| # `expression/` — sources |
|
|
| Two human tables. `reference_expression.tsv.gz` holds three references that are **never merged** — different measurements, different units, and |
| a gene-keyed table and a peptide-keyed one are not the same object. |
|
|
| | | | |
| |---|---| |
| | file | `reference_expression.tsv.gz` | |
| | rows | 6,681,814 | |
| | schema | `key`, `key_type`, `source`, `context`, `median_tpm`, `q25_tpm`, `q75_tpm`, `n` | |
| | provenance | **experimental** (all three sources are measured RNA-seq); the per-context median/IQR/`n` are **computed** summaries of it | |
|
|
| | `source` | `key_type` | rows | contexts | what a row is | |
| |---|---|--:|--:|---| |
| | `gtex` | `gene` | 3,955,284 | 53 | a gene's expression across normal tissue — the **safety** read | |
| | `hpa_consensus` | `gene` | 1,025,751 | 51 | the same read over HPA's tissue panel — **the only one that contains thymus** | |
| | `tcga` | `peptide` | 1,700,779 | 19 | a mutant peptide's expression by tumour type — the **target** read | |
|
|
| Total 6,681,814 rows. |
|
|
| `key_type` is the join key and it differs by source on purpose: GTEx and HPA answer "is this gene on |
| in normal tissue", TCGA answers "is this neoantigen transcribed in this tumour". A caller that treats |
| them as one column is asking a question none of them answers. GTEx and HPA are both gene-keyed but |
| are still not interchangeable — see the units caveat in the HPA section below. |
|
|
| Read through `mhcmatch.expression` (`lookup`, `tissues`, `tumor_types`, `safety_profile`), which |
| keeps them apart. Fetched by `mhcmatch bootstrap --reference` (~115 MB). |
|
|
| --- |
|
|
| ## `reference_expression_toil.tsv.gz` — GTEx and TCGA on one pipeline, in one unit |
|
|
| Added 2026-08-26. **This is the table to use when a normal tissue and a tumour type have to be |
| compared, or when one supplies a scale for the other.** |
|
|
| | | | |
| |---|---| |
| | rows | **5,037,966** | |
| | schema | `key`, `key_type`, `source`, `context`, `median_tpm`, `q25_tpm`, `q75_tpm`, `n`, `unit` | |
| | keys | 58,581 gene symbols (`key_type = gene` on every row) | |
| | `source` / contexts | `toil_gtex` — 53 GTEx tissues, 3,104,793 rows · `toil_tcga` — 33 TCGA studies, 1,933,173 rows | |
| | `unit` | `TPM` on every row | |
| | size | 38.6 MB | |
| | provenance | **experimental** — RSEM TPM from RNA-seq; the per-context median/IQR/`n` are **computed** summaries | |
| | built by | `bench/neoag/expression_toil.py` in `2026-mhcmatch-benchmark` | |
|
|
| **Why it exists.** `reference_expression.tsv.gz` carries GTEx in **TPM** and TCGA in **RSEM |
| upper-quartile normalised counts**, both written into a column called `median_tpm`. They are each |
| correct for their own question, but they cannot be put on one axis: a scale taken from one and |
| divided into an abundance from the other is a units error no caller can detect, because the column |
| name says TPM in both cases. This table removes the problem at the source rather than by converting |
| one into the other — a conversion that is not available from the deposited matrix, since RSEM |
| normalised counts are proportional to abundance x effective length and the effective lengths are not |
| published with it. |
|
|
| **Origin.** The UCSC Xena / Toil recompute, which put GTEx, TCGA and TARGET through a **single RSEM |
| pipeline against one annotation (GENCODE v23)** and publishes gene-level TPM for all of them, so a |
| GTEx tissue median and a TCGA study median differ only in the samples that went in. |
|
|
| | input | file | bytes | |
| |---|---|--:| |
| | expression matrix | `TcgaTargetGtex_rsem_gene_tpm.gz` | 1,323,254,426 | |
| | sample phenotype | `TcgaTargetGTEX_phenotype.txt.gz` | 135,753 | |
| | gene annotation | `probeMap/gencode.v23.annotation.gene.probemap` | 3,244,244 | |
|
|
| ``` |
