Evidence map›Paper›PMID 34450618›Full record

ArticleBioinformatics (Oxford, England)2022

TPWshiny: an interactive R/Shiny app to explore cell line transcriptional responses to anti-cancer drugs.

Peter Zhang, Alida Palmisano, Ravindra Kumar, Ming-Chung Li, James H Doroshow, Yingdong Zhao

Open access · hybridAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 32% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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 at 3 institutions in 1 country.

Peter ZhangUC Berkeley College of Letters and Science, Berkeley, CA 94720, USA.
Alida PalmisanoDivision of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD 20850, USA.ORCID 0000-0002-1859-3719
Ravindra KumarDivision of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD 20850, USA.ORCID 0000-0002-0121-8402
Ming-Chung LiDivision of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD 20850, USA.
James H DoroshowDivision of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD 20850, USA.
Yingdong ZhaoDivision of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD 20850, USA.ORCID 0000-0002-8514-0293
National Cancer Institute · USBerkeley College · USGeneral Dynamics (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

summaryThe NCI Transcriptional Pharmacodynamics Workbench (NCI TPW) is an extensive compilation of directly measured transcriptional responses to anti-cancer agents across the well-characterized NCI-60 cancer cell lines. The NCI TPW data are publicly available through a web interface that allows limited user interaction with the data. We developed 'TPWshiny' as a standalone, easy to install, R application to facilitate more interactive data exploration.With no programming skills required, TPWshiny provides an intuitive and comprehensive graphical interface to help researchers understand the response of tumor cell lines to 15 therapeutic agents. The data are presented in interactive scatter plots, heatmaps, time series and Venn diagrams. Data can be queried by drug concentration, time point, gene and tissue type. Researchers can download the data for further analysis. AVAILABILITY AND IMPLEMENTATION: Users can download the ready-to-use, self-extracting package for Windows or macOS, and R source code from the project website (https://brb.nci.nih.gov/TPWshiny/). TPWshiny documentation and additional information can be found on the project website.

Indexed as

Antineoplastic AgentsMobile ApplicationsCell Line, TumorSoftwareAntineoplastic Agents

Identifiers

PMID34450618
PMCPMC10060698
OpenAlexW3195324812

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.