To compute trillions of association typically required for quantitative trait locus (QTL) analysis. The statistical model is linear model. This program uses graphical processing unit (GPU) to achieve dramatic speedups. Created in 2009.
- Java version 7 or above
- NVIDIA or AMD graphic card, with the corresponding drivers installed
Invoke the following:
java -jar gpgpu.jar:qgenerics.jar:javacl-1.0.0-RC1-shaded.jar:jdistlib-0.3.5-bin.jar:javacsv.jar:commons-compress-1.3.jar:jgrapht.jar gov.nih.eqtl.QeQTLAnalysis your_file.ini
The structure of your_file.ini is the following:
genotype_file = your_genotype_file.csv
expression_file = your_expression_file.csv
output_file = your_output_file.csv
covariate_file = your_covariate_file.csv
covariate_fixed = Sex Age Batch PC1 PC2 PC3 PC4 PC5 PCP1 PCP2 PCP3 PCP4 PCP5
covariate_factor = Sex Batch
genotype_format = csv
expression_format = csv
df_offset = 0
block_size = 10240
num_threads = 8
lambda = 0.75
library_path = /usr/lib:/usr/lib64
threshold = pval 1e-4
your_genotype_file.csv is a CSV file with the number of genotypes (row) x number of samples (column). The extra first column must be an identifier of each row. Cannot have any missing values. Currently no other format is accepted.
your_expression_file.csv is a CSV file with the number of expression (row) x number of samples (column). The extra first column must be an identifier of each row. Cannot have any missing values. Currently no other format is accepted.
your_covariate_file.csv is a CSV file with the number of samples (row) x number of covariates (column). Cannot have any missing values on covariates that are used in the model. Currently no other format is accepted.
NOTE: Please make sure that the ordering of the samples match 100% between the genotype, expression, and covariate files because this program did NOT perform additional check other than the number of samples.
In reality, you can put in any Omics file modalities in either genotype_file or expression_file to match your research objective. For example, if you want to perform methylation QTL analysis, then you put in methylation file as the expression_file. If you want to perform splicing-protein analysis, then you put in splicing file as the genotype_file and proteomics data as the expression_file, and so on.
covariate_fixed is the covariate names you want to include in the model. Cannot have any missing values. The names must be an exact match in the covariate file.
covariate_factor is part of covariate_fixed that this program needs to treat as factors, not as numeric values. Covariate with more than two factors will be encoded using One-hot encoding.
df_offset is useful if you want to further reduce the degrees of freedom (perhaps because you already regress out several problematic covariates) and you want to account those factors into the DF computation. If you did not do any of that, leave it to zero.
block_size is the matrix size you want the GPU to handle at a time. Depends on the size of the GPU. 10240 is a good size for old GPUs.
num_threads is how many CPU thread you would like to use to perform the computation. Some of the computation (e.g., P-value) is done in CPU. So, values at least two would be good.
lambda leave it at 0.75. The intent was to use that much proportion of GPU memory, but evidently it could be unpredictable.
library_path is to specify where libOpenCL.so may reside. Linux only. Remove this line for Windows. This is to account for the various ways Linux distributions store the appropriate library.
threshold is to record anything below or above a certain threshold. The pval 1e-4 is to record all the results with p<1e-4. You can have rsq 0.1, which means record all results with partial R^2 of at least 0.1.
your_output_file.csv is the CSV file of the output format generated. The column description is as follows:
- The first column will contain the ID of the genotype file.
- ID of the expression file
- Partial R^2 of the association
- The regression (beta) coefficient
- T statistics
- log10 of the P-value
This program should automatically detect the appropriate drivers.
You need to install the appropriate drivers. For NVIDIA cards, you need to install nvidia-driver-<version>, nvidia-dkms-<version>, nvidia-cuda-toolkit, and clinfo. Check your Linux manual for the appropriate driver version. The package names may vary for other Linux distributions.
For AMD driver, please consult your system administrator.
IMPORTANT: You MUST reboot your Linux computer upon installing these drivers.