Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data — TEI-tagged view

Nicole M. Davis, Diana M. Proctor, Susan Holmes, David A. Relman, Benjamin J. Callahan · 2018 · biology · doi:10.1186/s40168-018-0605-2 · TEI xml · tagged edition · index · concepts · authors
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contaminants External contamination cross-contamination score statistic p value98 classification threshold negative controls2 gel-based quality control relative abundance thresholds true community members low-biomass SILVA2 HOMD processing batches placenta microbiome system-or-tool-building173
Method, as described: a two-component mixture model of contaminant and sample DNA, turned into two score statistics and a user-set classification threshold, validated on an oral dataset, a dilution series and two published low-biomass studies

Our tag layer for this paper

Cross-disciplinary analysis
content-tags & facets: phenomenon · claim-type · cross-domain-transfer · mechanism · claim-relation · replication-status · limitation — grounded in the full text
phenomenoncontamination that survives good laboratory practice and is invisible to the quality control usually used to detect it, biasing hardest exactly where biomass is lowest and the claims are most contested— “Contamination is often assumed to be absent if control samples do not yield a band on an agarose gel. However, band-less samples can generate non-negligible numbers of sequencing reads, suggesting that gel-based quality control is insufficient.”
claim-typemethod— “Decontam implements two simple de novo classification methods based on widely reproduced signatures of external contamination: (1) Sequences from contaminating taxa are likely to have frequencies that inversely correlate with sample DNA concentration and (2) sequences from contaminating taxa are likely to have higher prevalence in control…
method — evidence— “Let total sample DNA (T) be a mixture of two components (T = C + S): contaminating DNA (C) present in uniform concentration across samples and true sample DNA (S) present in varying concentration across samples.”
object of study — evidence— “However, the accuracy of marker-gene and metagenomic sequencing (MGS) is limited in practice by several processes that introduce contaminants—DNA sequences not truly present in the sampled community.”
research question — evidence— “Decontam implements two simple de novo classification methods based on widely reproduced signatures of external contamination: (1) Sequences from contaminating taxa are likely to have frequencies that inversely correlate with sample DNA concentration and (2) sequences from contaminating taxa are likely to have higher prevalence in control…
contribution — evidence— “Decontam implements two simple de novo classification methods based on widely reproduced signatures of external contamination: (1) Sequences from contaminating taxa are likely to have frequencies that inversely correlate with sample DNA concentration and (2) sequences from contaminating taxa are likely to have higher prevalence in control…
transferfrom statistics: model comparison by ratio of sums-of-squared-residuals, carried from linear regression into a per-sequence classifier - and deliberately stripped of the inferential guarantee it carries in its home field— “The frequency-based score statistic is best thought of as a transformation that takes as input two values—the ratio of the sum-of-squared residuals, and the number of observations—and outputs a score that is a better classification statistic than the ratio of the sum-of-squared residuals alone.”transfers[0]
transferfrom statistics: a two-component mixture model, carried from statistical modelling to represent total DNA as contaminant plus sample— “Let total sample DNA (T) be a mixture of two components (T = C + S): contaminating DNA (C) present in uniform concentration across samples and true sample DNA (S) present in varying concentration across samples.”transfers[1]
mechanisminverse frequency signature contaminant DNA enters at roughly constant absolute concentration while sample DNA varies, so as a proportion of the total the contaminant's frequency falls as sample concentration rises - a slope of -1 in log space against a slope of 0— “Let total sample DNA (T) be a mixture of two components (T = C + S): contaminating DNA (C) present in uniform concentration across samples and true sample DNA (S) present in varying concentration across samples.”mechanisms[0]
mechanismprevalence signature in negative controls with no competing sample DNA, a negative control's sequencing capacity is available to whatever contaminant is present, so contaminants are detected in a larger fraction of controls than of true samples— “Decontam implements two simple de novo classification methods based on widely reproduced signatures of external contamination: (1) Sequences from contaminating taxa are likely to have frequencies that inversely correlate with sample DNA concentration and (2) sequences from contaminating taxa are likely to have higher prevalence in control…mechanisms[1]
mechanismbiomass-correlated confounding because the frequency method reads low sample concentration as evidence of contamination, any real sequence that is genuinely commoner in low-biomass samples presents with the contaminant signature - so mixing environments manufactures false positives out of true biology— “The assumptions of decontam, especially the frequency method, can be violated if bacterial biomass systematically differs between groups of samples. For example, if decontam were applied to a mixed set of stool (high biomass) and airway (low biomass) samples, real sequences in the airway samples could be classified as contaminants, because…mechanisms[2]