| base=https://toil-xena-hub.s3.us-east-1.amazonaws.com/download |
| curl -L -o xena/TcgaTargetGtex_rsem_gene_tpm.gz $base/TcgaTargetGtex_rsem_gene_tpm.gz |
| curl -L -o xena/TcgaTargetGTEX_phenotype.txt.gz $base/TcgaTargetGTEX_phenotype.txt.gz |
| curl -L -o xena/gencode.v23.annotation.gene.probemap \\ |
| "$base/probeMap%2Fgencode.v23.annotation.gene.probemap" |
| python bench/neoag/expression_toil.py --out expression/reference_expression_toil.parquet |
| ``` |
|
|
| > Vivian J, Rao AA, Nothaft FA, Ketchum C, Armstrong J, Novak A, Pfeil J, Narkizian J, Deran AD, |
| > Musselman-Brown A, Schmidt H, Amstutz P, Craft B, Goldman M, Rosenbloom K, Cline M, O'Connor B, |
| > Hanna M, Birger C, Kent WJ, Patterson DA, Joseph AD, Zhu J, Zaranek S, Getz G, Haussler D, |
| > Paten B. **Toil enables reproducible, open source, big biomedical data analyses.** |
| > *Nat Biotechnol* 2017;35(4):314-316. |
| > PMID [28398314](https://pubmed.ncbi.nlm.nih.gov/28398314/) · |
| > PMC5546205 · doi:[10.1038/nbt.3772](https://doi.org/10.1038/nbt.3772) |
|
|
| > Goldman MJ, Craft B, Hastie M, Repecka K, McDade F, Kamath A, Banerjee A, Luo Y, Rogers D, |
| > Brooks AN, Zhu J, Haussler D. **Visualizing and interpreting cancer genomics data via the Xena |
| > platform.** *Nat Biotechnol* 2020;38(6):675-678. |
| > PMID [32444850](https://pubmed.ncbi.nlm.nih.gov/32444850/) · |
| > PMC7386072 · doi:[10.1038/s41587-020-0546-8](https://doi.org/10.1038/s41587-020-0546-8) |
|
|
| **The TCGA study code is joined through the barcode, never through the disease name.** Xena labels a |
| TCGA sample with a disease name (`Uveal Melanoma`); the rest of this compendium keys on the study |
| abbreviation (`UVM`). A hand-written name->code crosswalk can be silently wrong, so the code is taken |
| from PanCanAtlas `merged_sample_quality_annotations.tsv` on the 15-character sample barcode, which is |
| exact. **17,474 of 19,131 matrix columns are used**: 9,616 TCGA tumour aliquots and 7,862 GTEx |
| samples. TARGET (734 columns) is dropped -- paediatric, and none of its diseases has a matched normal |
| here -- as are TCGA adjacent normals and aliquots the source flags `Do_not_use`. |
|
|
| **Upstream values are `log2(TPM + 0.001)` and are inverted on build**, so what is stored is TPM. |
|
|
| **Caveats.** |
| - **The GTEx contexts are Toil-era, not v11.** `reference_expression.tsv.gz` is GTEx v11; this is the |
| earlier release Toil reprocessed, so the two GTEx halves are neither the same samples nor the same |
| depth. They are also not spelled the same: Toil writes `Skin - Sun Exposed (Lower Leg)` and GTEx |
| v11 writes `Skin - Sun Exposed (Lower leg)`. **A context string cannot be carried from one table |
| to the other without checking.** |
| - **Three tissues are thin and are kept with their `n` rather than dropped**: Bladder (9), |
| Cervix - Ectocervix (6), Fallopian Tube (5). They are the matched normals of BLCA, OV and CESC, so |
| dropping them would remove the safety read for three tumour types. `Cervix - Endocervix` has fewer |
| than five samples and is absent; CESC still resolves through Ectocervix. Every TCGA study clears 36. |
| - **353 of 58,581 symbols carry more than one Ensembl gene id** (0.6 %). The row kept per |
| (symbol, context) is the one with the **highest median**, not a sum across loci: a lookup asks |
| whether a gene is on in this context, and the dominant locus answers it without inventing a total |
| across paralogues. 164,862 duplicate rows were collapsed this way. |
| - `n` is a **sample** count here, as in the GTEx half, and not the transcript count the mouse table's |
| `n` is. |
|
|
| **What a floor built from it looks like**, as the 25th percentile of non-zero gene medians: |
| TCGA runs 0.1200 (KICH) to 0.3700 (LAML) TPM, a **3.08x** spread over 33 studies; GTEx runs 0.1000 |
