Evidence map›Paper›PMID 15199524›Full record

ArticleAmerican journal of human genetics2004

Authenticity of ancient-DNA results: a statistical approach.

Matthew Spencer, Christopher J Howe

Abstract read
In one paragraph

Article in American journal of human genetics, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Temporal genetic variation of the red fox,Quaternary science reviews · 2012
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Palaeomicrobiology: current issues and perspectives.Nature reviews. Microbiology · 2005
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Matthew SpencerDepartment of Biochemistry, University of Cambridge, Cambridge, United Kingdom. matts@mathstat.dal.ca
Christopher J Howe

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although there have been several papers recommending appropriate experimental designs for ancient-DNA studies, there have been few attempts at statistical analysis. We assume that we cannot decide whether a result is authentic simply by examining the sequence (e.g., when working with humans and domestic animals). We use a maximum-likelihood approach to estimate the probability that a positive result from a sample is (either partly or entirely) an amplification of DNA that was present in the sample before the experiment began. Our method is useful in two situations. First, we can decide in advance how many samples will be needed to achieve a given level of confidence. For example, to be almost certain (95% confidence interval 0.96-1.00, maximum-likelihood estimate 1.00) that a positive result comes, at least in part, from DNA present before the experiment began, we need to analyze at least five samples and controls, even if all samples and no negative controls yield positive results. Second, we can decide how much confidence to place in results that have been obtained already, whether or not there are positive results from some controls. For example, the risk that at least one negative control yields a positive result increases with the size of the experiment, but the effects of occasional contamination are less severe in large experiments.

Indexed as

Data Interpretation, StatisticalSequence Analysis, DNAHumansLikelihood FunctionsTime Factors

Identifiers

PMID15199524
PMCPMC1216058

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.