Evidence map›Paper›PMID 25594743›Full record

ArticleCancer medicine2015

Open pipelines for integrated tumor genome profiles reveal differences between pancreatic cancer tumors and cell lines.

Jeremy Goecks, Bassel F El-Rayes, Shishir K Maithel, H Jean Khoury, James Taylor, Michael R Rossi

Abstract read
In one paragraph

Article in Cancer medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  5. Article
  6. blend4php: a PHP API for galaxy.Database : the journal of biological databases and curation · 2017
    Article
  7. 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

6 authors.

Jeremy GoecksComputational Biology Institute, George Washington University, Ashburn, Virginia, 20147.
Bassel F El-Rayes
Shishir K Maithel
H Jean Khoury
James Taylor
Michael R Rossi

Funding

Winship Cancer Institute Cancer Center Support GrantP30CA138292 · NCI · EMORY UNIVERSITY · PI Suresh S Ramalingam · 2009 to 2026
$47.5M
Democratization of Data Analysis in Life Sciences Through GalaxyU41HG006620 · NHGRI · PENNSYLVANIA STATE UNIVERSITY, THE · PI NEKRUTENKO, ANTON, SCHATZ, MICHAEL · 2012 to 2020
$14.4M
Democratization of Data Analysis in Life Sciences Through GalaxyU24HG006620 · NHGRI · PENNSYLVANIA STATE UNIVERSITY, THE · PI Daniel James Blankenberg, Jeremy Goecks · 2021 to 2026
$9.8M
Dynamically scalable accessible analysis for next generation sequence dataRC2HG005542 · NHGRI · EMORY UNIVERSITY · PI NEKRUTENKO, ANTON, TAYLOR, JAMES PETER · 2009 to 2010
$1.5M
A Turnkey Solution for Next Generation Sequence Data AnalysisR21HG005133 · NHGRI · EMORY UNIVERSITY · PI TAYLOR, JAMES PETER · 2009 to 2010
$445k
NCI NIH HHS P30 CA138292NHGRI NIH HHS HG005133NHGRI NIH HHS HG005542NHGRI NIH HHS HG006620NHGRI NIH HHS R21 HG005133NHGRI NIH HHS RC2 HG005542NHGRI NIH HHS U24 HG006620NHGRI NIH HHS U41 HG006620
6 · The paper itself

Abstract

We describe open, reproducible pipelines that create an integrated genomic profile of a cancer and use the profile to find mutations associated with disease and potentially useful drugs. These pipelines analyze high-throughput cancer exome and transcriptome sequence data together with public databases to find relevant mutations and drugs. The three pipelines that we have developed are: (1) an exome analysis pipeline, which uses whole or targeted tumor exome sequence data to produce a list of putative variants (no matched normal data are needed); (2) a transcriptome analysis pipeline that processes whole tumor transcriptome sequence (RNA-seq) data to compute gene expression and find potential gene fusions; and (3) an integrated variant analysis pipeline that uses the tumor variants from the exome pipeline and tumor gene expression from the transcriptome pipeline to identify deleterious and druggable mutations in all genes and in highly expressed genes. These pipelines are integrated into the popular Web platform Galaxy at http://usegalaxy.org/cancer to make them accessible and reproducible, thereby providing an approach for doing standardized, distributed analyses in clinical studies. We have used our pipeline to identify similarities and differences between pancreatic adenocarcinoma cancer cell lines and primary tumors.

Indexed as

Genes, NeoplasmCell LineCell Line, TumorErb-b2 Receptor Tyrosine KinasesExomeGene Expression ProfilingGenome, HumanHigh-Throughput Nucleotide SequencingHumansMutationPancreatic NeoplasmsProto-Oncogene ProteinsProto-Oncogene Proteins p21(ras)ras ProteinsSequence Analysis, RNAERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesKRAS protein, humanProto-Oncogene ProteinsProto-Oncogene Proteins p21(ras)ras ProteinsAnalysis pipelinesbioinformaticsgalaxygenomic tumor profilespancreatic cancer

Identifiers

PMID25594743
PMCPMC4380965

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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.