Evidence map›Paper›PMID 29272348›Full record

ArticleBioinformatics (Oxford, England)2018

TCGA-assembler 2: software pipeline for retrieval and processing of TCGA/CPTAC data.

Lin Wei, Zhilin Jin, Shengjie Yang, Yanxun Xu, Yitan Zhu, Yuan Ji

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 119 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
119citing papers in PubMed, 1 pooled it
–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

119 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Identification of Clinically Relevant Genes Using Machine Learning Techniques.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  4. Rapid Exploratory Data Visualization for Cancer Genomics.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  5. Article
  6. An Interpretable Omics-to-Image Transformer Framework for Cancer Prognosis Prediction.Computational and structural biotechnology journal · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

59 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

6 authors.

Lin WeiProgram of Computational Genomics & Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA.
Zhilin JinDepartment of Applied Mathematics & Statistics, Johns Hopkins University, Baltimore, MD 21218, USA.
Shengjie YangProgram of Computational Genomics & Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA.
Yanxun XuDepartment of Applied Mathematics & Statistics, Johns Hopkins University, Baltimore, MD 21218, USA.
Yitan ZhuProgram of Computational Genomics & Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA.
Yuan JiProgram of Computational Genomics & Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA.

Funding

Bayesian models for cancer prognosis by integrating diverse types of dataR01CA132897 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI JI, YUAN, MUELLER, PETER · 2008 to 2019
$2.1M
NCI NIH HHS R01 CA132897
6 · The paper itself

Abstract

Motivation: The Cancer Genome Atlas (TCGA) program has produced huge amounts of cancer genomics data providing unprecedented opportunities for research. In 2014, we developed TCGA-Assembler, a software pipeline for retrieval and processing of public TCGA data. In 2016, TCGA data were transferred from the TCGA data portal to the Genomic Data Commons (GDCs), which is supported by a different set of data storage and retrieval mechanisms. In addition, new proteomics data of TCGA samples have been generated by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) program, which were not available for downloading through TCGA-Assembler. It is desirable to acquire and integrate data from both GDC and CPTAC. Results: We develop TCGA-assembler 2 (TA2) to automatically download and integrate data from GDC and CPTAC. We make substantial improvement on the functionality of TA2 to enhance user experience and software performance. TA2 together with its previous version have helped more than 2000 researchers from 64 countries to access and utilize TCGA and CPTAC data in their research. Availability of TA2 will continue to allow existing and new users to conduct reproducible research based on TCGA and CPTAC data. Availability and implementation: http://www.compgenome.org/TCGA-Assembler/ or https://github.com/compgenome365/TCGA-Assembler-2. Contact: zhuyitan@gmail.com or koaeraser@gmail.com. Supplementary information: Supplementary data are available at Bioinformatics online.

Indexed as

SoftwareGenomeGenomicsInformation Storage and RetrievalNeoplasmsProteomics

Identifiers

PMID29272348
PMCPMC5925773

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.