9bfd58221b1539193cb7f0a317b4e959c1c7e49a
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Thu May 21 01:00:45 2026 -0700
varFreqs: AI generated text sounds bad, hard to read, so remove typical AI language. "humanizer" pass on all 31 varFreqs description pages — cut em dashes, copula avoidance ("serves as", "stands as"), "-ing" puffery, and boilerplate filler ("We provide documentation that indicates how..."). Title-case headings and meaningful <b> emphasis preserved. No facts/URLs/counts/versions changed. tpmi.html added as a new file (was previously uncommitted). refs #36642
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
diff --git src/hg/makeDb/trackDb/human/npm.html src/hg/makeDb/trackDb/human/npm.html
index 26e9850021b..1f4386b3b04 100644
--- src/hg/makeDb/trackDb/human/npm.html
+++ src/hg/makeDb/trackDb/human/npm.html
@@ -1,63 +1,62 @@
<h2>Description</h2>
<p>
The <a href="https://www.npm.sg/" target="_blank">National Precision Medicine (NPM)</a> program
in Singapore sequenced 9,770 whole genomes, mostly of Chinese, Indian and Malay ancestry.
A minimum allele count cutoff of >5 was applied. CNV data is also available.
</p>
<h2>Data Access</h2>
<p>
Due to license restrictions, the data for this track cannot be downloaded from the UCSC
Genome Browser. The Table Browser, Data Integrator, and download server are not available
for this track.
</p>
<p>
VCF download can be requested on the <a href="https://chorus.grids-platform.io/"
target="_blank">Chorus Browser</a> website, which requires an
<a href="https://npm.a-star.edu.sg/" target="_blank">account and data access request</a>.
</p>
<h2>Methods</h2>
<p>
-Whole Genome Sequencing (WGS) data processing followed GATK4 best practices. GATK4 germline variant
-analysis workflow written in WDL was adapted to use Nextflow and deployed at the National
-Supercomputing Centre, Singapore (NSCC). WGS reads were aligned against GRCh38 using the BWA-MEM
+Whole Genome Sequencing (WGS) data processing followed GATK4 best practices. The GATK4 germline
+variant analysis workflow written in WDL was adapted to Nextflow and deployed at the National
+Supercomputing Centre, Singapore (NSCC). WGS reads were aligned against GRCh38 with the BWA-MEM
algorithm and used as input to GATK HaplotypeCaller to produce single sample gVCFs. The gVCF files
were joint-called then loaded in Hail. Low-quality WGS libraries and low-quality variants were
-removed. QC-ed variants were functionally annotated using Ensembl Variant Effect Predictor (VEP)
-(version 95). Functional annotations for variants impacting protein-coding regions were also
-complemented with information on the potential alteration to their cognate protein's 3D structure
-and drug binding ability.
+removed. QC-ed variants were functionally annotated with Ensembl Variant Effect Predictor (VEP)
+(version 95). For variants that affect protein-coding regions, the annotations also include
+information on potential changes to the cognate protein's 3D structure and drug binding ability.
</p>
<p>
Our data access request was approved by the NPM data access committee. It can be contacted at <A HREF="mailto:contact_npco@a-star.edu.sg">contact_npco@a-star.edu.sg</A><!-- above address is contact_npco at a-star.edu.sg -->.
We downloaded the data from the NPM Chorus browser download section.
-We provide documentation that indicates how all source files of the varFreqs track were converted in the <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/varFreqs.txt" target="_blank">makeDoc file</a> of the track.
+The <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/varFreqs.txt" target="_blank">makeDoc file</a> of the track documents how all source files of the varFreqs track were converted.
For some tracks, python scripts were necessary and are also available from <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/scripts/varFreqs" target="_blank">GitHub</a>.
</p>
<h2>Credits</h2>
<p>
Thanks to the NPM Data Access Committee and Eleanor for granting our data request.
By browsing the data, you agree to use the data only for academic, non-commercial
research to improve human health (biology/disease). We request all data users
agree to protect the confidentiality of the data subjects in any research papers or publications
that they may prepare, by taking all reasonable care to limit the possibility
of identification. In particular, the data users shall not use, or attempt
to use, the data to deliberately compromise or otherwise infringe the
confidentiality of information on data subjects and their right to privacy.
If you use any of the data obtained from the CHORUS variant browser, we request
that you cite the NPM flagship paper (Wong et al, 2023). All data users of the
data must take note that the data provider and relevant SG10K_Health cohort
owners bear no responsibility for the further analysis or interpretation of the data.
</p>
<h2>References</h2>
<p>
Wong E, Bertin N, Hebrard M, Tirado-Magallanes R, Bellis C, Lim WK, Chua CY, Tong PML, Chua R, Mak K
<em>et al</em>.
<a href="https://doi.org/10.1038/s41588-022-01274-x" target="_blank">
The Singapore National Precision Medicine Strategy</a>.
<em>Nat Genet</em>. 2023 Feb;55(2):178-186.
PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/36658435" target="_blank">36658435</a>
</p>