Welcome to SegAnalysis

last updated 2002.1.29


SegAnalysis is Mathematica packages for mapping factors that cause deviation from expected Mendelian segregation ratios in F2 progeny by a multiresponse non-linear regression analysis.

SegAnalysis allows one to map reproductive barriers, inbreeding depression genes, and hybrid vigor loci in a whole genome.

The genotype segregation of adjacent linked markers tends to be similar, and hence when the frequencies of each allele in F 2 progeny are plotted along a linkage map, three continuous series of allele frequencies are obtained for each chromosome, corresponding to the genotypes of the heterozygote and the two homozygotes. In the regression analysis, mathematical models are fitted to the observed allele frequencies of markers on an entire chromosome. The influence on genotype frequency of linked markers depends on whether the factor acts in the gametophyte or zygote. In the models, a gametophytic factor is described by two variables: the position, and the transmission rate of one parent allele to the progeny. In contrast, a zygotic factor is described by three variables: the position, the relative viabilities of one homozygote and the heterozygote to the other homozygote. By comparing results of several models, SegAnalysis can identify positions of factors, distinguish gametophytic or zygotic factors, and determine their intensity by characterizing the deviation from Mendelian segregation ratios in F 2 population. SegAnalysis can deal with following 18 mathematical models:
  1. Single: a single gametophytic factor.
  2. OneOne: two gametophytic factors on the different gametophyte.
  3. Two: two gametophytic factors on the same gametophyte.
  4. TwoOne: two gametophytic factors on the same gametophyte and another gametophytic factor on the different gametophyte.
  5. Three: three gametophytic factors on the same gametophyte.
  6. TwoTwo: two gametophytic factors on the same gametophyte and the other two gametophytic factors on the different gametophyte.
  7. ThreeOne: three gametophytic factors on the same gametophyte and another gametophytic factor on the different gametophyte.
  8. ThreeTwo: three gametophytic factors on the same gametophyte and the other two gametophytic factors on the different gametophyte.
  9. ThreeThree: three gametophytic factors on the same gametophyte and the other three gametophytic factors on the different gametophyte.
  10. ZOne: a single zygotic factor.
  11. SingleZOne: a single gametophytic factor and a single zygotic factor.
  12. ZTwo: two zygotic factors.
  13. OneOneZOne: two gametophytic factors on the different gametophyte and a single zygotic factor.
  14. TwoOneZOne: two gametophytic factors on the same gametophyte, another gametophytic factor on the different gametophyte and a single zygotic factor.
  15. SingleZTwo: a single gametophytic factor and two zygotic factors.
  16. OneOneZTwo: two gametophytic factors on the different gametophyte and two zygotic factors.
  17. TwoZTwo: two gametophytic factors on the same gametophyte and two zygotic factors.
  18. ZThree: three zygotic factors.

Installation Guide

Mathematica can run on Windows, Linux, Machintosh, UNIX platforms. SegAnalysis consists of 394 items, which requires 30.7 Mb disk space on a Macintosh computer. SegAnalysis will need at least 60 MB memory for MathKernel in case of virtual memory off. Put SegAnalysis folder or its alias on the path of Mathmatica ($Path). SegAnalysis folder was put in the "Mathmatica 3.0 files:AddOns:Applications:" in our case. Our test configuration is a Power Macintosh G3 266DT with 256 Mb memory and a 20 GB hard disk. We run MacOS 8.6 with 257 Mb virtual memory and Mathematica 3.0.1 PPC (memory of Front End and MathKernel were 30 and 70 Mb, respectively).

Preparing Data for SegAnalysis

Data files are three text files of lists of marker position and each allele frequency, {position, frequency}. Marker positions are expressed in Morgan of the Kosambi map function that should be calculated by other programs (e.g. MAPMAKER ) using genotypes in the F2 population to be analyzed.
An example of a homozygote raw file follows:
{{0.040, 0.255319148936170}, {0.056, 0.223404255319149}, {0.177, 0.212765957446809}, {0.232, 0.234042553191489}, {0.305, 0.212765957446809}, {0.332, 0.202127659574468}, {0.435, 0.265957446808511}, {0.665, 0.276595744680851}, {0.681, 0.276595744680851}, {0.777, 0.287234042553192}, {0.788, 0.297872340425532}, {0.821, 0.255319148936170}, {0.964, 0.212765957446809}, {0.986, 0.212765957446809}, {0.997, 0.202127659574468}, {1.100, 0.244680851063830}, {1.144, 0.255319148936170}, {1.188, 0.244680851063830}, {1.249, 0.265957446808511}, {1.328, 0.287234042553192}, {1.361, 0.308510638297872}, {1.372, 0.308510638297872}, {1.450, 0.276595744680851}, {1.499, 0.287234042553192}, {1.510, 0.297872340425532}, {1.618, 0.297872340425532}, {1.740, 0.297872340425532}, {1.778, 0.287234042553192}, {1.794, 0.276595744680851}, {1.810, 0.276595744680851}, {1.958, 0.265957446808511}}

Download SegAnalysis packages

A simple tutorial  (up on 2001.10.25)

Reference  for SegAnalysis:
Y. Harushima, M. Nakagahra, M. Yano, T. Sasaki, and N. Kurata (2001) "A genome-wide survey of reproductive barriers in an intraspecific hybrid."  Genetics 159: 883-892.

An example of SegAnalysis:
Y. Harushima, M. Nakagahra, M. Yano, T. Sasaki, and N. Kurata (2002) "Diverse variation of reproductive barriers in three intraspecific rice crosses."  Genetics 160: 313-322.


If you have a question, please contact to yharushi@lab.nig.ac.jp