critiques gel-band quality control as evidence that a sequencing run is free of contamination— “Contamination is often assumed to be absent if control samples do not yield a band on an agarose gel. However, band-less samples can generate non-negligible numbers of sequencing reads, suggesting that gel-based quality control is insufficient.”claim_relations[0]
critiques ad hoc in silico decontamination - abundance thresholds, negative-control subtraction and contaminant blacklists— “However, relative abundance thresholds remove rare features truly present in the sample and do not remove abundant contaminants that are the most likely to interfere with subsequent analysis.”claim_relations[1]
builds-on prior reports of the two contaminant signatures: inverse correlation with DNA concentration, and presence in negative controls— “Decontam implements two simple de novo classification methods based on widely reproduced signatures of external contamination: (1) Sequences from contaminating taxa are likely to have frequencies that inversely correlate with sample DNA concentration and (2) sequences from contaminating taxa are likely to have higher prevalence in control…claim_relations[2]
confirms the conclusion that marker-gene data from placenta biopsies do not support an indigenous placenta microbiome— “The application of decontam to 16S rRNA gene sequencing data generated from placenta biopsies corroborated the conclusion that the data did not support the existence of a placenta microbiome.”claim_relations[3]
sensescore statistic P - AS COMPUTED: set equal to a p-value from the chi-square or Fisher's exact test, and so arithmetically indistinguishable from one— “Although the prevalence-based score statistic is set equal to a p-value from the chi-square or Fisher’s exact tests, it is used by decontam only as a score that effectively distinguishes between the contaminant and non-contaminant mixture components.”senses[0]
sensescore statistic P - AS LICENSED: a classification score only, explicitly carrying no guarantee on the type 1 error rate. The paper states the difference rather than leaving it to the reader— “Although inspired by the general linear F test, the frequency-based score statistic is not a p value, i.e., it is not associated with any guarantees on the type 1 error rate.”senses[1]
senseaccuracy of decontam - PER SEQUENCE FEATURE: specificity and sensitivity described as sometimes moderate— “The sensitivity of contaminant identification increased substantially with feature prevalence. As a result, while the specificity and sensitivity of decontam on a per-feature basis were sometimes…senses[2]
senseaccuracy of decontam - PER READ: described as reaching exceptional levels, on the same classifications of the same data. The unit of account decides which number is reportedsenses[3]
controlthe field's standard check that a negative control shows no band on an agarose gel, taken as evidence that contamination is absent — absent-stated-about-other
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— rules out contamination in the sequencing library - and the paper's own sentence says this check does NOT eliminate it, because band-less samples still generate non-negligible reads
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controls[0]
controlremoving every sequence that appears in a negative control — absent-stated-about-other
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— rules out contaminant sequences - and it OVER-removes, because cross-contamination puts abundant TRUE sequences into the negative controls
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controls[1]
controldiscarding sequences below an ad hoc relative abundance threshold — absent-stated-about-other
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— rules out abundant contaminants, which it fails to remove, while removing rare features that are truly present in the sample
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controls[2]
controlexcluding taxa on a blacklist of previously reported contaminants — absent-stated-about-other
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— rules out previously reported contaminants - leaving study-specific contaminants in place and removing true sequences
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controls[3]
controlcross-checking taxonomic assignments against a second controlled vocabulary, HOMD against SILVA, at the genus level — partial
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— rules out a contaminant call that is an artefact of one reference vocabulary's genus boundaries
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controls[4]
controlan explicit 'ambiguous' class for genera that neither reference database resolves, instead of forcing every genus into contaminant or oral — held
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— rules out a genus with no evidence either way being forced into 'contaminant' or 'oral' and counted as if it had been decided
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controls[5]
controlturning the method on a published low-biomass claim - the placenta microbiome - where the expected answer was already contested — held
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— rules out a decontamination method validated only on data where the right answer was chosen by the people validating it
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controls[6]
weightgel-band quality control as evidence that a sequencing run is free of contamination — 0.9
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claim_relations[0]
weightad hoc in silico decontamination - abundance thresholds, negative-control subtraction and contaminant blacklists — 0.9
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claim_relations[1]
