Updated R/qtl description text

1 files changed, 1 insertions, 1 deletions

diff --git a/wqflask/wqflask/templates/show_trait_mapping_tools.html b/wqflask/wqflask/templates/show_trait_mapping_tools.html
index 66903c31..01d90d21 100644
--- a/wqflask/wqflask/templates/show_trait_mapping_tools.html
+++ b/wqflask/wqflask/templates/show_trait_mapping_tools.html
@@ -365,7 +365,7 @@
              <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>
              {% elif mapping_method == "R/qtl" %}
              <dt style="margin-top: 20px;">R/qtl</dt>
-             <dd>Major upgrade of R/qtl that supports most experimental populations including those with complex admixture and two or more parental lines as well as large omic data sets (<a href="https://www.ncbi.nlm.nih.gov/pubmed/30591514">PMID: 30591514</a>). Both R/qtl and R/qtl2 are available as stand-alone R packages (<a href="https://kbroman.org/pages/software.html">R suite</a>).</dd>
+             <dd>The original R/qtl mapping code that supports most classic experimental crosses provided that they  do not have complex kinship or admixture (<a href="https://www.ncbi.nlm.nih.gov/pubmed/30591514">PMID: 30591514</a>). Both R/qtl, implemented here, and R/qtl2 are available as stand-alone R packages (<a href="https://kbroman.org/pages/software.html">R suite</a>).</dd>
              {% elif mapping_method == "QTLReaper" %}
              <dt style="margin-top: 20px;">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>