solo: EmptyDrops_CR on CellRanger's actual statistics (SGT ambient profile, libc++ sampler) by BenjaminDEMAILLE · Pull Request #156 · scverse/rustar-aligner

BenjaminDEMAILLE · 2026-07-29T08:22:47Z

--soloCellFilter EmptyDrops_CR computes what CellRanger computes: a Simple-Good-Turing ambient profile, sampled with libc++'s generator.

What changed

The ambient profile is smoothed with Simple Good-Turing (src/solo/sgt.rs), the method CellRanger uses and STAR vendors as Elworthy's sgt.h. The ambient counts come from a small sample of empty droplets, so a gene seen twice there is not twice as likely as one seen once, and a gene seen zero times is not impossible — it is one the sample was too small to show. SGT reserves mass for the unseen from the singleton rate and smooths the rest along a fitted log-log line.

What this replaces had the right shape and the wrong numbers: it reserved unseen mass the same way, then distributed the remainder in proportion to raw counts with no smoothing at all.

The Monte-Carlo null is drawn with libc++'s std::mt19937 and std::discrete_distribution (src/solo/libcxx_rng.rs), seeded 19760110 * (isim + 1) per simulation as STAR seeds it. The standard fixes mt19937's output but not how generate_canonical consumes it, nor how discrete_distribution maps a uniform draw onto categories, so reproducing STAR's numbers needs libc++'s algorithm specifically, not a correct categorical sampler.

The module is wired into the EmptyDrops path in this same PR — it is not a module landed ahead of its use.

Why

solo::count sampled with a SplitMix64 stream under a comment calling it "WeightedIndex-equivalent; empirically byte-identical EmptyDrops cell calls". That claim cannot hold in general: two unrelated generators cannot agree over an arbitrary number of draws. It was true of whatever cases were checked and unknown everywhere else.

Divergence

DIVERGENCE.md §1.2. STAR leaves PZero uninitialised when the ambient spectrum has fewer than five distinct frequencies and analyse() bails, so it reads whatever the stack held. Here it is zero from construction. Degenerate inputs only, but on those an uninitialised read can place arbitrary mass on unseen genes.

Verification

Every expected value in the RNG tests was produced by compiling a C++ program against real libc++ (clang++ -stdlib=libc++) and printing the results, not derived from reading its source. tests/libcxx_oracle.cpp is in-tree so they can be regenerated. generate_canonical is asserted on bit patterns rather than decimals: a difference in the last place changes which category a sample lands in.

SGT tests cover a well-formed spectrum summing to one, monotonicity in the observation count, the absent-count case, the no-singletons case, and the D17 guard.

Gate: 570 lib + 26 integration tests, cargo clippy --all-targets -- -D warnings, cargo fmt --check, MSRV 1.89 — all green.

test/solo_diff_docker.sh (one run, Linux container with STAR 2.7.11b) passes:

PASS: rustar-aligner matrix matches real STARsolo exactly.
PASS: Gene raw matrix byte-identical to STARsolo (3 entries)
PASS: GeneFull raw matrix byte-identical to STARsolo (3 entries)

Read that for what it is. The harness exercises the raw matrix, which these changes do not touch, so it confirms nothing was broken on the way past — not that the cell calls are right. Both changes move filtered/ membership by construction, and the harness has no EmptyDrops fixture to compare against. Validating the cell calls themselves needs a dataset with a known CellRanger filtered/ result, which the harness does not currently carry.

Split out of #152 following the one-theme rule in CONTRIBUTING.md.

…_distribution STARsolo's `EmptyDrops_CR` rescue draws from `std::mt19937`, converts to doubles with `std::generate_canonical<double, 53>`, and picks categories with `std::discrete_distribution`. Two of those three are implementation-defined in the parts that matter: the standard fixes mt19937's output but not how `generate_canonical` consumes it, and says nothing about how `discrete_distribution` maps a uniform onto categories. So porting "the algorithm" is not enough — it has to be libc++'s algorithm, because that is what STAR is built against and where its numbers come from. libc++ accumulates two 32-bit draws in *ascending* significance and divides by 2^64; a most-significant-first accumulation, or one draw scaled to 53 bits, both give perfectly good uniforms and neither reproduces STAR. Every expected value in the tests came out of a C++ program compiled against the real libc++ and run, not from reading its source. `tests/libcxx_oracle.cpp` is that program, kept so the values can be regenerated rather than trusted. `generate_canonical` is compared as bit patterns, since a difference in the last place changes which category a sample lands in. Not yet wired into the EmptyDrops path. `solo::count` samples with a `SplitMix64` stream under a comment calling it "WeightedIndex-equivalent; empirically byte-identical EmptyDrops cell calls" — a claim that cannot hold in general, since two unrelated generators cannot agree on an arbitrary number of draws. It is true of whatever was checked and unknown elsewhere. Replacing it moves cell calls, so it belongs in its own change with the solo differential run against it. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

