- PLINK 형식 파일 : PED, MAP
- PLINK 이진 형식 파일 : BED, BIM, FAM
- Variant calling format : VCF, FAM
- Raw genotype file : RAW
- Long format file : LGEN, FAM
- Transposed format : TPED, TFAM
- Hardy-Weinberg Equilibrium (HWE)
- Minor Allele Frequency (MAF) / Minor Allele Count (MAC)
- Sample-wise/variant-wise call rate
- Mendelian errors
- Familial kinship relationship matrix
- Genotype-based relationship matrix
- Hybrid relationship matrix
- Identity-by-state relationship matrix
- User-defined relationship matrix
- Heritability estimation with family structure
- Heritability estimation with genotype
- Cochran-Armitage test
- Chi-squared test of genotype (2df)
- Linear regression
- Logistic regression
- Multidimensional scaling (Price et al., 2006)
- GEMMA (Zhou et al., 2012)
- MQLS (Thornton et al., 2010)
- FQLS (Park et al., submitted)
- Transmission disequilibrium test (Spielman et al., 1998)
- Sibship disequilibrium test (Horvath et al., 1998)
- GEMMA (Zhou et al., 2012)
- MQLS (Thornton et al., 2010)
- FQLS (Park et al., submitted)
- Transmission Disequilibrium Test (Spielman et al., 1993)
- Fast epistasis analysis (Purcell et al., 2007)
- MDR (Ritchie et al., 2001)
- BOOST (Wan et al., 2010)
- Regression analysis for 2-way interaction term
- CMC (Li et al., 2008)
- Weighted sum test (Madsen et al., 2009)
- Variable threshold test (Price et al., 2010)
- KBAC test (Liu et al., 2010)
- FARVAT (Choi et al., 2014)
- FARVAT-o (Choi et al., 2014)
- Q-test (Lee et al., submitted)
- PedCMC (add ref)
- Variable threshold test (Price et al., 2010)
- SKAT (Wu et al., 2010)
- SKATO (Lee et al., 2012)
- PedCMC (add ref)
- famVT test (Lee et al., submitted)
- FARVAT (Choi et al., 2014)
- FARVAT-o (Choi et al., 2014)
- FB-SKAT (Ionita-Laza et al., 2013) (from 1.1.0.8)
- rv-tdt (He et al., 2014) (from 1.1.0.8)
Overview
WISARD is featured by four major functionalities:
- Study design: WISARD calculates the expected power and the required number of families/individuals.
In particular, the certain number of individuals in extended families which maximize the statistical powers can be selected.
- Data management: retrieval, conversion, splitting and merging of a large-scale genetic data with various formats can be simply performed.
For extended families the family-based imputation by WISARD is also useful to handle missing genotypes.
- Quality control: genotype qualities for each variant or each individual can be evaluated with several statistics and samples can be filtered based on the quality scores.
- Association analyses: WISARD provides various useful functions ranging from heritability estimations to multiple genotypes/phenotypes association analysis. Most of association
test in WISARD can be automatically multi-threaded, and with the integration of R, WISARD enables the longitudinal data analysis and
the graphical summarization of analysis results.
Depending on the study design and the presence of population substrucutre, different test statistics for association analysis has to be utilized.
Compared to other genetic analysis software, WISARD calculates much more statistics, and association analyses supported by WISARD are :
Prerequisites
WISARD provides the command-line interface
and the graphical user interface is not supported.
In order to use WISARD properly, check whether it can be run in your operating systems requirements.
The operating systems supported by WISARD are described in the download page.
Readme
On the usage [top]
WISARD can be used freely with no limitation.
In addition, we do not guarantee any types of result from WISARD.
On the distribution [top]
A source, compiled binary of WISARD cannot be distributed except for this website.
A contents of this website can be distributed or cited, but we also do not guarantee the contents.
Distribution of the source code of WISARD [top]
Since WISARD is still before publish, we still not made our decision about the distribution of
source code of WISARD. We will notice about this issue after the publish.
Edit this pageLast modified : 2014-09-01 18:19:23