Evidence map›Paper›PMID 39745641›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Reconstructing Progenitor State Hierarchy and Dynamics Using Lineage Barcoding Data.

Weixiang Fang, Yi Yang, Hongkai Ji, Reza Kalhor

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Weixiang FangDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Yi YangDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Hongkai JiDepartment of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.
Reza KalhorDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA. kalhor@jhu.edu.

Funding

Dynamics of lineage-specific genome reorganization in gastrulation and their response to disease-associated epigenetic perturbationsU01HL156056 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI KALHOR, REZA · 2020 to 2024
$3.1M
Mapping the dynamics of mouse neurogenesis in autism models using high-resolution genomic barcoding technologiesR01HG012357 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI KALHOR, REZA · 2022 to 2025
$2.1M
Computational tools for regulome mapping using single-cell genomic dataR01HG010889 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI JI, HONGKAI · 2019 to 2022
$1.6M
NHGRI NIH HHS R01 HG010889NHGRI NIH HHS R01 HG012357NHLBI NIH HHS U01 HL156056NSF OAC1920103
6 · The paper itself

Abstract

Measurements of cell phylogeny based on natural or induced mutations, known as lineage barcodes, in conjunction with molecular phenotype have become increasingly feasible for a large number of single cells. In this chapter, we delve into Quantitative Fate Mapping (QFM) and its computational pipeline, which enables the interrogation of the dynamics of progenitor cells and their fate restriction during development. The methods described here include inferring cell phylogeny with the Phylotime model, and reconstructing progenitor state hierarchy, commitment time, population size, and commitment bias with the ICE-FASE algorithm. Evaluation of adequate sampling based on progenitor state coverage statistics is emphasized for interpreting the QFM results. Overall, this chapter describes a general framework for characterizing the dynamics of cell fate changes using lineage barcoding data.

Indexed as

AlgorithmsCell LineageAnimalsCell DifferentiationComputational BiologyDNA Barcoding, TaxonomicHumansPhylogenySingle-Cell AnalysisSoftwareStem CellsICE-FASELineage barcoding pipelineLineage tracingPhylotimeProgenitor state dynamicsQuantitative fate mapping (QFM)Time-scaled cell phylogeny

Identifiers

PMID39745641
PMCPMC12131283

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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.