standOff, and the article is at its publisher via the link below. When we have changed our mind. Some entries in the table begin with a word in capitals and the reason for it. EVIDENCE CORRECTED — the finding still stands, but we had quoted the wrong sentence from the paper, and the quotation has been replaced with the right one. RETRACTED — the entry itself was wrong; it stays on the page, marked, with the reason, rather than being deleted. WITHDRAWN AND REPLACED — the entry was wrong, and a corrected version of it appears in the entries below. Each mark carries its own reason, in brackets, because the reasons differ from one entry to the next. An entry we have WITHDRAWN is removed from this page and kept in the record, with its reason. A line reading Audit and a date is a later re-reading of the entry against its whole sentence: DOUBTFUL means it was kept, and the reason says what is loose about it. Quotation marks inside the tagger's sentence. Where a tag is the tagger's own sentence, a phrase in quotation marks inside it is borrowed from the paper — the tagger's wording around it is not. The paper's own sentence is the evidence quote for that row; on this page it is withheld with the article, and the article is at its publisher. Nothing inside quotation marks anywhere on this page is ours: if it is quoted, it is the paper's. Whose words a concept carries. A concept entry records a term the paper itself uses, so the term, the sense given for it, and its evidence are the paper's own words, quoted where the paper fixes them. This is the opposite of a sense entry in the tag table, which is the tagger's sentence about how the paper uses a term. Where a concept entry could not be grounded in the paper's words, the entry says so on its own row.| relation to other work | claim_relations | how this paper stands to another: agrees, contradicts, extends, qualifies |
| claim type | claim_type | the shape of the claim: existence, mechanism, method, critique, prediction, null |
| concept edge | concept_edges | an asserted relation between two concepts, with the sentence asserting it |
| concept | concepts | an idea the paper works with, quoted where the paper uses it |
| content tag | content_tags | a finding, definition, quantity, statistic or variable named in the paper |
| contribution | contribution | what the paper claims to add |
| control | controls | an experiment run to eliminate a rival explanation |
| limitation | limitations | what the paper says its evidence cannot support |
| mechanism | mechanisms | how the reported effect is said to come about |
| method | method | how the paper produced its evidence |
| object of study | object_of_study | what the paper is about — the thing it investigates |
| phenomenon | phenomenon | the effect or regularity under study |
| research question | research_question | the question the paper sets itself |
| sense | senses | a distinct use of a term, quoted where the paper fixes it |
| transfer | transfers | a method or concept carried in from another field |
Relations on this page carry a quotation for the claim. Where a relation was separately evidenced — and so tested against the vocabulary for its type — the row says so; 2 of 2 relations here carry that mark. The rest are the tagger’s reading of the sentence quoted beside them.
| facet | tag | field | conf. | whose words |
|---|---|---|---|---|
| object_of_study | normalisation of single-cell RNA-seq counts - how to remove the effect of sequencing depth without removing the biology along with it Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | object_of_study | the paper's words | |
| research_question | whether any single per-cell scaling factor can normalise genes of different abundance, and if not, what error model should replace it Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | research_question | the paper's words | |
| contribution | regularized negative binomial regression - fit a GLM per gene with depth as covariate, pool parameters across genes of similar abundance, and take the Pearson residuals as normalised values Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | contribution | the paper's words | |
| claim_type | method Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | claim_type | the paper's words | |
| phenomenon | a preprocessing choice that decides what counts as biological signal - the same data yielding heterogeneity or not depending on how the error model is constrained Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | phenomenon | the paper's words | |
| method | system-or-tool-building Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: system-or-tool-building | method | the paper's words | |
| mechanisms | counts of low- and high-abundance genes respond differently to sequencing depth, so one factor per cell cannot correct both; dividing by depth leaves the high-abundance tiers still confounded and the variance contribution of the other tiers dampened Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | mechanisms[0] | 0.95 | the tagger's words |
| mechanisms | an unconstrained per-gene model has enough freedom to explain real cell-type differences as technical effects of depth, so the residuals it produces have had the biology subtracted along with the noise - even cell-type markers come out with low residual variance Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | mechanisms[1] | 0.95 | the tagger's words |
| mechanisms | estimating each gene's parameters independently makes them a function of that gene's sampling noise; smoothing them against mean abundance replaces the noise with the population trend, and the estimates become reproducible across bootstraps Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: pooling across genes as a constraint | mechanisms[2] | 0.95 | the tagger's words |
| mechanisms | megakaryocytes carry little RNA, so they appear at low sequencing depth for reasons of biology rather than sampling; an unconstrained fit reads that as a negative slope between depth and the marker's count, which cannot be true of any single cell type Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | mechanisms[3] | 0.95 | the tagger's words |
| limitations | the regularisation assumes the majority of genes do not vary biologically, which the authors say may be overly simplistic on a highly heterogeneous sample Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | limitations[0] | 0.95 | the tagger's words |
