Evidence map›Paper›PMID 38017136›Full record

ReviewNature protocols2024

CONIPHER: a computational framework for scalable phylogenetic reconstruction with error correction.

Kristiana Grigoriadis, Ariana Huebner, Abigail Bunkum, Emma Colliver, Alexander M Frankell, Mark S Hill, Kerstin Thol, Nicolai J Birkbak, Charles Swanton, Simone Zaccaria and 1 more

Abstract readReview
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In one paragraph

Review in Nature protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

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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

11 authors.

Kristiana Grigoriadis *Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.ORCID 0000-0002-8435-0176
Ariana Huebner *Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.ORCID 0000-0001-8009-4999
Abigail Bunkum *Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.ORCID 0000-0002-7753-9421
Emma Colliver *Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.ORCID 0000-0002-1497-0740
Alexander M Frankell *Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.ORCID 0000-0002-0341-7878
Mark S HillCancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
Kerstin TholCancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.ORCID 0000-0002-4624-118X
Nicolai J BirkbakCancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.ORCID 0000-0003-1613-9587
Charles SwantonCancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK. charles.swanton@crick.ac.uk.ORCID 0000-0002-4299-3018
Simone ZaccariaCancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK. s.zaccaria@ucl.ac.uk.ORCID 0000-0002-5265-7392
Nicholas McGranahanCancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK. nicholas.mcgranahan.10@ucl.ac.uk.ORCID 0000-0001-9537-4045

Funding

Cancer Research UK 17786Cancer Research UK 19310Cancer Research UK 20265Cancer Research UK 20270Cancer Research UK 20466Cancer Research UK 22639Cancer Research UK 24956Cancer Research UK 25253Cancer Research UK 30025Medical Research Council G0701935Wellcome Trust CC2041
6 · The paper itself

Abstract

Intratumor heterogeneity provides the fuel for the evolution and selection of subclonal tumor cell populations. However, accurate inference of tumor subclonal architecture and reconstruction of tumor evolutionary histories from bulk DNA sequencing data remains challenging. Frequently, sequencing and alignment artifacts are not fully filtered out from cancer somatic mutations, and errors in the identification of copy number alterations or complex evolutionary events (e.g., mutation losses) affect the estimated cellular prevalence of mutations. Together, such errors propagate into the analysis of mutation clustering and phylogenetic reconstruction. In this Protocol, we present a new computational framework, CONIPHER (COrrecting Noise In PHylogenetic Evaluation and Reconstruction), that accurately infers subclonal structure and phylogenetic relationships from multisample tumor sequencing, accounting for both copy number alterations and mutation errors. CONIPHER has been used to reconstruct subclonal architecture and tumor phylogeny from multisample tumors with high-depth whole-exome sequencing from the TRACERx421 dataset, as well as matched primary-metastatic cases. CONIPHER outperforms similar methods on simulated datasets, and in particular scales to a large number of tumor samples and clones, while completing in under 1.5 h on average. CONIPHER enables automated phylogenetic analysis that can be effectively applied to large sequencing datasets generated with different technologies. CONIPHER can be run with a basic knowledge of bioinformatics and R and bash scripting languages.

Indexed as

AlgorithmsNeoplasmsComputational BiologyHumansMutationPhylogenySequence Analysis, DNA

Identifiers

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Registered trials

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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.