Difference between revisions of "MACH"
Moskalenko (talk | contribs) m (Text replacement - "#uppercase" to "uc") |
|||
| Line 41: | Line 41: | ||
--> | --> | ||
==System Variables== | ==System Variables== | ||
| − | * HPC_{{ | + | * HPC_{{uc:{{#var:app}}}}_DIR - installation directory |
| − | * HPC_{{ | + | * HPC_{{uc:{{#var:app}}}}_DIR - executable directory |
<!--Configuration--> | <!--Configuration--> | ||
{{#if: {{#var: conf}}|==Configuration== | {{#if: {{#var: conf}}|==Configuration== | ||
Revision as of 21:21, 6 December 2019
Description
Genome-wide association studies (GWAS) can identify common alleles that contribute to complex disease susceptibility. The effects of most common SNPs must be evaluated indirectly using either genotyped markers or haplotypes thereof as proxies. MACH software implements a computationally efficient Markov Chain framework for genotype imputation and haplotyping. The approach describes sampled chromosomes as mosaics of each other and uses available genotype and shotgun sequence data to estimate unobserved genotypes and haplotypes, together with useful measures of the quality of these estimates.
Required Modules
Serial
- mach
System Variables
- HPC_MACH_DIR - installation directory
- HPC_MACH_DIR - executable directory
Citation
If you publish research that uses mach you have to cite it as follows:
Li Y, Willer CJ, Ding J, Scheet P and Abecasis GR (2010) MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet Epidemiol 34:816-834.
Li Y, Willer CJ, Sanna S and Abecasis GR (2009) Genotype Imputation. Annu Rev Genomics Hum Genet 10:387-406.
Validation
- Validated 4/5/2018