| (Whole Blood) to 0.4000 (Testis), **4.00x** over 53 tissues. Pooled, TCGA is 0.1800 TPM over 882,959 |
| non-zero gene rows and GTEx 0.2700 over 1,402,705. **A tumour's own floor is consistently below its |
| matched normal's** -- SKCM 0.1600 against skin 0.3050 (0.52x), BLCA 0.1700 against bladder 0.3600 |
| (0.47x), LUAD 0.2000 against lung 0.3500 (0.57x), BRCA 0.1900 against breast 0.3000 (0.63x). |
|
|
| **Format: parquet, and the record is not in the bootstrap set.** As gzipped TSV this table was |
| 70.5 MB and 0.5 s to read with polars (5.2 s with the standard library); dictionary-encoded and |
| zstd-compressed it is **38.6 MB and 0.04 s**. On a link measured here at 154 kB/s that is three and |
| a half minutes of download saved, which is the difference between a bootstrap that finishes and one |
| that looks like it has hung. `mhcmatch bootstrap --reference` stages only the three companions |
| below — 6.6 MB between them, carrying the same numbers — and never this file. |
|
|
| **Label arrays in the `.npz` are fixed-width unicode, not `dtype=object`.** An object array is |
| pickled, and `np.load` needs `allow_pickle=True` to read it back; a pickled array in a file fetched |
| over the network executes on load. The deposit is written so that flag is never needed. |
|
|
| ### Its three companions, and why scoring never reads the table itself |
|
|
| Added 2026-08-26 beside it. `reference_expression_toil.tsv.gz` is the record; these are what a |
| program actually opens. |
|
|
| | file | size | what it is | |
| |---|--:|---| |
| | `toil_matrix.npz` | 6,632,665 B | the whole table as a dense **58,581 gene x 86 context float32 matrix**, contexts keyed `"<source>|<context>"` | |
| | `toil_floors.tsv` | 8,365 B | 88 rows -- each context's abundance floor at q05, q10, q25, plus a pooled row per cohort | |
| | `context_synonyms.tsv` | 29,334 B | 448 rows, 184 aliases -- how a free-text origin becomes a context | |
|
|
| **The matrix exists so a lookup does not cost a whole table.** Answering *what is this gene in this |
| tumour type* from the TSV means building a five-million-entry dictionary of dictionaries: measured, |
| **5.20 s and 3,168 MB resident**. The matrix is **0.05 s and 29 MB** -- 100x the speed on 1/109 of |
| the memory -- and every lookup a resolution chain makes is one array index. Both return the same |
| floor to four decimals, which is how the matrix is checked against the table it came from. A gene absent from a context is `0.0` and not `nan`: every gene here was |
| measured in every context that cleared the sample threshold, so absence is silence, and silence is a |
| measurement. Whether a *gene* is in the reference at all is a separate question and is reported |
| separately -- silence and ignorance must not collapse into one number. |
|
|
| **`context_synonyms.tsv` is derived, not hand-written.** Long format, one target per row, so it |
| sorts and joins like data rather than holding lists in cells: |
| |
| | alias_kind | where the aliases come from | rows | |
| |---|---|--:| |
| | `code` | the 33 TCGA studies in the matrix | 83 | |
| | `site` | Xena `_primary_site`, joined to the PanCanAtlas study code on the 15-character barcode | 218 | |
| | `disease` | Xena `detailed_category`, joined the same way | 83 | |
| | `gtex` | the 53 GTEx contexts in the matrix | 64 | |
| |
| **One alias resolves to two things and each is its own row**, which is why the alias count and the |
| row count differ: 150 rows carry `target_kind = tcga_code` and 298 carry `gtex_context`, so |
| `hepatocellular` names both `LIHC` and `Liver`. 152 of the 448 rows are `derived:*` and 296 are |
| `curated:*`, and the `provenance` column says which on every row. The curated majority is the |
| matched-normal half and the adjectival forms a free-text origin actually arrives in |
| (`cervical`, `pancreatic`, `uterine corpus`); the derived half is what the matrix and the barcode |