| limitations | the kernel bandwidth is a user-adjustable parameter; robust over an order of magnitude and producing over- or under-smoothing at the extremes Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | limitations[1] | 0.95 | the tagger's words |
| limitations | the batch extension requires all cell types to share a similar batch effect, which is an assumption about the experiment rather than a property of the model Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | limitations[2] | 0.95 | the tagger's words |
| limitations | Pearson residuals are an intermediate rather than a model - an alternative would fit the count distribution directly, as GLM-PCA does, instead of passing residuals to methods that assume normal errors Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | limitations[3] | 0.85 | the tagger's words |
| transfers | parameter regularisation by pooling across similar features, carried from bulk RNA-seq differential-expression error models into single-cell normalisation Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | transfers[0] | 0.95 | the tagger's words |
| transfers | generalized linear models and Pearson residuals, carried from regression theory to serve as the normalised data values themselves rather than as a diagnostic Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | transfers[1] | 0.95 | the tagger's words |
| controls | a dataset with NO biological variation by construction - droplets that are technical replicates of one bulk RNA sample - run through the unregularised model to see whether the parameter heterogeneity persists when biology cannot explain it Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. eliminates: true biological variation as the explanation of the parameter heterogeneity across genes - in a sample where every droplet is a technical replicate of one bulk RNA extract there is no biology left that could produce it · outcome: failed | controls[0] | 0.95 | the tagger's words |
| controls | the same control dataset run through the FINISHED method, where a correct model must find no high-variance genes at all Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. eliminates: residual technical variation as the source of the high-variance genes the finished method selects - run on a sample containing no biology, a correct model must find none, and does · outcome: held | controls[1] | 0.95 | the tagger's words |
| controls | bootstrapping the fit over randomised subsets of cells, to separate real between-gene differences from sampling variation in the estimates Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. eliminates: real between-gene differences as the explanation of the parameter spread - estimates that move when the cells are resampled are measuring the sample and not the gene · outcome: failed | controls[2] | 0.95 | the tagger's words |
| controls | substituting a Poisson and an unconstrained NB error model into the same pipeline, so the regularisation step is tested rather than assumed Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. eliminates: the generalised linear model framework itself as the source of the result - swapping only the error model shows the work is done by the regularisation, not by using a GLM · outcome: held | controls[3] | 0.95 | the tagger's words |
| controls | checking what the high-residual-variance genes actually are, rather than reporting that some exist Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. eliminates: residual technical noise as the explanation of the surviving high-variance genes - noise does not produce a list that is exclusively markers of known immune cell subsets · outcome: held | controls[4] | 0.95 | the tagger's words |
| controls | repeating the whole analysis on five UMI datasets from plate- and droplet-based protocols rather than on the one dataset the method was developed against Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. eliminates: the single development dataset, and the droplet protocol it came from, as the source of the result · outcome: held | controls[5] | 0.95 | the tagger's words |
| concepts | normalization Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: normalization | concepts[0] | 0.95 | the paper's words |
| concepts | size factor Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: size factor | concepts[1] | 0.95 | the paper's words |
| concepts | Pearson residuals Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: Pearson residuals | concepts[2] | 0.95 | the paper's words |
| concepts | overfitting Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: overfitting | concepts[3] | 0.95 | the paper's words |
| concepts | regularization Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: regularization | concepts[4] | 0.95 | the paper's words |
| concepts | Chromium control dataset Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: Chromium control dataset | concepts[5] | 0.95 | the paper's words |
| concepts | kernel bandwidth Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: kernel bandwidth | concepts[6] | 0.95 | the paper's words |
| concepts | zero-inflated negative binomial Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: zero-inflated negative binomial | concepts[7] | 0.95 | the paper's words |
| concepts | Poisson Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: Poisson | concepts[8] | 0.95 | the paper's words |
| concepts | sequencing depth Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: sequencing depth | concepts[9] | 0.95 | the paper's words |
| concepts | PPBP Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: PPBP | concepts[10] | 0.95 | the paper's words |
| concepts | regularized NB Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: regularized NB | concepts[11] | 0.95 | the paper's words |
| senses | parameter heterogeneity across genes - READING 1: true biological variation in the distribution of single-cell gene expression Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | senses[0] | 0.95 | the tagger's words |
| senses | parameter heterogeneity across genes - READING 2: irreproducible variation driven by overfitting. Resolved in favour of this one by a control dataset with no biological variation in it, where the heterogeneity persisted Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | senses[1] | 0.95 | the tagger's words |
