| Type: | Package |
| Title: | Minimum-Hypergeometric Test |
| Version: | 1.1 |
| Date: | 2017-08-18 |
| Author: | Kobi Perl |
| Maintainer: | Kobi Perl <kobipe3@gmail.com> |
| Description: | Runs a minimum-hypergeometric (mHG) test as described in: Eden, E. (2007). Discovering Motifs in Ranked Lists of DNA Sequences. Haifa. |
| License: | GPL-2 |
| Depends: | methods |
| Suggests: | testthat |
| NeedsCompilation: | no |
| Packaged: | 2017-08-18 07:25:39 UTC; kobip_000 |
| Repository: | CRAN |
| Date/Publication: | 2017-08-18 07:57:10 UTC |
Minimum-Hypergeometric Test
Description
Sometimes when running a hypergeometric test to check for enrichment for a feature in a group versus the background, the separation between the group and the background is done arbitrarily by setting a threshold on some other property.
When the correct threshold is unknown, different thresholds can be tried, and the minimal p-value of the hypergeometric tests can be retreived.
If the elements can be sorted according to the property, it is possible to perform the hypergeometric tests on groups of increasing size.
The minimum over all the tests is the minimum hypergeometric statistic, or mHG.
The mHG is not a p-value by itself, as multiple tests were performed, without correcting for this.
The package provides means to calculate the statistic (mHG.statistic.calc), to fix the p-value (mHG.pval.calc) or to perform the entire test at once (mHG.test).
This is an R implementation of the algorithm described in:
Eden, E. (2007). Discovering Motifs in Ranked Lists of DNA Sequences. Haifa.
Retrieved from http://bioinfo.cs.technion.ac.il/people/zohar/thesis/eran.pdf
Details
| Package: | mHG |
| Type: | Package |
| Version: | 1.0 |
| Date: | 2015-05-18 |
| License: | GPL-2 |
| Depends: | methods |
The package provides means to calculate the statistic (mHG.statistic.calc), to fix the p-value (mHG.pval.calc) or to perform the entire test at once (mHG.test).
Author(s)
Kobi Perl <kobipe3@gmail.com>
References
Eden, E. (2007). Discovering Motifs in Ranked Lists of DNA Sequences. Haifa. Retrieved from http://bioinfo.cs.technion.ac.il/people/zohar/thesis/eran.pdf
See Also
mHG.statistic.calc
mHG.pval.calc
mHG.test
Examples
N <- 50
B <- 15
lambdas <- numeric(50)
lambdas[sample(N, B)] <- 1
t <- mHG.test(lambdas)
t <- mHG.test(lambdas, n_max = 20)
Calculate the p-value of a minimum-hypergeometric (mHG) statistic.
Description
Calculates the p-value associated with the (minimum-hypergeometric) mHG statistic.
Usage
mHG.pval.calc(p, N, B, n_max = N)
Arguments
p |
the mHG statistic. It is marked as p as it represents an "uncorrected" p-value. |
N |
total number of white and black balls (according to the hypergeometric problem definition). |
B |
number of black balls. |
n_max |
the algorithm will calculate the p-value under the assumption that only the
first |
Details
O(NB) running time, O(NB) space.
Value
the p-value of the test.
Author(s)
Kobi Perl
References
Eden, E. (2007). Discovering Motifs in Ranked Lists of DNA Sequences. Haifa. Retrieved from http://bioinfo.cs.technion.ac.il/people/zohar/thesis/eran.pdf (pages 11-12, 19-20)
Examples
N <- 50
B <- 15
lambdas <- numeric(50)
lambdas[sample(N, B)] <- 1
p <- mHG.statistic.calc(lambdas)@mHG
p.corrected <- mHG.pval.calc(p, N, B) # Could have used mHG.test directly
Calculate the minimum-hypergeometric (mHG) statistic.
Description
Calculates the minimum-hypergeometric (mHG) statistic.
mHG definition: mHG(\lambda)=min_{1<=n<N} HGT(b_n(\lambda))
Where HGT is the hypergeometric tail: HGT(b;N,B,n)=Probability(X>=b),
and b_n=\sum\limits_{i=1}^n \lambda_i.
Usage
mHG.statistic.calc(lambdas, n_max = length(lambdas))
Arguments
lambdas |
|
n_max |
the algorithm will only consider the first |
Details
O(n_{max}+B^2*log(B)) running time, O(B) space.
Value
Instance of the class mHG.statistic.info (stores the statistics, and for which n and b_n it was obtained).
If several n give the same mHG, the smallest one is chosen.
Author(s)
Kobi Perl
References
Eden, E. (2007). Discovering Motifs in Ranked Lists of DNA Sequences. Haifa. Retrieved from http://bioinfo.cs.technion.ac.il/people/zohar/thesis/eran.pdf (pages 10-11, 18-19)
See Also
Examples
N <- 50
B <- 15
lambdas <- numeric(50)
lambdas[sample(N, B)] <- 1
mHG.statistic.info <- mHG.statistic.calc(lambdas)@mHG
Class "mHG.statistic.info"
Description
Summarizes data about the minimum-hypergeometric (mHG) statistic of a {0,1}^N vector.
Objects from the Class
Objects can be created by calls of the form new("mHG.statistic.info", ...).
Slots
mHG:The actual statistic.
n:The index in which the minimum was obtained.
b:\sum\limits_{i=1}^n \lambda_i.
Methods
No methods defined with class "mHG.statistic.info" in the signature.
Author(s)
Kobi Perl
References
Eden, E. (2007). Discovering Motifs in Ranked Lists of DNA Sequences. Haifa. Retrieved from http://bioinfo.cs.technion.ac.il/people/zohar/thesis/eran.pdf (page 10)
See Also
Examples
showClass("mHG.statistic.info")
Perform Minimum-Hypergeometric test.
Description
Performs a minimum-hypergeometric (mHG) test. The null-hypothesis is that provided list was randomly and equiprobable selected from all lists containing N entries, B of which are 1s. The alternative hypothesis is that the 1s tend to appear at the top of the list.
Usage
mHG.test(lambdas, n_max = length(lambdas))
Arguments
lambdas |
|
n_max |
the algorithm will only consider the first |
Details
O(NB) running time, O(NB) space.
Value
A list with class "htest" containing the following components:
statistic |
The mHG statistic. |
p.value |
The p-value for the test. |
parameters |
|
n |
The index for which the mHG was obtained (smallest one if several n give the same mHG). |
b |
|
Author(s)
Kobi Perl
References
Eden, E. (2007). Discovering Motifs in Ranked Lists of DNA Sequences. Haifa. Retrieved from http://bioinfo.cs.technion.ac.il/people/zohar/thesis/eran.pdf (pages 10-12, 18-20)
Examples
N <- 50
B <- 15
lambdas <- numeric(50)
lambdas[sample(N, B)] <- 1
t <- mHG.test(lambdas)
t <- mHG.test(lambdas, n_max = 20)