| | 1 | = GenotypePipeline = |
| | 2 | |
| | 3 | ||developers:||AndreDeVries, JorisLops, MorrisSwertz|| |
| | 4 | ||state:||design|| |
| | 5 | |
| | 6 | In general, genome wide genotype data (SNPs) goes through the following processing steps:[[BR]] |
| | 7 | 1. Genotype calling[[BR]] |
| | 8 | 2. Cleaning of the genotype data[[BR]] |
| | 9 | 3. Imputation (optional)[[BR]] |
| | 10 | 4. Analysis |
| | 11 | |
| | 12 | Steps 1-3 can be regarded as preprocessing steps, while step 4 is one that can be re-iterated many times, based on a single outcome of steps 1-3. |
| | 13 | |
| | 14 | Steps 1 and 2 can be combined in a single software package.[[BR]] |
| | 15 | Step 3 is performed using imputation software, such as IMPUTE, Beagle or MaCH.[[BR]] |
| | 16 | Step 4 combines the cleaned (+imputed) data plus some phenotype data into an analysis. |
| | 17 | |
| | 18 | An automated pipeline may be desirable. Steps 1+2 could be standardized and thus also automized into a pipeline. Step 3 may be added to that. |
| | 19 | |
| | 20 | Step 4 probably has to be in a separate pipeline. This would result in a kind of platform (based on Molgenis?) in which researchers construct instructions in order to run some analysis.[[BR]] |
| | 21 | Results come back to the platform and can be inspected.[[BR]] |
| | 22 | An important ingredient of whole genome SNP analysis is the command line program PLINK. Information about that can be found below. |