| senses | "effectively normalized" - UNDER LOG-NORMALIZATION: true only of the bottom three abundance tiers; high-abundance genes remain confounded with sequencing depth Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | senses[2] | 0.95 | the tagger's words |
| senses | "effectively normalized" - UNDER PEARSON RESIDUALS: level and variance independent of sequencing depth across the full range of expression Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | senses[3] | 0.95 | the tagger's words |
| claim_relations | critiques → size-factor normalisation for single-cell data - including recent methods that compute the factor more cleverly, since the problem is the single factor and not its estimation Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | claim_relations[0] | 0.95 | the tagger's words |
| claim_relations | critiques → unconstrained negative binomial and zero-inflated negative binomial error models as used in current statistical and deep-learning methods for scRNA-seq Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | claim_relations[1] | 0.95 | the tagger's words |
| claim_relations | builds-on → regularisation of error-model parameters across genes of similar abundance, standard in bulk RNA-seq differential expression and not previously used for single-cell normalisation Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | claim_relations[2] | 0.95 | the tagger's words |
| claim_relations | qualifies → SCnorm's conclusion that gene groups need separate treatment - reached for non-UMI data by a method that ignores the zero values which dominate droplet-based assays Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | claim_relations[3] | 0.95 | the tagger's words |
| concept_edges | size factor —distinct-from→ normalization Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. differs in: whether one constant per cell can serve genes across the whole range of abundance · the relation itself is separately evidenced · strength of the relation: 0.95 · differs in (stated by the tagger, no quotation): whether one constant per cell can serve genes across the whole range of abundance · the relation stated: a single per-cell scaling factor introduces different effects on genes of different average abundance, so it is not normalization for all of them
Audit 2026-09-28: DOUBTFUL - read against its span and kept, but the span says a single size factor has distinct effects; distinct-from is loose. also in: size factor · normalization | concept_edges[0] | 0.95 | the tagger's words |
| concept_edges | Poisson —distinct-from→ regularized NB Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. differs in: whether the error model can represent overdispersion without absorbing the biology · the relation itself is separately evidenced · strength of the relation: 0.95 · differs in (stated by the tagger, no quotation): whether the error model can represent overdispersion without absorbing the biology · the relation stated: the single-parameter Poisson cannot represent overdispersion and leaves residual variance above one for highly expressed genes; the unconstrained NB overfits in the other direction and flattens the markers also in: Poisson · regularized NB | concept_edges[3] | 0.95 | the tagger's words |
| content_tags | a single per-cell scaling factor cannot normalise genes of different abundance, whatever method computes the factor Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[0] | 0.95 | the tagger's words |
| content_tags | log-normalisation effectively normalises only the bottom three abundance tiers; high-abundance genes stay confounded with depth Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[1] | 0.95 | the tagger's words |
| content_tags | an unconstrained negative binomial model overfits and removes biological variation along with technical variation Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[2] | 0.95 | the tagger's words |
| content_tags | the parameter heterogeneity persists in a dataset containing no biological variation, which is what identifies it as overfitting Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[3] | 0.95 | the tagger's words |
| content_tags | after normalisation the genes with high residual variance are exclusively markers of known immune cell subsets Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[4] | 0.95 | the tagger's words |
| content_tags | both non-regularised models fit a negative depth-count slope for a megakaryocyte marker, which cannot be true of a single cell type Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[5] | 0.95 | the tagger's words |
| content_tags | removing the influence of technical effects in the underlying molecular counts while preserving true biological variation Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: normalization | content_tags.definitions[0] | 0.95 | the tagger's words |
| content_tags | response residuals divided by the expected standard deviation, effectively a variance-stabilizing transformation putting lowly and highly expressed genes on a common scale Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: Pearson residuals | content_tags.definitions[1] | 0.95 | the tagger's words |
| content_tags | droplets each representing a technical replicate of a bulk RNA sample - no biological variation in it by construction Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: Chromium control dataset | content_tags.definitions[2] | 0.95 | the tagger's words |
| content_tags | the unit residual variance expected for a gene with no biological heterogeneity Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[0] | 0.85 | the tagger's words |
| content_tags | negative binomial Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: negative binomial | content_tags.statistics[0] | 0.95 | the tagger's words |
| content_tags | kernel bandwidth Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: kernel bandwidth | content_tags.statistics[1] | 0.95 | the tagger's words |
| content_tags | generalized linear model Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: generalized linear model | content_tags.statistics[2] | 0.85 | the tagger's words |
| content_tags | sequencing depth Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: sequencing depth | content_tags.variables[0] | 0.95 | the tagger's words |
Tags that could not be placed in the text:
What was deliberately not tagged, and why, is recorded per paper by the tagger. Where a paper has no such record, this page says so rather than implying that nothing was declined.