Cell-Free DNA-Based Methods to Map Chromatin.

Stephanie Eramo, Abigail Weirich, Srinivas Ramachandran

Abstract read

In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. 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

3 authors.

Stephanie EramoStructural Biology, Biochemistry, and Biophysics Graduate Program, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.

Abigail WeirichDepartment of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.

Srinivas RamachandranDepartment of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. srinivas.ramachandran@cuanschutz.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell-free DNA (cfDNA) provides a non-invasive means to monitor physiological states and diagnose diseases, with widespread applications in oncology. Our lab utilizes cfDNA as a tool to investigate the state of the tumor and the tumor microenvironment in patients with cancer. This chapter outlines methods for cfDNA extraction from plasma, library preparation for sequencing, and subsequent computational analysis that will enable analysis of cfDNA footprints genome-wide. By examining cfDNA fragment lengths and their genomic origins, we can infer cellular dynamics and identify potential biomarkers for various health conditions, offering valuable insights into the body's internal processes with significant implications for advancing diagnostic and therapeutic approaches.

Indexed as

Cell-Free Nucleic AcidsChromatinBiomarkers, TumorHigh-Throughput Nucleotide SequencingHumansNeoplasmsSequence Analysis, DNABiomarkers, TumorCell-Free Nucleic AcidsChromatincfDNAChromatinEpigenomicsSubnucleosome

Identifiers

PMID42642604

DOI10.1093/bioinformatics/btq033

What OpenQuestion holds

Textmetadata

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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.