| join supply on their own. Hand-writing this would have been wrong in the places nobody checks: **an organ is |
| more than one study more often than not** -- `Lung` is `LUAD` *and* `LUSC`, `Kidney` is three -- and a |
| crosswalk that picks one is silently wrong for the rest. The tumour-to-matched-normal half is carried |
| from `mhcmatch.expression.TUMOR_TISSUE` against the spellings this matrix uses, because Toil writes |
| `Brain - Frontal Cortex (Ba9)` where GTEx v11 writes `(BA9)` and an exact match drops it. |
|
|
| An alias that does not resolve **raises**. Falling back to the pooled reference would return a |
| plausible number computed from the wrong distribution with nothing downstream able to tell. |
|
|
| **A note on what these floors are for.** `c` is a property of a transcriptome, and the numerator is |
| one candidate's abundance. Where the numerator is not in reference TPM the two stop cancelling, and |
| the obvious repair -- a median of ratios against the reference -- **must not be estimated from a |
| candidate list**. A mutation reaches such a list only if it was called, and only where the gene was |
| seen in RNA, so the ratio measures that conditioning instead of the library: on three screens whose |
| columns are all deposited as TPM it returns 1.78, 2.18 and 3.15, never below 1. `mhcmatch` gates it |
| on coverage of the reference transcriptome for that reason, and a candidate list cannot clear it. |
|
|
| --- |
|
|
| ## Mouse — `reference_expression_mmu.tsv.gz` and `protein_abundance_mmu.tsv.gz` |
|
|
| Added 2026-08-21. The compendium's normal-tissue safety read was GTEx, and GTEx is human, so a mouse |
| epitope had no reference to be scored against. These two files are the mouse counterpart. |
|
|
| **They are two files, not one, and that is deliberate.** The human table's value column is literally |
| `median_tpm`. RNA and protein are different measurements in different units, and writing a SILAC |
| abundance into a `_tpm` column would be a units lie no caller could detect. |
|
|
| ### `reference_expression_mmu.tsv.gz` — the GTEx analogue |
|
|
| | | | |
| |---|---| |
| | rows | **659,050** | |
| | schema | `key`, `key_type`, `source`, `context`, `median_tpm`, `q25_tpm`, `q75_tpm`, `n` — **column for column identical to the human file** | |
| | keys | 18,830 gene symbols (`key_type = gene`) | |
| | contexts | **35 adult tissues** | |
| | `source` | `fantom5_mouse` | |
| | provenance | **experimental** — CAGE tag counts; the per-gene median across transcripts and the quantile summary are **computed** | |
|
|
| **Origin.** EBI Expression Atlas [E-MTAB-3579](https://www.ebi.ac.uk/gxa/experiments/E-MTAB-3579), |
| the RIKEN FANTOM5 mouse CAGE atlas. `q25_tpm` / `median_tpm` / `q75_tpm` are taken from the Atlas' |
| own five-number summary per gene × group; they are not re-derived here. |
|
|
| > Lizio M, Harshbarger J, Shimoji H, Severin J, Kasukawa T, Sahin S, Abugessaisa I, Fukuda S, |
| > Hori F, Ishikawa-Kato S, Mungall CJ, Arner E, Baillie JK, Bertin N, Bono H, de Hoon M, Diehl AD, |
| > Dimont E, Freeman TC, Fujieda K, Hide W, Kaliyaperumal R, Katayama T, Lassmann T, Meehan TF, |
| > Nishikata K, Ono H, Rehli M, Sandelin A, Schultes EA, 't Hoen PAC, Tatum Z, Thompson M, |
| > Toyoda T, Wright DW, Daub CO, Itoh M, Carninci P, Hayashizaki Y, Forrest ARR, Kawaji H. |
| > **Gateways to the FANTOM5 promoter level mammalian expression atlas.** |
| > *Genome Biol* 2015;16:22. |
| > PMID [25723102](https://pubmed.ncbi.nlm.nih.gov/25723102/) · |
| > doi:[10.1186/s13059-014-0560-6](https://doi.org/10.1186/s13059-014-0560-6) |
|
|
| **Only plain `adult` groups are kept** — 35 of the deposit's 170. GTEx is adult normal tissue; |
| folding an E14 embryo, a pregnancy timepoint or a lactating mammary gland into a "is this gene on in |