Two approximations in the CellRanger cell-calling path are replaced by what CellRanger and STAR actually compute. Both move cell calls, which is the point: the previous numbers were plausible rather than right. The ambient profile is now smoothed with Simple Good-Turing (Gadsby & Sampson, via Elworthy's implementation, which is what STAR vendors). The ambient counts come from a small sample of empty droplets, so a gene seen twice there is not twice as likely as one seen once, and a gene seen zero times is not impossible — it is one the sample was too small to show. SGT fits the frequency spectrum and reserves mass for the unseen from the singleton rate, then smooths the rest along a log-log line. What was here before had the right shape and the wrong numbers: it reserved mass the same way but distributed the remainder in proportion to raw counts, with no smoothing at all. The Monte-Carlo null is now drawn with libc++'s `std::mt19937` and `std::discrete_distribution`, seeded `19760110 * (isim + 1)` per simulation, as STAR seeds it. The previous sampler was a SplitMix64 stream under a comment calling it "WeightedIndex-equivalent; empirically byte-identical EmptyDrops cell calls" — a claim that cannot hold in general, since two unrelated generators cannot agree over an arbitrary number of draws. The libc++ types were ported and checked against real libc++ in the previous commit on this branch; this wires them in. One generator per simulation, no shared state, so the walks still run in any order on any number of threads and give the same p-values. D17 comes with it: STAR leaves `PZero` uninitialised when the spectrum has fewer than five distinct frequencies and `analyse()` bails, so it reads whatever the stack held. Here it is zero from construction, which is what "no basis for reserving unseen mass" means. Recorded in docs-old/dev/divergences.md.

Section 1.2, in the What STAR does / What rustar-aligner does / Why / Impact / Source format CONTRIBUTING.md asks for, replacing the docs-old file the earlier version of this work carried.

