Evidence map›Paper›PMID 40029517›Full record

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

In-Depth, High-Throughput Analysis of BcR IG Clonality and Diversity Levels in Immune Repertoires.

Laura Zaragoza-Infante, Glykeria Gkoliou, Elisavet Vlachonikola, Athanasios Roussos, Konstantinos Kardamiliotis, Anastasia Chatzidimitriou, Fotis Psomopoulos, Andreas Agathangelidis

Abstract read
PubMed 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

8 authors.

Laura Zaragoza-InfanteSwiss Tropical and Public Health Institute, Basel, Switzerland.
Glykeria GkoliouInstitute of Applied Biosciences, Thessaloniki, Greece.
Elisavet VlachonikolaInstitute of Applied Biosciences, Thessaloniki, Greece.
Athanasios RoussosInstitute of Applied Biosciences, Thessaloniki, Greece.
Konstantinos KardamiliotisInstitute of Applied Biosciences, Thessaloniki, Greece.
Anastasia ChatzidimitriouInstitute of Applied Biosciences, Thessaloniki, Greece.
Fotis PsomopoulosInstitute of Applied Biosciences, Thessaloniki, Greece.
Andreas AgathangelidisDepartment of Biology, School of Science, National and Kapodistrian University of Athens, Athens, Greece. agathan@biol.uoa.gr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advent of high-throughput sequencing technologies revolutionized the analysis of immune repertoires, allowing a much more detailed characterization in both qualitative and quantitative terms. This delved into a better understanding of the complexity of B-cell receptor immunoglobulin (BcR IG) repertoires in a wide range of diseases, such as infections, autoimmune diseases, and B-cell lymphomas. More particularly, growing evidence highlights the role of interactions with (auto)antigens in driving disease onset and evolution through selecting B-cell clones bearing immunogenetically specific BcR IG and continuously transforming the latter through inducing intraclonal diversification (ID). However, the increase in the volume and complexity of high-throughput data necessitated the development of bioinformatics tools enabling a fast and efficient analysis of immune repertoires.Here, we describe an approach to dissect high-throughput BcR IG data, through the application of purpose-built analytical tools. This strategy offers a compartmentalized characterization of BcR IG repertoires starting from raw high-throughput data. First, the T-cell receptor/immunoglobulin profiler (TRIP) tool represents a robust and flexible software framework for the analysis of the clonality and diversity of BcR IG gene repertoires. Subsequently, the Immunoglobulin Intraclonal Diversification Analysis (IgIDivA) tool integrates both traditional and innovative graph-based metrics to determine objectively the level of intraclonal diversification (ID), alongside statistical analysis to compare ID levels and features across various sample groups.

Indexed as

Computational BiologyHigh-Throughput Nucleotide SequencingReceptors, Antigen, B-CellAnimalsB-LymphocytesHumansSoftwareReceptors, Antigen, B-CellB-cell receptor immunoglobulinClonalityDiversityGraph metricsGraph networksImmune repertoireIntraclonal diversificationNext-generation sequencingSomatic hypermutation

Identifiers

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.