weightprior reports of the two contaminant signatures: inverse correlation with DNA concentration, and presence in negative controls — 0.9
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claim_relations[2]
weightthe conclusion that marker-gene data from placenta biopsies do not support an indigenous placenta microbiome — 0.85
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claim_relations[3]
differs in (stated by the tagger, no quotation)score statistic —distinct-from→ p value — whether it licenses a claim about the type 1 error rateconcept_edges[0]
relationscore statistic —distinct-from→ p value — computed the same way and carrying none of the same guarantees
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concept_edges[0]
weightscore statistic —distinct-from→ p value — 0.95
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concept_edges[0]
differs in (stated by the tagger, no quotation)contaminants —distinct-from→ true community members — whether the sequence originated in the sampled environmentconcept_edges[1]
relationcontaminants —distinct-from→ true community members — assumed to be disjoint populations - the assumption the whole method rests on
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concept_edges[1]
weightcontaminants —distinct-from→ true community members — 0.9
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concept_edges[1]
differs in (stated by the tagger, no quotation)cross-contamination —distinct-from→ External contamination — whether the contaminating DNA came from outside the study or from another sample in itconcept_edges[2]
relationcross-contamination —distinct-from→ External contamination — different sources, and different statistical signatures in the data
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concept_edges[2]
weightcross-contamination —distinct-from→ External contamination — 0.9
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concept_edges[2]
outcomecontrol — absent-stated-about-other
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controls[0]
outcomecontrol — absent-stated-about-other
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controls[1]
outcomecontrol — absent-stated-about-other
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controls[2]
outcomecontrol — absent-stated-about-other
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controls[3]
outcomecontrol — partial
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controls[4]
outcomecontrol — held
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controls[5]
outcomecontrol — held
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controls[6]
limitationdecontam is not designed for cross-contamination, which violates its founding assumption that contaminants and true members are distinct populations
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limitations[0]
limitationthe frequency method's approximations break down in exactly the low-biomass regime where contamination matters most - when contaminants are a large fraction of reads
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limitations[1]
limitationapplying it across environments of systematically different biomass can classify real sequences as contaminants, because low concentration is the contaminant signature
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limitations[2]
limitationit depends on patterns across samples, so it has low sensitivity for contaminants present in very few samples - the tail it cannot see
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limitations[3]
limitationthe default classification threshold is not recommended as-is: the authors direct users to read a threshold off their own score histogram instead
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limitations[4]
limitationthe method is less effective when groups of samples carry systematically different contaminant patterns, which is why batches must be declared by the user rather than detected
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limitations[5]
Content tags
content-observations: finding · quantity · variable · definition · key-term — grounded in the full text
finding
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content_tags.findings[0]
finding
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content_tags.findings[1]
finding
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content_tags.findings[2]
finding
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content_tags.findings[3]
finding
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content_tags.findings[4]
quantitythe default classification threshold, which the authors recommend against using unexamined
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content_tags.quantities[0]
quantitythe threshold at which classification reduces to 'is the contaminant model the better fit'
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content_tags.quantities[1]
quantitysequences on which the two reference databases disagreed, resolved by BLAST
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content_tags.quantities[2]
variablesample DNA concentration
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content_tags.variables[0]
variableprevalence
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content_tags.variables[1]
definitioncontaminants
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content_tags.definitions[0]
definitionExternal contamination
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content_tags.definitions[1]
definitionscore statistic
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content_tags.definitions[2]
Concepts
terms this paper carries, each with the sentence it was cut from — the layer that joins one paper to another. Terms with no quote yet are on CONCEPTS.html.
