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Mouse Genetic Map
Files
Updated Nov. 2, 2000
The following files are in text or Map Manager format. You can download
Macintosh or Windows versions of Map Manager at the
Map Manager QTX web
site.
Many files have been bin-hexed (files with the ".hqx" suffix). You will
need a decoding utility such as BinHqx or Stuffit Expander (available for
Mac and Win) to decode Map Manager files. To configure your web browser to
automatically launch a Map Manager file after downloading and decoding,
add Map Manager as a helper application for the MIME type "application/x-mapmanager "
and the file extension ".mm.hqx ."
A Tenth Generation Advanced Intercross Map Manager files
R.W. Williams and G. Zhou, November 2000 Update
- Genetic
Maps based on a set of 500 10th generation progeny in a simple text
format. The cross was generated starting with reciprocal
intercrosses between the common strains C57BL/6J and DBA/2J. We crossed
progeny for 10 generations, intentionally mating animals with as few
common immediate ancestors as possible. This is why the progeny are
referred to as Generation 10 (G10) rather than the Filial F10
generation. This 348 kb text file should be saved and then opened in Map
Manager QTX, Excel, or a text-editing program. Each row consists of 7
fields that are separated by tab characters (tab-delimited). Each of the
340 rows has the following structure: CrossName tab Chromosome
tab MarkerName tab Position tab 500Progeny tab
Reference tab Notes. Empty fields actually contain a single
period. Individual genotypes in the field of 500 progeny are delimited
by single spaces and can be parsed into columns of a spreadsheet program
such as Excel (select Data, then Text to Columns...). However, most
spreadsheets, including Excel, DO NOT support more than 256 columns.
(Sept 27, 2000, RW)
For QGene users: Here are the
two BDG10 text files that this Macintosh QTL mapping program needs to
get going. This pair of files also includes a set of sample phenotypes
that you can use to explore multiple trait mapping. The traits are:
brain weight, eye weight, raw and residual weights of the hippocampus,
olfactory bulbs, and cerebellum. The residuals were computed to minimize
variance associated primarly with brain weight. Weights of the eye,
brain, and brain parts are expressed in milligrams; body weight is
expressed in grams. (November 2, 2000, RW)
- Map file
- Population
file
Genotypes were generated by Maggie Yin at the
Mammalian Genotyping Service with the support of the NHLBI (Dr.
James Weber, PI).
Recombinant Inbred Map Manager files
Composite High-Resolution RI Microsatellite Maps, Release 1, Jan 15,
2001
Release 1 of the
Consensus Maps of RI Strains is described in a preprint included
with the data release. RI consensus maps were assembled from genotypes of
over 1500 microsatellite loci by R. Williams and colleagues (Informatics
Center for Mouse Neurogenetics).
Complete BXN Database in Map Manager QTX-style text format: 853 KB
datafile (inferred genotypes)
Complete BXN Database in native Map Manager QTXformat: 772 KB datafile
(inferred genotypes)
Complete BXN Database in graphic format: 1.9 MB GIF image file
format for printing or reformating in Photoshop (wall paper format).
R.W. Elliott, 1997 edition
- AXB/BXA
RI data
- AXB/BXA
QGene population text file (RWiliams, Nov 2000 data)
- AXB/BXA
QGene map text file (RWiliams, Nov 2000 data)
- AXB/BXA
RI data for QTL analysis
- BXD RI
data
- BXD
RI data: Truncated to 584 loci with unique strain distribution patterns:
for QTL mapping
- AKXD RI
data
- AKXL RI
data
- BXH RI data
- BXJ RI data
- CX8 RI data
- CXB RI data
- CXJ RI data
- CXS RI data
- LSXSS RI
data
- LXP RI data
- NX8 RI data
- NX9 RI data
- NXSM RI
data
- OXA RI data
- SWXJ RI
data
- SWXL RI
data
- 129XB RI
data
- 58NXL RI
data
- 9XA RI data
- BRX58N RI
data
MIT F2 Intercross Panel Data Files
These files were generated from the Whitehead/MIT Center for Genome
Research SSLP F2 panel, Release 9 (April 1995) by R.W Williams. All
chromosome-specific files are under 80 KB.
