Evidence map›Paper›PMID 33713107›Full record

ArticleG3 (Bethesda, Md.)2021

MetaPrism: A versatile toolkit for joint taxa/gene analysis of metagenomic sequencing data.

Jiwoong Kim, Shuang Jiang, Yiqing Wang, Guanghua Xiao, Yang Xie, Dajiang J Liu, Qiwei Li, Andrew Koh, Xiaowei Zhan

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Jiwoong KimQuantitative Biomedical Research Center, Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
Shuang JiangDepartment of Statistical Science, Southern Methodist University, Dallas, TX 75275, USA.
Yiqing WangDepartment of Statistical Science, Southern Methodist University, Dallas, TX 75275, USA.
Guanghua XiaoQuantitative Biomedical Research Center, Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
Yang XieQuantitative Biomedical Research Center, Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
Dajiang J LiuDepartment of Public Health Sciences, Pennsylvania State University, Hershey, PA, 17033, USA.
Qiwei LiDepartment of Mathematical Sciences, The University of Texas at Dallas, Richardson, TX 75080, USA.
Andrew KohHarold C. Simmons Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
Xiaowei ZhanQuantitative Biomedical Research Center, Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.

Funding

UNIVERSITY OF TEXAS--SPORE IN LUNG CANCERP50CA070907 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI GIBBONS, DON LYNN · 1996 to 2024
$57.4M
UT Southwestern Medical Center Simmons Comprehensive Cancer CenterP30CA142543 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI Sandi Leigh Pruitt · 2010 to 2026
$53.7M
Method to Enhance the Rare Variant Genetic Architecture Analysis in Meta-AnalysesR01HG008983 · NHGRI · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI LIU, DAJIANG · 2016 to 2019
$1.6M
Integrative Analysis to Identify Regulation Targets of RNA-Binding ProteinsR01GM115473 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI XIE, YANG · 2016 to 2019
$1.3M
Tools for integrative genomics and disease association study for the X chromosomeR01GM126479 · NIGMS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI LIU, DAJIANG · 2018 to 2021
$1.2M
Methods to Identify, Validate & Interpret GWAS Loci in Multi-ethnic Meta-analysisR56HG011035 · NHGRI · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI LIU, DAJIANG · 2021 to 2021
$576k
NCI NIH HHS P30 CA142543NCI NIH HHS P50 CA070907NHGRI NIH HHS R01 HG008983NHGRI NIH HHS R56 HG011035NIGMS NIH HHS R01 GM115473NIGMS NIH HHS R01 GM126479
6 · The paper itself

Abstract

In microbiome research, metagenomic sequencing generates enormous amounts of data. These data are typically classified into taxa for taxonomy analysis, or into genes for functional analysis. However, a joint analysis where the reads are classified into taxa-specific genes is often overlooked. To enable the analysis of this biologically meaningful feature, we developed a novel bioinformatic toolkit, MetaPrism, which can analyze sequence reads for a set of joint taxa/gene analyses to: 1) classify sequence reads and estimate the abundances for taxa-specific genes; 2) tabularize and visualize taxa-specific gene abundances; 3) compare the abundances between groups; and 4) build prediction models for clinical outcome. We illustrated these functions using a published microbiome metagenomics dataset from patients treated with immune checkpoint inhibitor therapy and showed the joint features can serve as potential biomarkers to predict therapeutic responses. MetaPrism is a toolkit for joint taxa and gene analysis. It offers biological insights on the taxa-specific genes on top of the taxa-alone or gene-alone analysis. MetaPrism is open-source software and freely available at https://github.com/jiwoongbio/MetaPrism. The example script to reproduce the manuscript is also provided in the above code repository.

Indexed as

MetagenomicsMicrobiotaAlgorithmsComputational BiologyHumansMetagenomeSequence Analysis, DNASoftwarejoint analysismetagenomics sequence analysismicrobiome biomarker

Identifiers

PMID33713107
PMCPMC8049424

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.