| normal tissue" safety read answers a different question. The other stages are in the source and are |
| recoverable by re-running without the filter. |
|
|
| **A parsing trap worth recording.** Atlas group labels are two `;`-separated parts and **the order |
| is not fixed**: 136 of the 170 are stage-first (`adult; thymus`) and 32 are tissue-first |
| (`adrenal gland; adult`). Taking either position blindly mislabels a third of the table — the first |
| build of this file produced contexts named `adult` and `whole body` that way. The stage is matched by |
| vocabulary wherever it sits, and the tissue is whatever remains. |
|
|
| **Checked against known biology, not assumed.** Of 35 tissues, thymus ranks **first** for `Prss16` |
| (31 TPM), `Psmb11` (88), `Dntt` (961), `Rag1`, `Cd8a` (131) and `Lck` (12) — thymic epithelium and |
| thymocyte genes. As a negative control `Cela1` peaks in pancreas at 225,010 TPM against 0.3 in |
| thymus. |
|
|
| **Caveats.** |
| - **`n` is 1 for every row.** FANTOM5 provides one library per adult tissue, so `q25`/`q75` describe |
| the spread across transcripts of a gene, **not across animals**. GTEx `n` runs to several hundred |
| donors. Do not read the two `n` columns as the same quantity. |
| - **`Aire` is 0 TPM in thymus here, and that is a detection floor, not biology.** Aire is expressed |
| in a rare mTEC subset; bulk CAGE at this depth cannot see it. Any promiscuous-expression question |
| needs sorted mTEC data, not this file. |
| - CAGE measures 5′-capped tag density. It is reported as TPM and behaves like expression, but it is |
| not RNA-seq TPM and the two are not numerically interchangeable across sources. |
|
|
| ### `tumor_expression_mmu.tsv.gz` — the mouse TUMOUR read, and why it is a separate file |
|
|
| Added 2026-09-04. `reference_expression_mmu.tsv.gz` answers the *safety* half of the expression |
| question -- is this gene on in normal tissue -- and there was no counterpart for the *ranking* half. |
| Mouse has no TCGA, so a mouse neoantigen's own abundance fell back to the gene's normal-tissue |
| median, which is the number `expr_norm` already carries. Measured on the 923 class-I rows of the |
| IEDB mouse neoantigen deposit, `expr_lvl` and `expr_norm` came out **identical on 100 %** of the |
| rows lacking a deposited abundance: two fitted terms on one column. |
|
|
| | | | |
| |---|---| |
| | rows | **149,640** | |
| | schema | `key`, `key_type`, `source`, `context`, `median_tpm`, `q25_tpm`, `q75_tpm`, `n` — **column for column identical to the two files above** | |
| | keys | 24,940 gene symbols (`key_type = gene`) | |
| | contexts | **6 syngeneic tumour models**: B16F10, CT26, E0771, LLC, MC38, Panc02 | |
| | `source` | `gse245293_syngeneic` | |
| | `n` | **3 on every row** — three biological replicates per model, so `q25`/`q75` are a spread across *animals*, unlike the FANTOM5 file's spread across transcripts | |
| | provenance | **experimental** — RNA-seq counts; the length normalisation, the per-model quantiles and the gene-level aggregation are **computed** | |
|
|
| **Origin.** NCBI GEO [GSE245293](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE245293), |
| supplementary file `GSE245293_Normalized_count_table_tumor.txt.gz` (2.9 MB), staged at |
| `raw/expression_mouse/`. 23 samples in the series; the 18 `*_tumor_rep*` columns are used and the |
| 8 CAF (cancer-associated fibroblast) columns are **not** -- those are stroma, not the tumour |
| transcriptome, and folding them in would answer a different question. |
|
|
| curl -O https://ftp.ncbi.nlm.nih.gov/geo/series/GSE245nnn/GSE245293/suppl/GSE245293_Normalized_count_table_tumor.txt.gz |
| python src/build_tumor_expression_mmu.py # in ~/vcs/projects/public_expression_peptidomes |
| |
| > Comparison of syngeneic tumor models reveals different tumor microenvironments with distinct |