* fix(solo): MultiGeneUMI_CR gives a tied UMI to nobody, not to everybody `--soloUMIfiltering MultiGeneUMI_CR` kept every gene tied at the highest read count. CellRanger's rule is the opposite on exactly that case: the gene with the *strictly* highest count takes the UMI, and a tie means no gene counts it. STAR walks the genes keeping a running maximum and clears its winner whenever it meets an equal count (`SoloFeature_collapseUMIall.cpp:212-224`): if (ig.second>maxu) { maxu=ig.second; maxg=ig.first; } else if (ig.second==maxu) { maxg=-1; }; ... if ( maxg+1==0 ) continue; // not counted for any gene One read per gene is the ordinary shape of a multi-gene UMI, and it is always a tie, so the old rule made the flag inert in practice rather than merely inaccurate. Measured on a 20 000-read 10x fixture (200 cells from the real v3 whitelist, 400 genes, 720 UMIs deliberately shared between two genes), against STAR 2.7.11b with the same flags: identical entries STAR counts rustar counts before 13 749 / 14 806 15 423 16 465 after 13 902 / 13 967 15 423 15 414 The flag removed nothing at all before; STAR removes 1 030 counts. The gap goes from +1 042 to -9. The outcome does not depend on the order the genes are visited — a strict maximum always ends as the winner, a tie always ends with none — so iterating a `HashMap` here stays deterministic. `multi_gene_umi_cr_drops_a_tie_entirely` pins the case the old tests missed: they only covered 3 reads against 1, where both rules agree. Not yet implemented, and stated so rather than left to be discovered: STAR applies a second condition, that the winning gene must also hold the top count among *uncorrected* UMIs (`umiGeneMapCount0`, same file, lines 226-232). That needs the pre-correction counts, which this code does not keep. The 65 entries still differing out of 13 967 are the place to look for its effect. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> * docs(changelog): record the MultiGeneUMI_CR tie fix Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> * fix(solo): MultiGeneUMI_CR decides ownership on corrected UMIs STAR corrects UMIs within each gene *before* deciding which gene owns a UMI, and applies two conditions, not one (`SoloFeature_collapseUMIall.cpp:134-148` and `:203-235`): 1. one gene must hold a strictly higher read count than every other, on the **corrected** UMI map — that is #173, already landed; 2. and that winner must not be beaten in the **uncorrected** map at the same key. The second condition exists because correction moves reads between UMIs: a gene can win only because correction folded a neighbouring UMI onto it, and STAR rejects that win rather than counting it. Reproducing it needs the order STAR uses. The generic path here filters multi-gene UMIs first and corrects afterwards, which cannot express either condition: by the time correction happens the ownership decision is already made. `MultiGeneUMI_CR` therefore takes its own path, which is also what STAR does — the flag is only valid with `--soloUMIdedup 1MM_CR`, so there is no combination this bypasses. `cellranger_1mm_map` exposes the correction mapping that `cellranger_1mm` already computed and threw away. Measured against **CellRanger 10.0.0** on the 20 000-read fixture from #172, with #165 and #173 also applied: identical entries CellRanger rustar #165 + #173 13 651 / 13 709 15 111 15 091 plus this change 13 676 / 13 709 15 111 15 116 Entries CellRanger has and we do not go from 29 to 7, and the count gap from -20 to +5, which is 0.03%. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> * docs(divergence): drop a reference to a test that no longer exists * feat(solo): bit-exact libc++ mt19937, generate_canonical and discrete_distribution STARsolo's `EmptyDrops_CR` rescue draws from `std::mt19937`, converts to doubles with `std::generate_canonical<double, 53>`, and picks categories with `std::discrete_distribution`. Two of those three are implementation-defined in the parts that matter: the standard fixes mt19937's output but not how `generate_canonical` consumes it, and says nothing about how `discrete_distribution` maps a uniform onto categories. So porting "the algorithm" is not enough — it has to be libc++'s algorithm, because that is what STAR is built against and where its numbers come from. libc++ accumulates two 32-bit draws in *ascending* significance and divides by 2^64; a most-significant-first accumulation, or one draw scaled to 53 bits, both give perfectly good uniforms and neither reproduces STAR. Every expected value in the tests came out of a C++ program compiled against the real libc++ and run, not from reading its source. `tests/libcxx_oracle.cpp` is that program, kept so the values can be regenerated rather than trusted. `generate_canonical` is compared as bit patterns, since a difference in the last place changes which category a sample lands in. Not yet wired into the EmptyDrops path. `solo::count` samples with a `SplitMix64` stream under a comment calling it "WeightedIndex-equivalent; empirically byte-identical EmptyDrops cell calls" — a claim that cannot hold in general, since two unrelated generators cannot agree on an arbitrary number of draws. It is true of whatever was checked and unknown elsewhere. Replacing it moves cell calls, so it belongs in its own change with the solo differential run against it. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> * feat(solo): EmptyDrops_CR uses Simple Good-Turing and libc++'s sampler Two approximations in the CellRanger cell-calling path are replaced by what CellRanger and STAR actually compute. Both move cell calls, which is the point: the previous numbers were plausible rather than right. The ambient profile is now smoothed with Simple Good-Turing (Gadsby & Sampson, via Elworthy's implementation, which is what STAR vendors). The ambient counts come from a small sample of empty droplets, so a gene seen twice there is not twice as likely as one seen once, and a gene seen zero times is not impossible — it is one the sample was too small to show. SGT fits the frequency spectrum and reserves mass for the unseen from the singleton rate, then smooths the rest along a log-log line. What was here before had the right shape and the wrong numbers: it reserved mass the same way but distributed the remainder in proportion to raw counts, with no smoothing at all. The Monte-Carlo null is now drawn with libc++'s `std::mt19937` and `std::discrete_distribution`, seeded `19760110 * (isim + 1)` per simulation, as STAR seeds it. The previous sampler was a SplitMix64 stream under a comment calling it "WeightedIndex-equivalent; empirically byte-identical EmptyDrops cell calls" — a claim that cannot hold in general, since two unrelated generators cannot agree over an arbitrary