conceptcontaminants — not defined in this paper's own words; DNA sequences not truly present in the sampled community - defined by provenance rather than by anything observable in the sequence itself
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concepts[0]
conceptExternal contamination — not defined in this paper's own words; contributed from outside the samples being measured - reagents, instruments, surfaces, bodies. The type decontam is built for
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concepts[1]
conceptcross-contamination — not defined in this paper's own words; samples mixing with each other during processing or sequencing - the type decontam explicitly does not address, because its statistical signature is different
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concepts[2]
conceptscore statistic — not defined in this paper's own words; a number computed as a tail probability and licensed only as a classification score - the paper's own distinction, stated twice
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concepts[3]
conceptp value — not defined in this paper's own words; the reading the score statistic invites and the paper refuses: it carries no type 1 error guarantee
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concepts[4]
conceptclassification threshold — not defined in this paper's own words; P*, compared against the score to classify; default 0.1, and the authors tell users not to trust the default without inspecting their own score distribution
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concepts[5]
conceptnegative controls — not defined in this paper's own words; reagent-only or blank samples processed alongside real ones - the input to the prevalence method, and the thing whose gel band was wrongly treated as the test
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concepts[6]
conceptgel-based quality control — not defined in this paper's own words; checking whether a control sample yields a band on an agarose gel - argued here to be insufficient, because band-less samples still generate reads
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concepts[7]
conceptrelative abundance thresholds — not defined in this paper's own words; the commonest in silico decontamination practice, which removes rare true sequences and keeps abundant contaminants - wrong at both ends
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concepts[8]
concepttrue community members — not defined in this paper's own words; the sequences actually present in the sampled environment, assumed distinct from contaminants - an assumption cross-contamination violates
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concepts[9]
conceptlow-biomass — not defined in this paper's own words; the regime where contaminant DNA approaches or exceeds sample DNA, breaking the frequency method's approximations and producing the field's most contested claims
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concepts[10]
conceptSILVA — not defined in this paper's own words; one of two taxonomic references used to name the sequences, and one half of a disagreement resolved by a third method
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concepts[11]
conceptHOMD — not defined in this paper's own words; the Human Oral Microbiome Database, the other half of that disagreement
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concepts[12]
conceptprocessing batches — not defined in this paper's own words; user-declared groups scored independently, because separately processed samples can carry different contaminants
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concepts[13]
conceptplacenta microbiome — not defined in this paper's own words; a contested claim the method was turned on: applying decontam corroborated that the data do not support it
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concepts[14]
Statistics — cross-field join keys
field-invariant statistical terms, used in their statistical sense (gated on a number / symbol / test). A p-value or a standard deviation means the SAME thing in physics, biology, psychology and sociology — so these are the strongest cross-field join keys. Grounded verbatim.
general linear F test
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content_tags.statistics[0]
type 1 error rate
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content_tags.statistics[1]
chi-square
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content_tags.statistics[2]
Fisher’s exact tests
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content_tags.statistics[3]
specificity
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content_tags.statistics[4]
sensitivity
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.statistics[5]

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.

Tag layer © the Meta-Tagging Project, CC BY 4.0. The paper text is © its authors/publisher and is linked, not reproduced. Excerpts shown are short quotations for identification and verification. · back to index · concepts · authors · עברית
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