| > subsets of cancer-associated fibroblasts polarized by infiltrating T cells. GEO GSE245293, |
| > deposited 2023-10-13, released 2024-01-29. *Mus musculus*, expression profiling by high |
| > throughput sequencing. |
|
|
| **Units are computed and the file says so.** The deposit is **normalised counts** with a `Length` |
| column, not TPM. Length-normalising each sample and rescaling to a million gives a TPM-like |
| quantity comparable *within* this table; it is **not** interchangeable with FANTOM5 CAGE TPM or |
| with GTEx RSEM TPM. `mhcmatch.rank.expr_level` is unit-free when its floor is a quantile of the |
| same column, which is exactly why a floor for these contexts must be taken from this file. |
|
|
| **Checked against known biology, not assumed.** Three independent melanocytic markers separate the |
| melanoma line by three orders of magnitude: `Tyr` **398.9**, `Dct` **4,611.8** and `Pmel` |
| **4,636.7** TPM in B16F10 against ≤ 4.3 in all five other models. They would all move together if |
| the sample-to-model mapping were wrong. |
|
|
| **Colon markers were tried and do not work here; do not re-try them.** `Muc2` reads ~0 in every |
| model -- CT26 is an undifferentiated colon carcinoma and makes no goblet-cell mucin -- and |
| `Cdx1`/`Cdx2` do not separate CT26 and MC38 from the rest (Cdx2 is highest in Panc02, 8.8 against |
| CT26's 1.4). The expectations were wrong, not the data. |
|
|
| **Coverage of the IEDB mouse neoantigen deposit**, joining on model × gene symbol: **347 of 968 |
| class-I rows (36 %)** and **304 of 522 class-II rows (58 %)**. The class-II figure is the reason |
| this file exists -- that arm previously had a deposited abundance on 13 % of its rows. |
|
|
| **Two models it does not carry** that the neoantigen deposit names often: `P815` (89 rows) and the |
| `T3`/`CMS5`/`Meth A` fibrosarcomas (150 rows between them). Those still take the pooled floor. |
|
|
| ### `PRJNA1271699` — located, not fetched |
|
|
| [PRJNA1271699](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1271699), *"Mouse syngeneic model |
| RNAseq sequencing"* (CrownBio), submitted 2025-06-04: **120 runs over 12 models × 10 replicates** |
| -- A20, B16BL6, B16F10, CT26, EMT6, H22, Hepa16, LL2, MC38, Pan02, RM1, Renca -- paired-end |
| Illumina NovaSeq 6000, **418 GB** of raw reads. It would cover Renca and EMT6, which nothing here |
| does. |
|
|
| **NCBI carries raw reads only; there is no processed matrix.** The BioProject abstract advertises |
| an interactive resource at `https://muscreen.crownbio.com/syngeneic_omics`, and **as of 2026-09-04 |
| that URL is dead** -- `/syngeneic_omics` returns 404 and the host root returns a bare Apache |
| default page (403). So the processed tables the abstract promises are not currently retrievable, |
| and using this project means downloading 418 GB and running an alignment pipeline. Recorded here |
| so the cost is known rather than rediscovered. |
|
|
| **This is the source to re-process if these models are wanted here** -- it is the one that covers |
| P815, Renca and EMT6, which `tumor_expression_mmu.tsv.gz` does not. |
|
|
| # metadata only, no reads: |
| curl -sS "https://trace.ncbi.nlm.nih.gov/Traces/sra-db-be/runinfo?acc=PRJNA1271699" |
| |
| ### `toil_matrix_mmu.npz` + `toil_floors_mmu.tsv` — the harmonised mouse compendium |
|
|
| Added 2026-09-04. The mouse counterpart of `toil_matrix.npz` / `toil_floors.tsv`, same array names |
| and the same `source|context` key shape, so code written against the human pair reads this one. |
|
|
| | | | |
| |---|---| |
| | shape | **26,737 genes x 68 contexts**, dense float32 | |
| | `genes` | official NCBI symbol, synonyms resolved via Ensembl release-100 (= GENCODE M25) and NCBI Gene | |
| | `contexts` | `fantom5_mouse\|<tissue>` x 35 normal, `gse245293\|<model>` x 6 tumour, `prjna1271699+\|<model>` x 27 tumour | |
