Evidence map›Paper›PMID 38683324›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

Analyses of Nuclear Reads Obtained Using Genome Skimming.

Siavash Mirarab, Vineet Bafna

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. DipSkmer: Reference-free population genomics with diploid genome skims.bioRxiv : the preprint server for biology · 2026
    Article
  2. Article
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.

Siavash MirarabElectrical and Computer Engineering, University of California-San Diego, La Jolla, CA, USA. smirarab@ucsd.edu.
Vineet BafnaComputer Science and Engineering, University of California-San Diego, La Jolla, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this protocol paper, we review a set of methods developed in recent years for analyzing nuclear reads obtained from genome skimming. As the cost of sequencing drops, genome skimming (low-coverage shotgun sequencing of a sample) becomes increasingly a cost-effective method of measuring biodiversity at high resolution. While most practitioners only use assembled over-represented organelle reads from a genome skim, the vast majority of the reads are nuclear. Using assembly-free and alignment-free methods described in this protocol, we can compare samples to each other and reference genomes to compute distances, characterize underlying genomes, and infer evolutionary relationships.

Indexed as

High-Throughput Nucleotide SequencingSequence Analysis, DNACell NucleusComputational BiologyGenomeGenomicsHumansSoftwareBioinformaticsGenome sequencingGenome skimmingNuclear DNAShort read archive (SRA)

Identifiers

PMID38683324

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.