Evidence map›Paper›PMID 21622959›Full record

ArticleNucleic acids research2011

A novel bioinformatics pipeline for identification and characterization of fusion transcripts in breast cancer and normal cell lines.

Yan W Asmann, Asif Hossain, Brian M Necela, Sumit Middha, Krishna R Kalari, Zhifu Sun, High-Seng Chai, David W Williamson, Derek Radisky, Gary P Schroth and 3 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.

0numbers the graph read from it
0cells of the map it votes in
65citing 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

65 citing papers in PubMed.

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5 more citing papers are in PubMed but not listed here.

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

13 authors.

Yan W AsmannDivision of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA.
Asif Hossain
Brian M Necela
Sumit Middha
Krishna R Kalari
Zhifu Sun
High-Seng Chai
David W Williamson
Derek Radisky
Gary P Schroth
Jean-Pierre A Kocher
Edith A Perez
E Aubrey Thompson

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SnowShoes-FTD, developed for fusion transcript detection in paired-end mRNA-Seq data, employs multiple steps of false positive filtering to nominate fusion transcripts with near 100% confidence. Unique features include: (i) identification of multiple fusion isoforms from two gene partners; (ii) prediction of genomic rearrangements; (iii) identification of exon fusion boundaries; (iv) generation of a 5'-3' fusion spanning sequence for PCR validation; and (v) prediction of the protein sequences, including frame shift and amino acid insertions. We applied SnowShoes-FTD to identify 50 fusion candidates in 22 breast cancer and 9 non-transformed cell lines. Five additional fusion candidates with two isoforms were confirmed. In all, 30 of 55 fusion candidates had in-frame protein products. No fusion transcripts were detected in non-transformed cells. Consideration of the possible functions of a subset of predicted fusion proteins suggests several potentially important functions in transformation, including a possible new mechanism for overexpression of ERBB2 in a HER-positive cell line. The source code of SnowShoes-FTD is provided in two formats: one configured to run on the Sun Grid Engine for parallelization, and the other formatted to run on a single LINUX node. Executables in PERL are available for download from our web site: http://mayoresearch.mayo.edu/mayo/research/biostat/stand-alone-packages.cfm.

Indexed as

Gene FusionSoftwareBreast NeoplasmsCell LineCell Line, TumorComputational BiologyErb-b2 Receptor Tyrosine KinasesFemaleHumansMutant Chimeric ProteinsMutationPromoter Regions, GeneticRNA, MessengerSequence AlignmentSequence Analysis, RNAErb-b2 Receptor Tyrosine KinasesMutant Chimeric ProteinsRNA, Messenger

Identifiers

PMID21622959
PMCPMC3159479

What OpenQuestion holds

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LicenceCC BY-NC
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.