find-the-last

Metadata

Description

## Goal
Find the most recently added markdown file in this git repository and report its full contents.

## Approach
1. Use `git log --diff-filter=A --name-only -- '*.md'` to find the last added markdown file(s)
2. Read the contents of the most recent one
3. Report the file path and full contents in your task log

## Validation
- The task log contains the full path and full contents of the most recently git-added .md file

Depends on

• done .assign-find-the-last

Required by

• (none)

Log

• 2026-03-31T20:57:51.796832953+00:00 Task paused
• 2026-03-31T20:57:54.087601182+00:00 Task published
• 2026-03-31T20:58:19.688815837+00:00 Lightweight assignment: agent=Default Evaluator (31847164), exec_mode=light, context_scope=task, reason=Evaluator with proven track record (score 1.00) best fits evaluation/reporting task; light mode for git inspection and file reading
• 2026-03-31T20:58:19.796943279+00:00 Spawned by coordinator --executor claude --model claude-sonnet-4-20250514
• 2026-03-31T20:58:32.819237695+00:00 Starting task - looking for most recently added markdown file
• 2026-03-31T20:58:38.867265731+00:00 Found most recent markdown file: TODO.md (added in commit 340e61d). Now reading its contents.
• 2026-03-31T20:59:29.486038900+00:00 COMPLETED: Found the most recently added markdown file. File path: TODO.md Full contents: # TODO: PHR-specific gene enrichment analysis ## Context Angela Gyamfi (Heather Mefford's student, Memphis) ran GSEA on genes within **1 Mb** of PHR boundaries. Results show strong OR gene enrichment (146-fold, z=18.0) and innate immune gene enrichment, with histone/keratin/MHC class II depletion. But the 1 Mb window is ~10x wider than the median PHR (105 kb), so the analysis captures the *neighborhood*, not just the PHRs themselves. We want to redo this with genes **within the actual PHR intervals** only. ## What we have ### PHR coordinates on CHM13 The file `CHM13-HG002.sub-telo-phrs.bed` contains PHR boundaries for both CHM13 and HG002. The CHM13 rows (lines 1-37) use PanSN naming: ``` CHM13#0#chr1 2706 297706 chr1,chr2,... CHM13#0#chr1 248369277 248384276 chr1,chr2,... ... ``` Column 4 lists which chromosomes share sequence at that arm. There are 37 CHM13 PHR intervals covering the 41 arms with inter-chromosomal signal (some chromosomes have both p and q arm entries). **To make a standard BED**: strip the `CHM13#0#` prefix, giving coordinates directly on CHM13v2.0 chromosome names. ### Gene annotations on CHM13 `chm13v2.0_RefSeq_Liftoff_v5.2.gff3.gz` — RefSeq gene models lifted to CHM13v2.0. This is already in the repo. Alternatively, Andrea's pipeline used CHM13 Liftoff GFF3 files at: ``` /moosefs/guarracino/HPRCv2/PHR_III/hprc_annotations/*.gff3.gz ``` The CHM13 reference annotation is among these 465 files. This is what was used for the per-community gene enrichment in section 9 of the report. For GO enrichment, we should use GENCODE on CHM13 if available, or the RefSeq Liftoff already in the repo. ### Angela's existing gene catalog `PHR_Subtelomeric Regions_Summary_March 2026.xlsx` has 511 gene entries (327 unique) within CHM13 subtelomeric regions, mapped to the 15 Leiden communities. Sheets: - Overview: biotype counts (65 protein-coding, 101 lncRNA, 130 pseudogene, ...) - Protein Coding Genes: 65 unique with disease annotations - lncRNAs: 101 unique with function annotations - Novel T2T: copies resolved by T2T but missing from GRCh38 - Gene Clustering by Chromosome: per-arm gene lists - PCA+Gene Clustering: genes mapped to 15 Leiden communities (C1-C15) ### Angela's GSEA results (1 Mb window) - `Figure1_GSEA_BP_vertical.pdf` — GO Biological Process - `Figure_GSEA_MF_vertical.pdf` — GO Molecular Function - `PHR_enrichment_summary.xlsx` — top-line results (ORA + permutation) - `PHR_enrichment_all_results.xlsx` — all 89 significant GSEA terms ## Task: PHR-only GO enrichment ### Step 1: Extract CHM13 PHR BED From `CHM13-HG002.sub-telo-phrs.bed`, extract CHM13 rows and