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

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

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>

…_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.

second RNG

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.

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.

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.

…GeneUMI

`--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>

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

homopolymer one