Evidence map›Paper›PMID 35879727›Full record

ArticleGenome biology2022

ZetaSuite: computational analysis of two-dimensional high-throughput data from multi-target screens and single-cell transcriptomics.

Yajing Hao, Shuyang Zhang, Changwei Shao, Junhui Li, Guofeng Zhao, Dong-Er Zhang, Xiang-Dong Fu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome biology, 2022. 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
0.3field-weighted citation impact, top 48% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  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

7 authors at 3 institutions in 2 countries.

Yajing HaoDepartment of Cellular and Molecular Medicine, Institute of Genomic Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
Shuyang ZhangDepartment of Cellular and Molecular Medicine, Institute of Genomic Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
Changwei ShaoDepartment of Cellular and Molecular Medicine, Institute of Genomic Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
Junhui Li, 29 Rosedale Ave, MA 01545, Shrewsbury, USA.
Guofeng ZhaoHoward Hughes Medical Institute, Department of Medicine, University of California, San Diego, La Jolla, CA, 92093, USA.
Dong-Er ZhangMoores Cancer Center, Department of Biological Sciences, Department of Pathology, University of California, San Diego, La Jolla, CA, 92093, USA.
Xiang-Dong FuDepartment of Cellular and Molecular Medicine, Institute of Genomic Medicine, University of California San Diego, La Jolla, CA, 92093, USA. xdfu@health.ucsd.edu.ORCID 0000-0001-5499-8732
University of California San Diego · USHoward Hughes Medical Institute · USShrewsbury College · GB

Funding

Functional RNA elements in the human genomeR01HG004659 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Kevin Daniel Corbett, Eugene Wei-Ming Yeo · 2008 to 2026
$12.4M
Synergestic roles of SRSF2 and RUNX1 in blood cell development and pathologyR01DK098808 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ZHANG, DONG-ER · 2013 to 2022
$4.8M
Synergestic roles of SRF2 and RUNX1 in blood cell development and pathologyR56DK098808 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FU, XIANG-DONG, ZHANG, DONG-ER · 2018 to 2018
$100k
NHGRI NIH HHS R01 HG004659NIDDK NIH HHS R01 DK098808NIDDK NIH HHS R56 DK098808
6 · The paper itself

Abstract

Two-dimensional high-throughput data have become increasingly common in functional genomics studies, which raises new challenges in data analysis. Here, we introduce a new statistic called Zeta, initially developed to identify global splicing regulators from a two-dimensional RNAi screen, a high-throughput screen coupled with high-throughput functional readouts, and ZetaSuite, a software package to facilitate general application of the Zeta statistics. We compare our approach with existing methods using multiple benchmarked datasets and then demonstrate the broad utility of ZetaSuite in processing public data from large-scale cancer dependency screens and single-cell transcriptomics studies to elucidate novel biological insights.

Indexed as

High-Throughput Screening AssaysTranscriptomeGenomicsRNA InterferenceSingle-Cell AnalysisSoftwareCancer checkpointCancer dependencySingle-cell RNA-seqtwo-dimensional RNAi screeningZeta statistics

Identifiers

PMID35879727
PMCPMC9310463
OpenAlexW4287146918

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.