strip PanSN: ```bash grep '^CHM13#0#' CHM13-HG002.sub-telo-phrs.bed \ | sed 's/CHM13#0#//' \ > chm13.phrs.bed ``` This gives ~37 intervals (the actual PHR regions on CHM13, not 1 Mb windows). ### Step 2: Get CHM13 gene annotations Option A — use RefSeq Liftoff already in repo: ```bash zcat chm13v2.0_RefSeq_Liftoff_v5.2.gff3.gz \ | awk '$3 == "gene"' \ | bedtools intersect -a - -b chm13.phrs.bed -wa \ > phrs.genes.gff3 ``` Option B — use GENCODE CHM13 annotation (download if needed): ``` https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_46/ GRCh38_mapping/gencode.v46.annotation.gff3.gz ``` But we need CHM13 coords, not GRCh38. The CAT/Liftoff annotations from HPRC are the right choice. Get the CHM13 one from Andrea's cluster: ``` /moosefs/guarracino/HPRCv2/PHR_III/hprc_annotations/ ``` ### Step 3: Run GO enrichment With the gene list from step 2, run ORA (over-representation analysis) using clusterProfiler in R or gprofiler2: ```r library(clusterProfiler) library(org.Hs.eg.db) # PHR genes (from bedtools intersect) phr_genes <- read_gene_list("phrs.genes.txt") # Background: all genes in the genome (or all genes in subtelomeric 500kb) # Using all genes as background is conservative enrichGO(gene = phr_genes, OrgDb = org.Hs.eg.db, ont = "BP", pAdjustMethod = "BH", pvalueCutoff = 0.05) ``` Key decision: **what is the background set?** - All human genes → most conservative, tests "are PHR genes enriched vs genome" - Genes in 500 kb subtelomeric flanks → tests "are PHR genes enriched vs the broader subtelomeric region" (this is what Angela's 1 Mb GSEA approximated) - Genes in 1 Mb of chromosome ends → closest to Angela's original analysis Recommendation: run with **all human genes** as background first (simplest, most defensible), then optionally with subtelomeric background. ### Step 4: Compare to Angela's results The PHR-only analysis should: - **Sharpen** the OR gene signal (OR genes are within PHRs, not just nearby) - **Lose** the negative enrichments for histones/keratins/MHC (those are in chromosome interiors, not near PHRs — they appeared in the 1 Mb GSEA because the window was wide enough to be informative about what's NOT near chromosome ends generally) - **Confirm** Angela's community-specific gene mapping in the xlsx ### Step 5: Reconcile with Andrea's report (section 9) Andrea's report already has per-community gene enrichment (section 9) using 174K gene annotations across 233 samples. Key findings: - 374 unique genes across 39 arms - Predominantly pseudogenes (28-86%) and ncRNA - OR4F family in 7 communities - DUX4L in C1, MTCO in C7, SHOX in C15 - RPL23AP45 spans 10 communities (most widespread hub gene) The CHM13-only GO enrichment should be consistent with this but provide the standard GO framework (BP, MF, KEGG) for the paper. ## Files to get from Andrea's cluster ``` # The main PHR TSV (per-haplotype, all 18,827 flanks) /moosefs/guarracino/HPRCv2/PHR_III/all-vs-all.1Mb.p95.id95.len.tsv # CHM13 gene annotation (Liftoff GFF3) /moosefs/guarracino/HPRCv2/PHR_III/hprc_annotations/ (the CHM13 file) # Community assignments # (embedded in Andrea's R scripts / RDS files — need the arm-level # and sequence-level Leiden community labels) ``` ## Notes - The `chm13-annotations.bed` file in the repo has centromere, PAR, XTR, PHR-sex, and PHR-acro coordinates — the latter two are from the 2023 acrocentric paper. The `CHM13-HG002.sub-telo-phrs.bed` is the genome-wide PHR file from the current analysis. - Angela's xlsx maps genes to communities already — we may be able to use her gene list directly for GO enrichment without re-running the bedtools intersection, but should verify coordinates match. - The RefSeq Liftoff in the repo (`chm13v2.0_RefSeq_Liftoff_v5.2.gff3.gz`) is from August 2024 — should be current enough.
• 2026-03-31T20:59:36.634351274+00:00 Validated: Task criteria met - identified last added markdown file (TODO.md) and reported full contents as requested
• 2026-03-31T20:59:42.613871257+00:00 Task marked as done