- MIT
loci, Chr 01
- MIT
loci, Chr 02
- MIT
loci, Chr 03
- MIT
loci, Chr 04
- MIT
loci, Chr 05
- MIT
loci, Chr 06
- MIT
loci, Chr 07
- MIT
loci, Chr 08
- MIT
loci, Chr 09
- MIT
loci, Chr 10
- MIT
loci, Chr 11
- MIT
loci, Chr 12
- MIT
loci, Chr 13
- MIT
loci, Chr 14
- MIT
loci, Chr 15
- MIT
loci, Chr 16
- MIT
loci, Chr 17
- MIT
loci, Chr 18
- MIT
loci, Chr 19
- MIT
loci, Chr X
- MIT
loci, All Chromosomes � 1.4MB
Jackson Lab Backcross Panel Map Data
The following two files were provided by Lucy Rowe of theJackson
Laboratory (see Rowe et al. (1994) Mammalian Genome 5:253). Please contact
Lucy Rowe (lbr@aretha.jax.org) or Mary Barter (meb@aretha.jax.org) if you
have specific questions regarding either dataset. These datasets were
obtained Feb. 1996.
Shionogi Loci
The following three files were provided by V. Chapman and K. Manly,
Roswell Park Institute. A paper describing these loci is now in press.
Please contact Drs. Chapman and Manly if you have specific questions
regarding these files.
This Map Manager file includes the data that were used to generate the
poster "Genome Maps IV, The Mouse." This poster accompanied an article by
Copeland et al (1993, Science 262:57-66) entitled, "A genetic linkage map
of the mouse: Current applications and future prospects." This Map Manager
file includes data on 912 loci typed in a group of 203 interspecies
backcross animals (C57BL/6JxSPRET/Ei)xC57BL/6J.
The order of loci and their positions were fine-tuned by R. Elliott.
The nomenclature has been updated and corrected by R. Williams. As
explained in detail below, the order and positions of loci in the Map
Manager file may differ somewhat from those on the Genome Maps IV poster.
Copeland-Jenkins-MIT map data
Notes on this Map Manager file by R. Elliott and R. Williams (March 10,
1994)
The original file was obtained from the Center for Genome Research via
anonymous ftp at ftp://genome.wi.mit.edu/. Nomenclature of loci was brought into
concordance with the Portable Dictionary of the Mouse Genome. The
file was transferred to Microsoft Word, reformatted, and imported into Map
Manager 2.5.
Once in Map Manager, the ends of each map were anchored using proximal
and distal loci that were shared between the Mouse Chromosome Committee
Reports and the Copeland/Jenkins backcross panel. Loci typed by Neil
Copeland, Nancy Jenkins, and their co-workers were ordered in sequence,
working from the ends toward the middle of each map. The "Links Report"
feature of Map Manager�set at 99.99% probability�was used to position loci
with the highest LOD scores. Other loci were added and ordered using
internal recombination data. The process was repeated until the loci
overlapped in the middle of each map. The MIT SSLP marker loci were added
next. These microsatellite loci were moved in groups that shared similar
progeny distribution patterns (PDPs). The "Links Report" feature was used
again, and sets of loci with similar PDPs were again shifted and
reordered. Following this integration between the two types of loci, the
data set was reexamined to find all single locus double recombinants. The
order of loci was adjusted.
A DISTANCE CAVEAT: The map distances given in the map window of Map
Manager differ somewhat from those published on the Genome Maps IV
poster. These Map Manager position estimates do not take into account
obligate crossovers that are not completely defined. However, the map
distances in the haplotype window of Map Manager do take these crossovers
into account, and consequently, the distances given in this window often
differ from those in the map window. (The haplotype window splits the
difference on the undefined crossovers, assuming that the recombination
event occurred in the middle of the interval.)
A third distance estimate may be obtained by using the "infer
phenotypes" feature in Map Manager. Note however, that this "infer
phenotypes" feature was developed for maps that use completely typed
anchors. In this Fredrick-MIT dataset the anchors are not established and
the recombinant animals were often not typed for the loci on either side
of the crossover. (The choice of animals to be typed probably varied
between loci and was apparently based on other criteria.) Thus using
"infer phenotypes" skews the data in favor of non-recombinants, giving a
low estimate of the distance. In contrast, the data used in the map window
in which phenotypes are not inferred may be skewed the other way for some
of the loci.
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