9bfd58221b1539193cb7f0a317b4e959c1c7e49a
max
  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/tishkoff180.html src/hg/makeDb/trackDb/human/tishkoff180.html
index 661aa78a1f4..d20a40f1449 100644
--- src/hg/makeDb/trackDb/human/tishkoff180.html
+++ src/hg/makeDb/trackDb/human/tishkoff180.html
@@ -1,19 +1,19 @@
 <h2>Description</h2>
 <p>
 This track shows allele frequencies from high-coverage whole-genome sequencing of
-180 individuals (15 per population) from 12 indigenous African populations representing
+180 individuals (15 per population) from 12 indigenous African populations that cover
 all four major African language phyla (Khoesan, Niger-Congo, Nilo-Saharan, Afroasiatic).
 The cohort, generated by the Tishkoff lab and collaborators (Fan et al., <em>Cell</em> 2023),
 spans the Amhara, Dizi, Chabu and Mursi from Ethiopia; the Hadza and Sandawe from Tanzania;
 the Central African rainforest hunter-gatherers (Baka and Bagyeli, merged), Fulani and Tikari
 from Cameroon; and the Herero, Ju|&apos;hoansi and !Xoo (the latter two collectively the &quot;San&quot;)
 from Botswana. The dataset was generated to capture demographic history and signatures of
 local adaptation in African populations that are poorly represented in other reference panels.
 </p>
 
 <p>
 Only aggregate allele frequencies (AC, AF, AN summed over all 180 individuals) are
 shown for each variant; per-population frequencies are not provided in the released
 sites VCF. The original variant calls were on the GRCh37/hs37d5 reference and were
 lifted to hg38 at UCSC.
 </p>
@@ -23,32 +23,32 @@
 Variants display as standard VCF allele frequency tracks. On mouseover and click,
 the allele count (AC), total allele number (AN) and allele frequency (AF) are shown.
 When zoomed in, alleles are colored by base. Multi-allelic records were split into
 biallelic rows during normalization upstream.
 </p>
 
 <h2>Methods</h2>
 <p>
 Whole genome sequencing of 180 individuals (15 unrelated samples per population)
 was performed at &gt;30&times; average coverage on the Illumina HiSeq X Ten platform
 using PCR-free library preparation with paired-end 150&nbsp;bp reads and a 350&nbsp;bp
 insert size. Adapters were trimmed with trimadap, optical duplicates were marked with
 SAMBLASTER (v0.1.22), and reads were aligned to the hs37d5 decoy version of GRCh37
 with BWA-MEM (v0.7.10). Reads with mapping quality &lt;&nbsp;20 were filtered. Per-sample
 short variants were called with GATK HaplotypeCaller (nightly-2016-09-26-gfade77f) in
-gVCF mode using a custom genotype prior (0.4995, 0.001, 0.4995) to reduce reference
-bias, following the SGDP recommendation. Joint genotyping was performed with GATK
+gVCF mode with a custom genotype prior (0.4995, 0.001, 0.4995) to reduce reference
+bias, as recommended by SGDP. Joint genotyping was performed with GATK
 GenotypeGVCFs. Variants were filtered with GATK VQSR using 1000 Genomes Phase 3,
 Illumina Omni 5M and HapMap as SNP truth sets and Mills indels as the indel truth set.
 Variants overlapping potential duplications detected by Delly (v0.7.6) and low-complexity
 regions were excluded. After QC the cohort yielded 32.4&nbsp;M SNPs and 2.8&nbsp;M small
 indels. The publicly released SNP-only sites VCF used here contains 33.6&nbsp;M
 biallelic SNPs with aggregate AC/AF/AN summaries. See Fan et al. (2023) for full
 methods.
 </p>
 
 <p>
 The hg19 SNPs sites VCF was provided directly by Matthew Hansen at the Tishkoff lab
 (University of Pennsylvania) via a Box link
 (<tt>180wgs.SNPs.sites.AF.vcf.gz</tt>). Bare chromosome names (1-22) were converted
 to UCSC-style names with <tt>bcftools annotate --rename-chrs</tt>, the VCF was lifted
 from hg19 to hg38 with <tt>CrossMap.py vcf</tt> using the UCSC