| Criteria | Recommended |
| Strains |
MPD priority strains
(Tier 1 has highest priority).
Strain panels derivated from the priority strains (F1 hybrids, recombinant inbreds, congenics, etc) are also encouraged.
Data from other strains may be posted if other requirements are met.
|
| Strain purity |
Mice must be obtained from recognized breeding sources. |
| Number of strains examined |
Ideal: 20 or more strains, both female and male.
Allowable: 8 or more strains.
Occasional lower number of strains are sometimes allowed on a case-by-case basis.
|
| Number of animals per strain (N) |
Ideal: at least 10 males and 10 females for each measurement.
Allowable: 5 or more males and/or females for each measurement.
Occasional lower N are sometimes allowed on a case-by-case basis.
Note that if a project involves treatment groups or other subgroups, this guideline applies to each treatment group or subgroup.
|
| Animal age | Ideal: 10-14 weeks of age. |
| Assay types | Mouse anatomy, physiology, and behavior. |
| Study design |
Projects should be structured as strain surveys that serve to characterize mouse strains.
In addition to basic strain surveys, more complex study designs such as aging studies,
disease state studies, treatment vs. control studies, are also acceptable
if they offer straightforward characterization of mouse strains.
|
| Unit of analysis |
MPD's basic unit of analysis is strain / sex / measurement. For example: Peters1 platelet count mean for C57BL/6J females |
| Peer review | Project publication in a peer-reviewed journal is not required, but is encouraged
and useful for data validation. |
| Data set |
Tabular data set should be organized as one row per animal, or as one row per animal/assay.
Strain means (with SD or SEM and N) are acceptable but individual animal data are preferred.
Missing data codes should be used.
More information and examples
|
| Strain nomenclature |
Strain names should appear in the data set using current nomenclature.
For nomenclatures that are unwieldy (consomics, congenics, etc.) abbreviated strain names may be used
if these are clearly defined in an equivalence table.
|
| Animal identifiers |
Unique animal identifiers should be present on each row in the data set, to allow
linkage across assays, and for trace purposes.
|
| Animal sexes |
Sex (M or F) must be indicated for every animal (or every submitted summary statistic). |
| Animal ages and body weights |
Animal ages (in days) should be present in the data set (preferred) or
specified in the animal documentation (discussed below).
Animal body weights (in grams) should be present in the data set.
For both age and weight, multiple values should be provided if
testing occurs over a significant period of time.
|
| Measurement descriptions |
Each measurement in the data set must be fully defined, including the units of measurement,
at a level understandable by a non-specialist.
Standard units should be used where feasible.
Measurement descriptions may be submitted in a tabular file or as part of the project protocol (discussed below).
Example
|
Protocol |
MPD staff will prepare an illustrated protocol document based on publication
as well as information gathered directly from investigators.
Typically addresses areas such as:
- Workflow
- Methods
- Equipment (source and settings)
- Sampling scheme. Multiple samples per animal are preferred where appropriate.
- Reagents (sources and amounts)
- If anesthesia is used, indicate: drug, dose, route, restraint, and problems
- Description of study design, data gathering workflow, data review and data cleaning procedures
- Analysis / statistical methods
- References (if applicable)
|
Animal documentation |
MPD staff will prepare animal documentation based on publication
as well as information gathered directly from investigators.
Typically addresses areas such as:
- Strain vendor sources
- Duration of acclimation period
- Environment during acclimation period
- cage dimensions or cage type/vendor
- number of mice per cage
- bedding type and vendor
- feed (examples) and water
- photoperiod
- temperature, humidity
- animal health status
- Dates of testing
- Animal ages at time of testing, if not in the data set
- Environment during testing period (where different from acclimation period)
|
| Quality and completeness |
The data set should be thoroughly reviewed before submission and should be clean and without
unexplained missing or implausible values.
Missing data codes should be used.
Project documentation should be logical and thorough.
|
| Clarity and conciseness |
The study design, contributed data, and accompanying material should be clear, concise,
and understandable by non-experts.
Data sets should be structured intuitively and concisely.
|
