diff options
| -rwxr-xr-x | wqflask/wqflask/templates/show_trait_mapping_tools.html | 18 |
1 files changed, 9 insertions, 9 deletions
diff --git a/wqflask/wqflask/templates/show_trait_mapping_tools.html b/wqflask/wqflask/templates/show_trait_mapping_tools.html index d7d8be1c..09442b4e 100755 --- a/wqflask/wqflask/templates/show_trait_mapping_tools.html +++ b/wqflask/wqflask/templates/show_trait_mapping_tools.html @@ -1,6 +1,6 @@ -<div class="row mapping-main"> +<div class="mapping-main"> {% if dataset.group.mapping_names|length > 0 %} - <div class="col-xs-2 mapping-options"> + <div class="mapping-options"> <div class="tabbable"> <!-- Only required for left/right tabs --> <ul class="nav nav-pills"> @@ -52,7 +52,7 @@ </div> {% endif %} <div class="mapping_method_fields form-group"> - <label for="maf_gemma" class="col-xs-3 control-label">MAF >=</label> + <label for="maf_gemma" class="col-xs-3 control-label">Minor Allele ≥</label> <div class="col-xs-4 controls"> <input name="maf_gemma" value="{{ maf }}" type="text" class="form-control maf-select"> </div> @@ -416,21 +416,21 @@ </div> </div> </div> - <div class="col-xs-6"> + <div class="mapping-descriptions"> <div class="section-form-div"> <dl> {% for mapping_method in dataset.group.mapping_names %} {% if mapping_method == "GEMMA" %} <dt>GEMMA</dt> - <dd>Maps traits with correction for kinship among samples using a linear mixed model method, and also allows users to fit multiple covariates such as sex, age, treatment, and genetic markers (<a href="https://www.ncbi.nlm.nih.gov/pubmed/24531419">PMID: 2453419</a>, and <a href="https://github.com/genetics-statistics/GEMMA"> GitHub code</a>). GEMMA incorporates the Leave One Chromosome Out (LOCO) method to ensure that the correction for kinship does not remove useful genetic variance near each marker. Markers can be filtered to include only those with minor allele frequencies (MAF) above a threshold. The default MAF is 0.05.</dd> + <dd>GEMMA maps with correction for kinship using a linear mixed model and can include covariates such as sex and age. Defaults include a minor allele frequency of 0.05 and the leave-one-chromosome-out method (<a href="https://www.ncbi.nlm.nih.gov/pubmed/24531419">PMID: 2453419</a>, and <a href="https://github.com/genetics-statistics/GEMMA"> GitHub code</a>).</dd> {% elif mapping_method == "R/qtl" %} <dt class="map-method-text">R/qtl (version 1.44.9)</dt> - <dd>The original R/qtl mapping package that supports classic experimental crosses including 4-parent F2 intercrosses (e.g., NIA ITP UM-HET3). R/qtl is ideal for populations that do not have complex kinship or admixture (<a href="https://www.ncbi.nlm.nih.gov/pubmed/12724300">PMID: 12724300</a>). Both R/qtl as implemented here, and R/qtl2 (<a href="https://www.ncbi.nlm.nih.gov/pubmed/30591514">PMID: 30591514</a>) are available as <span class="broken-link" href="https://kbroman.org/pages/software.html">R suites</span>.</dd> - <dt class="map-method-text">Pair Scan</dt> - <dd>Pair Scan using the R/qtl scantwo function.</dd> + <dd><a href="https://www.ncbi.nlm.nih.gov/pubmed/12724300">R/qtl</a> maps using several models and uniquely support 4-way intercrosses such as the "Aging Mouse Lifespan Studies" (NIA UM-HET3). We will add support for R/qtl2 (<a href="https://www.ncbi.nlm.nih.gov/pubmed/30591514">PMID: 30591514</a>) in 2023—a version that handles complex populations with admixture and many haplotypes.</dd> + <dt class="map-method-text">Pair Scan (R/qtl v 1.44.9)</dt> + <dd>The Pair Scan mapping tool performs a search for joint effects of two separate loci that may influence a trait. This search typically requires large sample sizes. Pair Scans can included covariates such as age and sex. For more on this function by K. Broman and colleagues see www.rdocumentation.org/packages/qtl/versions/1.60/topics/scantwo</dd> {% elif mapping_method == "QTLReaper" %} <dt class="map-method-text">Haley-Knott Regression</dt> - <dd>Fast linear mapping method (<a href="https://www.ncbi.nlm.nih.gov/pubmed/16718932">PMID 16718932</a>) works well with F2 intercrosses and backcrosses, but that is not recommended for complex or admixed populations (e.g., GWAS or heterogeneous stock studies) or for advanced intercrosses, recombinant inbred families, or diallel crosses. Interactive plots in GeneNetwork have relied on the fast HK mapping for two decades and we still use this method for mapping omics data sets and computing genome-wide permutation threshold (<a href="https://github.com/pjotrp/QTLReaper">QTL Reaper code</a>).</dd> + <dd>HK regression (QTL Reaper) is a fast mapping method with permutation that works well with F2 intercrosses and backcrosses (<a href="https://www.ncbi.nlm.nih.gov/pubmed/16718932">PMID 16718932</a>), but is not recommended for admixed populations, advanced intercrosses, or strain families such as the BXDs (<a href="https://github.com/pjotrp/QTLReaper">QTL Reaper code</a>).</dd> {% endif %} {% endfor %} </dl> |