994850e59495b20664fd6fb1a74a6f44d7e97731
max
  Wed Oct 8 03:19:07 2025 -0700
adding credits to spliceAi impact html page, especially Illumina, refs #35100

diff --git src/hg/makeDb/trackDb/human/spliceImpactSuper.html src/hg/makeDb/trackDb/human/spliceImpactSuper.html
index 19be2d8f869..0f872a76fa1 100644
--- src/hg/makeDb/trackDb/human/spliceImpactSuper.html
+++ src/hg/makeDb/trackDb/human/spliceImpactSuper.html
@@ -221,31 +221,35 @@
 
 <p>
 For automated download and analysis, the genome annotation is stored in a bigBed file that
 can be downloaded from
 <a href="http://hgdownload.soe.ucsc.edu/gbdb/$db/" target="_blank">our download server</a>.
 Individual regions or the whole genome annotation can be obtained using our tool
 <tt>bigBedToBed</tt> which can be compiled from the source code or downloaded as a precompiled
 binary for your system. Instructions for downloading source code and binaries can be found
 <a href="http://hgdownload.soe.ucsc.edu/downloads.html#utilities_downloads">here</a>.
 The tool can also be used to obtain only features within a given range, e.g.
 <tt>bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg19/splicevardb/SVADB.bb -chrom=chr21 -start=0 -end=100000000 stdout</tt></p>
 </p>
 
 <h2>Credits</h2>
 
-<p>Thanks to Nils Wagner for helpful comments and suggestionsi for the AbSplice track.</p>
+<p>Thanks to Illumina for making available SpliceAI, both the model and the precomputed data files.</p>
+
+<p>Thanks to Francois Lecoquierre from the University of Oxford, Jean-Madeleine de Sainte Agathe from Institut Pasteur Paris and Michael Hiller from the Senckenberg Museum Frankfurt for suggesting and then creating the SpliceAI wildtype annotations.</p>
+
+<p>Thanks to Nils Wagner for helpful comments and suggestions for the AbSplice track.</p>
 
 <p>Thanks to the SpliceVarDB team for converting the data into our data formats.</p>
 
 <h2>References</h2>
 <p>
 Jaganathan K, Kyriazopoulou Panagiotopoulou S, McRae JF, Darbandi SF, Knowles D, Li YI, Kosmicki JA,
 Arbelaez J, Cui W, Schwartz GB <em>et al</em>.
 <a href="https://linkinghub.elsevier.com/retrieve/pii/S0092-8674(18)31629-5" target="_blank">
 Predicting Splicing from Primary Sequence with Deep Learning</a>.
 <em>Cell</em>. 2019 Jan 24;176(3):535-548.e24.
 PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/30661751" target="_blank">30661751</a>
 </p>
 
 <p>
 Sullivan PJ, Quinn JMW, Wu W, Pinese M, Cowley MJ.