a significant hit on processing speed. This can be a particularly big hit if the analysis is too big to fit into the available memory all at once, in which case BRLMM will divide the job into smaller pieces and read the CEL files multiple times. For speed considerations it is advisable to ensure the CEL files are on local disk. A local hard disk of 250 GB will be sufficient to comfortably analyze datasets on the order of hundreds of CELs. This package has been verified on Microsoft Windows XP service pack 2 per the configuration below: Processor: 3.6 GHz Intel Pentium 4 Memory: (RAM) 2-4 GB Disk Drive Storage: 250 GB 7200 RPM SATA Operating System: Microsoft Windows XP Professional SP2 Example System: Dell OptiPlex GX620 DT IV. BRLMM ANALYSIS TOOL WORKFLOW Prior to analyzing CEL files with BRLMM Analysis Tool, evaluate the performance using GTYPE and DM algorithm at default 0.33 confidence threshold (Figure 1, Step 1). Samples which meet the > 93% call rate using DM at 0.33 can be re-analyzed using the BRLMM Analysis Tool. It is recommended that samples not meeting this specification be re-hybridized or repeated. Samples meeting this specification will the majority of the time yield a call rate of at least 96% and an accuracy of at least 99% when re-analyzed with BRLMM Analysis Tool at default settings. We recommend running at least 50 distinct samples (excluding replicates) and ideally on about 100 samples. Launch BRLMM Analysis Tool from Start/Programs/Affymetrix/BRLMM Analysis Tool.

4 Screen 1 - Select the parameters for the analysis (Figure 2). The file locations are saved from session to session so you should only need to set this once. Figure 2 Select Parameters for Analysis 1) Select library path (e.g. C:\Program Files\Affymetrix\GeneChip\Affy_Data\Library). Note: The selected directory must contain both the CDF/Library file and the chromosome X file. 2) Select analysis parameters. The score threshold (default 0.5) is the maximum score at which the algorithm will make a genotype call, all calls of lower confidence will result in a No Call. Advanced parameters (optional) o The block size refers to the number of probesets to process at once. This parameter is useful when memory is limiting. If set to 0 (default) BRLMM ANALYSIS TOOL attempts to guess the available RAM and set it appropriately. See the manual for more information on adjusting this parameter. o The prior size sets the number of probesets to use for determining the prior (default 10000). o The DM threshold is the confidence threshold for the DM algorithm used for seeding the clusters (default 0.17). o The probeset ID file allows for the specification of a subset of SNPs to which the analysis will be restricted. Run time is directly proportional to the number of SNPs so using this option can greatly speed up the run time.

5 NOTE: It is not possible to create CHP files with only a subset of SNPs. So if this option is used, the CHP output will be suppressed. The results will be in a tab-delimited text file. Note: If advanced algorithm settings have been applied, the main UI will display a flag (Figure 3). Figure 3 Advanced Options Enabled 3) Select output directory and file types. Use the browse button to select the output location. Use the check boxes to select the output file types: Output CHP files (default), Output text files, and/or Output tables Output CHP files Results in the output of a binary CHP file. Currently these CHP files are not importable into GCOS or GTYPE 4.0. Output txt files Text files contain genotype and confidence calls. Essentially a text version of the CHP file. Output tables Outputs genotype calls and confidences in a pair of tab-delimited text matrices name brlmm.calls.txt and brlmm.confidences.txt. The format for each file is a few comment lines prefixed with #, a header line specifying the CEL file names and then a line per SNP, the first field is the SNP_ID and subsequence fields contain genotype calls or confidence scores. Note: Regardless of which output files are selected, a report file (brlmm.report.txt) will be generated. The content of that file includes call rate per CEL file analyzed and additional metrics. See Section V Results/Output files or the manual for a detailed description of the output. 4) Select Next. The next button enables when valid entries are made. Valid being defined as directories exist, numbers are entered in the parameters and at least one of the three output check boxes are checked.

6 Note: The Reset button will reset the parameters back to default values (Not including the paths). Screen 2 - Select the CEL files and the batch name (the sub-directory name) for the analysis (Figure 4). Figure 4 Select CEL Files for Analysis 1) Batch name. Note: The default batch name is date and time. This batch name is used as a subdirectory name under the output directory (selected in the previous screen). All results for that run are stored in the batch name sub-directory. 2) Select CEL files. Using the Add button, browse to the directory containing your CEL files and shiftclick or control-click to select CEL files. You must select only a single array type (e.g. Mapping250K_Sty) to be analyzed in a batch. If multiple array types are selected, a dialog box pops up indicating that not all files were added but only files that match the first selected CEL file probe array type (Figure 5). When completed select Open. Figure 5 Error Message when Selecting Multiple CEL Files from Different Probe Array Types

7 Using the Import button, browse to the directory containing a text file listing the CELs to process. The text file format is: first line cel_files followed by the full path name of the CEL files to process, one per line. To remove CEL files from the list, select the CEL file names and click the Remove button. Note: We recommend running at least 50 distinct samples (excluding replicates) and ideally on about 100 samples. Note: Microsoft Windows operating system has a limitation in the number of files that can be open at any one time (512). Therefore, large batch sizes which exceed this file limitation will cause the software to crash. The total number of CEL files which can be simultaneously batched will depend on the output file options chosen (e.g. txt only or txt and chp). 3) Select Next. The Next button enables when a batch name and CEL files are entered. Note: Clicking Next will start the analysis. Screen 3 - Progress/Status (Figure 6) Figure 6 Progress/Status View This is where status (messages and progress meter) from the algorithm are displayed. NOTE: When canceling the analysis using the Cancel button, the process that is running will continue running and then the analysis will cancel. Depending on what action is running, this may take a few minutes. V. RESULTS/OUTPUT FILES Based on the output files chosen in Screen 1, result files will be written to the output directory specified (Figure 3). (See section BRLMM Analysis Tool Workflow step 3 for more details on the

8 output file types.) All successful runs will result in a report file (brlmm.report.txt, Figure 7). This file contains the following information: 1. The CEL file name. 2. The estimated gender (based upon DM chrx calls at confidence of 0.33). 3. The BRLMM call rate at the default or user-specified threshold. 4. The percentage of SNPs called AB by BRLMM (i.e. the heterozygosity). 5. The percentage of SNPs called AA by BRLMM. 6. The percentage of SNPs called BB by BRLMM. 7. The average of the raw PM probe intensities. 8. The standard deviation of the raw PM probe intensities. 9. The average of the allele signal estimates (log2 scale). 10. The standard deviation of the allele signal estimates (log2 scale). 11. The average of the absolute difference between the log2 allele signal estimate and its median across all chips. 12. The standard deviation of the absolute difference between the log2 allele signal estimate and its median across all chips. 13. The average of the median absolute deviation (MAD) between observed probe intensities and probe intensities fitted by the model. 14. The standard deviation of the median absolute deviation (MAD) between observed probe intensities and probe intensities fitted by the model. 15. The average distance to the cluster center for the called genotype. 16. The standard deviation of the distance to the cluster center for the called genotype. Example brlmm.report.txt file: Figure 7 Example brlmm.report.txt File VI. ADDITIONAL INFORMATION AND SUPPORT Please refer to the complete manual for additional information including advanced parameters. Additionally, a detailed whitepaper explaining the motivation and mathematics of the underlying model is provided at For support information, please contact your FAS or local support team United States / Canada: 888-DNA-CHIP ( ) Europe: +44 (0) Japan: