Evidence map›Paper›PMID 40455162›Full record

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

Diverse Facets of Nonhuman Sequences in Read Outputs of the Human Next-Generation Sequencing Data and Their Relevance with Viruses.

Amit Pathania

Abstract read
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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

1 author.

Amit PathaniaMM Engineering College, Maharishi Markandeshwar University, Mullana-Ambala, Haryana, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In human genomic studies, on average, 10% of next-generation sequencing (NGS) reads fail to align with the human reference genome. These unmapped reads vary across samples and have three main potential sources. First, they could represent contamination introduced during sample processing or from the sequencing technology itself. Second, these sequences might originate from microorganisms, like viruses, bacteria, and fungi, that have coevolved with humans and residing within humans. These natural inhabitants of the human body make up the human microbiota. During taking the human cell samples, the microbiota of the surroundings can infect the human samples. Third, these reads could come from active or dormant pathogens residing in the taken human cell samples, like viruses. Research shows that the composition of these microbial species changes with the health and condition of human tissues. In this study, author proposes that unmapped reads may serve as indicators of the pathological state of various tissues and cell types. An outline is marked for experimental approaches to test these ideas and explore the potential of these reads as diagnostic markers.

Indexed as

High-Throughput Nucleotide SequencingVirusesComputational BiologyGenome, HumanGenomicsHumansMicrobiotaSequence Analysis, DNAMicrobiomeMicrobiotaNext-generation sequencingTranscriptomicsViriomeVirus infections

Identifiers

PMID40455162

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.