| | `values` | linear TPM-like, **harmonised across sources**; `NaN` = the gene is absent from that source, which is not the same as measured at zero | |
| | `n_samples` | 3 for GSE245293 (replicate **mean**), 1 for FANTOM5, 0 where the source reports none | |
| | `toil_floors_mmu.tsv` | 71 rows -- each context's floor at q05/q10/q25, plus a pooled row per source, same seven columns as the human file | |
|
|
| **Sources.** FANTOM5 mouse CAGE (EBI E-MTAB-3579); GEO **GSE245293** (6 syngeneic models x 3 |
| replicates); and the CrownBio syngeneic panel, labelled `prjna1271699+` for NCBI BioProject |
| **PRJNA1271699** plus the further models that panel carries beyond the 12 the accession lists. |
| GSE245293 wins the five models both cover. The 27 filled models include **P815, Renca and EMT6**, |
| which no other deposit here reaches. |
|
|
| **Harmonised, and here is what that means.** The three sources sat on three scales -- pooled mean |
| `log2(1 + TPM)` of 1.721, 2.513 and 2.059. Each source's non-zero values are quantile-mapped onto |
| the mean of the three sources' quantile functions; **per source, not per context**, so |
| between-context structure survives. Zero maps to zero. The map is monotone and its grid spans each |
| source's support, so **every within-context rank is preserved exactly** -- which is what |
| `mhcmatch.rank.expr_level` consumes. Non-zero spread falls 0.577 -> 0.087 log2 units, and the |
| pooled q25 floor agrees to 0.714--0.717 across all three. |
|
|
| Two things it does not do. It cannot correct a **gene-specific** platform effect: `Actb` reads 3,032 |
| in B16F10 and 10.4 in FANTOM5 thymus after harmonisation, because CAGE at that promoter genuinely |
| ranks it mid-distribution. And it cannot correct the **detection-rate** difference (65.2 / 78.1 / |
| 65.0 % non-zero), because a monotone map that respects zero cannot move it. |
|
|
| **Absolute values are no longer any one source's own number.** That is the trade: comparability |
| across all 68 contexts, at the cost of each source's internal scale. The unharmonised per-source |
| tables are not deposited; `tumor_expression_mmu.tsv.gz` and `reference_expression_mmu.tsv.gz` above |
| remain the unharmonised reads of two of the three sources. |
|
|
| Built by `src/build_deposit_mmu.py` in `~/vcs/projects/public_expression_peptidomes`; the protocol |
| and its numbers are `results/expression_harmonization.md` there. |
|
|
| **For comparison, the human pair needed none of this.** Same measurement on `toil_matrix.npz`: |
| `toil_gtex` and `toil_tcga` pooled means differ by **0.011** log2 units, against 0.565 for the |
| mouse CAGE-vs-RNA-seq seam. Both human halves went through one Toil RSEM recompute, and it worked. |
|
|
| ### `protein_abundance_mmu.tsv.gz` — the protein-level read |
|
|
| | | | |
| |---|---| |
| | rows | **133,848** | |
| | schema | `key`, `key_type`, `source`, `context`, `abundance`, `unit`, `n` | |
| | keys | 5,148 gene symbols | |
| | contexts | **26 tissues**, including thymus | |
| | `source` / `unit` | `geiger_silac_mouse` / `ppb_ibaq` | |
| | provenance | **experimental** — SILAC-normalised MS abundance | |
|
|
| **Origin.** EBI Expression Atlas [E-PROT-11](https://www.ebi.ac.uk/gxa/experiments/E-PROT-11). |
|
|
| > Geiger T, Velic A, Macek B, Lundberg E, Kampf C, Nagaraj N, Uhlen M, Cox J, Mann M. |
| > **Initial quantitative proteomic map of 28 mouse tissues using the SILAC mouse.** |
| > *Mol Cell Proteomics* 2013;12(6):1709–1722. |
| > PMID [23436904](https://pubmed.ncbi.nlm.nih.gov/23436904/) · |
| > doi:[10.1074/mcp.M112.024919](https://doi.org/10.1074/mcp.M112.024919) |
|
|
| **Why keep a protein table at all.** A peptide can only be presented if the protein was translated, |
| so for immunopeptidome work protein abundance is the more direct evidence and RNA is a proxy. It is |
