Source 1primary paper2014PLoS Genetics
Toolkit/Anderson-Darling test
Anderson-Darling test
Also known as: A-D test
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
The Anderson-Darling test is a nonparametric computational method applied in genome-wide association studies of complex quantitative traits. In an enlarged maize association panel, it identified loci across 17 agronomic traits, including both previously known loci and additional candidate loci detected only by this test.
Usefulness & Problems
Why this is useful
This method is useful as a complement to GWAS analysis for complex quantitative traits. The cited study states that it is especially useful for traits with abnormal phenotype distributions and for traits influenced by moderate-effect loci or rare variations.
Problem solved
It addresses limitations of GWAS approaches when phenotype distributions are abnormal or when genetic architecture includes moderate-effect loci or rare variants. In the cited maize study, it enabled detection of candidate loci that were not observed by other compared analyses.
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete computational method used to design, rank, or analyze an engineered system.
Mechanisms
nonparametric statistical association testingnonparametric statistical association testingnonparametric statistical association testingTarget processes
No target processes tagged yet.
Implementation Constraints
cofactor dependency: cofactor requirement unknownencoding mode: genetically encodedimplementation constraint: context specific validationoperating role: builder
The available evidence supports use as a computational method within genome-wide association studies in an enlarged maize association panel. No implementation details such as software package, parameterization, input formatting, or integration with specific GWAS pipelines are described in the supplied evidence.
The supplied evidence is limited to a single 2014 maize GWAS study. No quantitative performance metrics, false-positive behavior, computational cost, or validation in other organisms or study designs are provided in the supplied evidence.
Validation
Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication
Supporting Sources
Ranked Claims
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Bonferroni-corrected threshold 7.05loci identified for plant height 107SNPs used 556809traits analyzed 17
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
Using the mixed linear model, ten loci for five traits were identified at a Bonferroni-corrected threshold of -log10(P) greater than 5.74.
Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold -log10 (P) >5.74 (α=1).
Bonferroni-corrected threshold 5.74loci identified 10traits with identified loci 5
Using the mixed linear model, ten loci for five traits were identified at a Bonferroni-corrected threshold of -log10(P) greater than 5.74.
Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold -log10 (P) >5.74 (α=1).
Bonferroni-corrected threshold 5.74loci identified 10traits with identified loci 5
Using the mixed linear model, ten loci for five traits were identified at a Bonferroni-corrected threshold of -log10(P) greater than 5.74.
Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold -log10 (P) >5.74 (α=1).
Bonferroni-corrected threshold 5.74loci identified 10traits with identified loci 5
Using the mixed linear model, ten loci for five traits were identified at a Bonferroni-corrected threshold of -log10(P) greater than 5.74.
Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold -log10 (P) >5.74 (α=1).
Bonferroni-corrected threshold 5.74loci identified 10traits with identified loci 5
Using the mixed linear model, ten loci for five traits were identified at a Bonferroni-corrected threshold of -log10(P) greater than 5.74.
Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold -log10 (P) >5.74 (α=1).
Bonferroni-corrected threshold 5.74loci identified 10traits with identified loci 5
Using the mixed linear model, ten loci for five traits were identified at a Bonferroni-corrected threshold of -log10(P) greater than 5.74.
Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold -log10 (P) >5.74 (α=1).
Bonferroni-corrected threshold 5.74loci identified 10traits with identified loci 5
Using the mixed linear model, ten loci for five traits were identified at a Bonferroni-corrected threshold of -log10(P) greater than 5.74.
Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold -log10 (P) >5.74 (α=1).
Bonferroni-corrected threshold 5.74loci identified 10traits with identified loci 5
Using the mixed linear model, ten loci for five traits were identified at a Bonferroni-corrected threshold of -log10(P) greater than 5.74.
Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold -log10 (P) >5.74 (α=1).
Bonferroni-corrected threshold 5.74loci identified 10traits with identified loci 5
Using the mixed linear model, ten loci for five traits were identified at a Bonferroni-corrected threshold of -log10(P) greater than 5.74.
Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold -log10 (P) >5.74 (α=1).
Bonferroni-corrected threshold 5.74loci identified 10traits with identified loci 5
Using the mixed linear model, ten loci for five traits were identified at a Bonferroni-corrected threshold of -log10(P) greater than 5.74.
Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold -log10 (P) >5.74 (α=1).
Bonferroni-corrected threshold 5.74loci identified 10traits with identified loci 5
Approval Evidence
1 source2 linked approval claimsfirst-pass slug anderson-darling-test
a new method, the Anderson-Darling (A-D) test
Source:
method comparisonsupports
The Anderson-Darling test identified many loci across 17 agronomic traits, including known and new candidate loci that were only observed by the A-D test.
Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test
Source:
method comparisonsupports
The Anderson-Darling test is a useful complement for GWAS analysis of complex quantitative traits and is especially useful for traits with abnormal phenotype distribution or those controlled by moderate effect loci or rare variations.
we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power.
Source:
Comparisons
Source-backed strengths
In the reported application, the Anderson-Darling test detected many loci across 17 agronomic traits. Its strengths, as supported by the source, are complementary locus discovery in GWAS and sensitivity to known loci as well as additional candidate loci uniquely identified by the A-D test.
Compared with free-energy calculations
Anderson-Darling test and free-energy calculations address a similar problem space.
Shared frame: same top-level item type
Compared with mathematical model
Anderson-Darling test and mathematical model address a similar problem space.
Shared frame: same top-level item type
Strengths here: looks easier to implement in practice.
Compared with SwiftLib
Anderson-Darling test and SwiftLib address a similar problem space.
Shared frame: same top-level item type
Ranked Citations
- 1.