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/abraom.html src/hg/makeDb/trackDb/human/abraom.html
index 9cbf4351a18..871903a8c9e 100644
--- src/hg/makeDb/trackDb/human/abraom.html
+++ src/hg/makeDb/trackDb/human/abraom.html
@@ -1,63 +1,62 @@
 <h2>Description</h2>
 <p>
 The <a href="https://abraom.ib.usp.br/" target="_blank">Arquivo Brasileiro Online de
 Muta&ccedil;&otilde;es (ABraOM)</a> provides genomic variants obtained with whole-genome sequencing
 from SABE, a census-based sample of elderly individuals from S&atilde;o Paulo, Brazil&apos;s largest
-city. The Brazilian population is constituted by ~500 years of admixture between Africans,
-Europeans, and Native Americans. Additionally, the cohort presents ~3% of individuals with
-non-admixed Japanese ancestry (early 20th century migration). Coverage 38.6x. TEs, HLAs and
-new sequence are also available.
+city. The Brazilian population reflects ~500 years of admixture between Africans,
+Europeans, and Native Americans. About 3% of the cohort has non-admixed Japanese ancestry
+(early 20th century migration). Coverage is 38.6x. TEs, HLAs and new sequence are also available.
 </p>
 
 <h2>Data Access</h2>
 <p>
 The data can be explored interactively with the
 <a href="../cgi-bin/hgTables">Table Browser</a> or the
 <a href="../cgi-bin/hgIntegrator">Data Integrator</a>.
 For programmatic access, our <a href="https://api.genome.ucsc.edu" target="_blank">REST API</a> can be used; the
 track name is <em>abraom</em>.
 For bulk download, the VCF file can be obtained from
 <a href="http://hgdownload.soe.ucsc.edu/gbdb/hg38/varFreqs/" target="_blank">our download server</a>.
 </p>
 <p>
 The original data can also be downloaded from the <a href="https://abraom.ib.usp.br/download/"
 target="_blank">ABraOM website</a>.
 </p>
 
 <h2>Methods</h2>
 <p>
 For academic use only. Licensing for commercial use might be available under request and agreement.
 By using this resource you agree to cite the flagship paper (Naslavsky et al. Nat Comm 2022).
 </p>
 <p>
 Whole-genome sequencing was performed at Human Longevity Inc. using TruSeq Nano DNA HT libraries
 sequenced on Illumina HiSeqX instruments with 150 bp paired-end reads targeting 30x coverage, and
 reads were mapped to GRCh38 using ISIS software. Sample sex was validated by comparing CPMs of X
 chromosome and male-specific Y (MSY) reads relative to autosomes, yielding the expected female
 (~55,000 X CPM, &lt;200 MSY CPM) and male (~27,500 X CPM, &gt;550 MSY CPM) patterns. Germline SNVs
 and indels were called following GATK Best Practices (GATK v3.7) via per-sample GVCFs
 (HaplotypeCaller), joint genotyping (CombineGVCFs, GenotypeGVCFs), and Variant Quality Score
 Recalibration (VQSR-AS); multiallelic variants were split with an in-house script, left-aligned with
 BCFtools, and annotated using Annovar and custom scripts against dbSNP, 1000 Genomes, and gnomAD,
 with putative loss-of-function variants identified using LOFTEE v0.3-beta irrespective of confidence
 labels. Variant and genotype quality was further assessed using the in-house CEGH-Filter two-step
 algorithm based on depth and allele balance, and analyses retained only GATK VQSR-AS PASS variants
 and higher-confidence CEGH-Filter calls. Relatedness was assessed using KING and PC-Relate
 (GENESIS), retaining a single proband per related pair and excluding one contaminated sample
 (&gt;3% by verifyBAMID), resulting in a final dataset of 1,171 unrelated individuals. Final samples
 achieved mean coverages ranging from 31.3x to 64.8x, with an average of 38.65x and a median of
 36.6x.
-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> documents how the 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>References</h2>
 <p>
 Naslavsky MS, Scliar MO, Yamamoto GL, Wang JYT, Zverinova S, Karp T, Nunes K, Ceroni JRM, de
 Carvalho DL, da Silva Sim&otilde;es CE <em>et al</em>.
 <a href="https://doi.org/10.1038/s41467-022-28648-3" target="_blank">
 Whole-genome sequencing of 1,171 elderly admixed individuals from S&atilde;o Paulo, Brazil</a>.
 <em>Nat Commun</em>. 2022 Mar 4;13(1):1004.
 PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/35246524" target="_blank">35246524</a>; PMC: <a
 href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8897431/" target="_blank">PMC8897431</a>
 </p>