| much shallower — 5,148 genes against 18,830 — so it complements the RNA table rather than replacing |
| it. |
|
|
| ### Why not E-PROT-13 |
|
|
| [E-PROT-13](https://www.ebi.ac.uk/gxa/experiments/E-PROT-13) (Huttlin's mouse phosphorylation and |
| expression atlas) was the first candidate considered. It covers **9 tissues and does not include |
| thymus**, so it cannot serve either purpose here. Of the **65 mouse baseline experiments in |
| Expression Atlas, only six contain thymus**; E-MTAB-3579 (35 adult tissues) and E-PROT-11 (26) are |
| the only two of those with broad tissue coverage. |
|
|
| ### Regenerate |
|
|
| cd ~/vcs/projects/public_expression_peptidomes && ./src/build_expression_mmu.py |
| |
| --- |
|
|
| ## Human — the `hpa_consensus` arm, and why GTEx alone was not enough |
| |
| Added 2026-08-21, in the same pass that built the mouse references. |
| |
| **GTEx has no thymus.** Its 53 contexts contain no thymus, no lymph node and no bone marrow — adult |
| thymus involutes and is not routinely sampled, so the normal-tissue safety read was blind to the one |
| tissue central tolerance actually happens in. Expression Atlas is no better: of its **123 human |
| baseline experiments only three carry any thymus group**, and all three are compromised for this |
| purpose — E-MTAB-3871 is fetal tissue from fetuses with congenital defects, E-MTAB-3827 is sorted |
| thymocyte subsets rather than tissue, and E-MTAB-9641 is thymic epithelium cultured on a 3T3-J2 |
| feeder layer. |
| |
| HPA samples thymus directly, so its consensus tissue set is what fills the hole. |
| |
| | | | |
| |---|---| |
| | rows | **1,025,751** | |
| | keys | 20,151 gene symbols (`key_type = gene`) | |
| | contexts | **51 tissues, including thymus** | |
| | `source` | `hpa_consensus` | |
| | provenance | **experimental** — RNA-seq; the HPA consensus normalisation is **computed** | |
|
|
| **Origin.** [`rna_tissue_consensus.tsv.zip`](https://www.proteinatlas.org/download/tsv/rna_tissue_consensus.tsv.zip) |
| from the Human Protein Atlas. |
|
|
| > Uhlén M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, Sivertsson Å, Kampf C, |
| > Sjöstedt E, Asplund A, Olsson I, Edlund K, Lundberg E, Navani S, Szigyarto CA, Odeberg J, |
| > Djureinovic D, Takanen JO, Hober S, Alm T, Edqvist PH, Berling H, Tegel H, Mulder J, Rockberg J, |
| > Nilsson P, Schwenk JM, Hamsten M, von Feilitzen K, Forsberg M, Persson L, Johansson F, Zwahlen M, |
| > von Heijne G, Nielsen J, Pontén F. |
| > **Tissue-based map of the human proteome.** |
| > *Science* 2015;347(6220):1260419. |
| > PMID [25613900](https://pubmed.ncbi.nlm.nih.gov/25613900/) · |
| > doi:[10.1126/science.1260419](https://doi.org/10.1126/science.1260419) |
|
|
| **It is added as a third `source`, not merged into GTEx and not replacing it.** The schema was |
| designed with a `source` column for exactly this; every existing `gtex` and `tcga` row is untouched. |
|
|
| **Checked against known biology.** Of 51 tissues, thymus ranks **first** for `PRSS16` (770 nTPM), |
| `PSMB11` (28.5), `DNTT` (306), `CD1A` (296), `RAG1` (368), `CCL25` (718), `CD3E` (596) and `LCK` |
| (326). Negative controls behave: `ALB` peaks in liver at 198,524 nTPM against 0.3 in thymus, `INS` in |
| pancreas, `MYH7` in skeletal muscle. |
|
|
| **Caveats.** |
| - **nTPM is not GTEx TPM.** Both are TPM-family units but the normalisation differs, so compare |
| *within* a `source`, not across. This is what the `source` column is for. |
| - `n` is 1 — HPA consensus publishes one value per gene × tissue, so `q25_tpm` and `q75_tpm` equal |
| `median_tpm` and carry no spread. GTEx `n` runs to several hundred donors; the two `n` columns are |
| not the same quantity. |
| - **`AIRE` is detectable here (1.2 nTPM, rank 2 of 51) but reads 0 in the mouse CAGE atlas.** That is |
| a difference in assay depth, not in biology — do not read it as a species difference. |
|
|
