Evidence map›Paper›PMID 39068367›Full record

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

A Protocol for the Detection of Fusion Transcripts Using RNA-Sequencing Data.

Fiza Hamid, Simran Arora, Pragya Chitkara, Shailesh Kumar

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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. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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.

Fiza HamidBioinformatics Laboratory, National Institute of Plant Genome Research (NIPGR), New Delhi, India.
Simran AroraBioinformatics Laboratory, National Institute of Plant Genome Research (NIPGR), New Delhi, India.
Pragya ChitkaraBioinformatics Laboratory, National Institute of Plant Genome Research (NIPGR), New Delhi, India.
Shailesh KumarBioinformatics Laboratory, National Institute of Plant Genome Research (NIPGR), New Delhi, India. shailesh@nipgr.ac.in.ORCID 0000-0002-1872-9903

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fusion transcripts are formed when two genes or their mRNAs fuse to produce a novel gene or chimeric transcript. Fusion genes are well-known cancer biomarkers used for cancer diagnosis and as therapeutic targets. Gene fusions are also found in normal physiology and lead to the evolution of novel genes that contribute to better survival and adaptation for an organism. Various in vitro approaches, such as FISH, PCR, RT-PCR, and chromosome banding techniques, have been used to detect gene fusion. However, all these approaches have low resolution and throughput. Due to the development of high-throughput next-generation sequencing technologies, the detection of fusion transcript becomes feasible using whole genome sequencing, RNA-Seq data, and bioinformatics tools. This chapter will overview the general computational protocol for fusion transcript detection from RNA-sequencing datasets.

Indexed as

Computational BiologyHigh-Throughput Nucleotide SequencingSequence Analysis, RNAGene FusionHumansNeoplasmsRNA, MessengerSoftwareRNA, MessengerChimeric RNAsFusion geneFusion transcriptRNA-SeqTools

Identifiers

What OpenQuestion holds

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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.