number of draws. The libc++ types were ported and checked against real libc++ in the previous commit on this branch; this wires them in. One generator per simulation, no shared state, so the walks still run in any order on any number of threads and give the same p-values. D17 comes with it: STAR leaves `PZero` uninitialised when the spectrum has fewer than five distinct frequencies and `analyse()` bails, so it reads whatever the stack held. Here it is zero from construction, which is what "no basis for reserving unseen mass" means. Recorded in docs-old/dev/divergences.md. * docs: record the EmptyDrops SGT divergence in DIVERGENCE.md Section 1.2, in the What STAR does / What rustar-aligner does / Why / Impact / Source format CONTRIBUTING.md asks for, replacing the docs-old file the earlier version of this work carried. * docs(divergence): file the EmptyDrops entry under section 1, note the second RNG * fix(params): refuse MultiGeneUMI_CR without --soloUMIdedup 1MM_CR * feat(solo): --soloFeatures Transcript3p, with --soloClusterCBfile Quantifies transcripts rather than genes, from where each read's 3' end sits relative to each transcript's. In a 3'-biased assay that distance is what separates isoforms: a read 200 bases from the end of one and 4000 from the end of another is evidence for the first. The distribution of those distances is estimated from the run's own histogram, smoothed and cut where the 3' peak decays into the body, and used as the likelihood in an EM over UMIs. Concordance needed no new code. `align_to_transcripts` already refuses to project an alignment that leaves the transcript, touches an intron, or crosses a junction the transcript does not have — which is exactly STAR's `Concordant` (`Transcriptome_classifyAlign.cpp`). A projection that survives is concordant; one that does not, is not. The projection also puts the 5' end at coordinate zero for both strands, so the distance to the 3' end is one expression rather than two. Two behaviours worth stating because they are not the obvious ones: Output is per cluster, not per cell, and `--soloClusterCBfile` is required. A single cell does not have enough UMIs to resolve isoforms, so the EM would be fitting noise. Asking for the feature without a clustering is refused rather than run. A UMI seen on several reads contributes the *intersection* of their transcript sets. Those reads came from one molecule, so a transcript missing from any of them cannot be its source. Taking the union would let a single stray read resurrect an isoform every other read excluded. Two of STAR's quirks are reproduced rather than corrected, because the cut point and every weight depend on them: the running-average divisor is `min(2N+1, i + N)` rather than the number of elements actually summed, and the transcript length factor is taken from the cumulative distribution at `trLen - 1` (`SoloFeature_quantTranscript.cpp`). Numbers are formatted the way C++'s default stream prints them — six significant digits, fixed inside `[1e-4, 1e6)` and scientific outside — since the normalised distribution runs down to ~1e-4 where Rust's `{}` and C++'s default disagree on both notation and digit count. * refactor(solo): drop Transcript3pAcc::merge, which nothing calls Records are accumulated under a mutex, so there are no partials to merge. It was dead from the moment it was written; CONTRIBUTING.md rules out shipping it. * docs(solo): note that STAR marks Transcript3p under development parametersDefault puts both Transcript3p and --soloClusterCBfile between "#####UnderDevelopment_begin : not supported - do not use" and "#####UnderDevelopment_end", and STAR --help prints that banner around them. The module said none of this. It matters for how the port is read: it follows STAR's code, so it inherits the unfinished parts of that code, and a differential against STAR compares two implementations of something STAR does not support. A reviewer should be told that before deciding to take it. * fix(solo): implement MultiGeneUMI_All instead of aliasing it to MultiGeneUMI `--soloUMIfiltering MultiGeneUMI_All` resolved to the same variant as `MultiGeneUMI`, which is neither what STAR does nor what the option is documented to do. Of the three available behaviours it was the only one nobody had asked for. In STAR the option is a no-op: it is parsed and stored, but its consumption site tests only the `MultiGeneUMI` flag, so selecting it leaves the filter entirely off. Documented, it removes a UMI seen in more than one gene from *all* of them, rather than from the losers only. `UmiFiltering::MultiGeneUmiAll` now exists and does the documented thing: a UMI appearing in several genes is evidence of a collision or of chimeric amplification, so it is discarded outright rather than attributed to whichever gene happened to read deepest. Single-gene UMIs are untouched, which the test checks across every mode. Raised upstream as #144 before changing it, since "be faithful to STAR" and "do what the flag says" genuinely point in opposite directions here. Also adds `docs-old/dev/divergences.md`, recording this and the homopolymer-UMI rule, so deliberate differences are written down rather than rediscovered as surprises in a differential run. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> * docs(changelog): record the MultiGeneUMI_All fix Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> * docs(divergence): correct the MultiGeneUMI_All entry, defer the homopolymer one --------- Co-authored-by: Benjamin Demaille <benjamin.demaille@icloud.com> Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>

Psy-Fer · 2026-08-06T11:12:05Z

Closed by #212

BenjaminDEMAILLE and others added 3 commits July 29, 2026 10:20

docs: record the EmptyDrops SGT divergence in DIVERGENCE.md

9bede61

Section 1.2, in the What STAR does / What rustar-aligner does / Why / Impact / Source format CONTRIBUTING.md asks for, replacing the docs-old file the earlier version of this work carried.

This was referenced Jul 29, 2026

solo: --soloUMIfiltering MultiGeneUMI_All (closes #144) #152

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CellRanger GEX pipeline: coverage map, stage by stage #181

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PR review queue: what is ready, what is stacked, what is waiting on a decision #195

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Psy-Fer mentioned this pull request Aug 6, 2026

Batch PRs #173, #175, #156, #158, #152 #212

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solo: EmptyDrops_CR on CellRanger's actual statistics (SGT ambient profile, libc++ sampler) - #156

solo: EmptyDrops_CR on CellRanger's actual statistics (SGT ambient profile, libc++ sampler)#156
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