GUItars: A GUI Tool for Analysis of High-Throughput RNA Interference Screening Data

被引:13
|
作者
Goktug, Asli N. [1 ]
Ong, Su Sien [1 ]
Chen, Taosheng [1 ]
机构
[1] St Jude Childrens Res Hosp, Dept Chem Biol & Therapeut, Memphis, TN 38105 USA
来源
PLOS ONE | 2012年 / 7卷 / 11期
关键词
FALSE NONDISCOVERY RATES; ASSAY QUALITY ASSESSMENT; HIT SELECTION; STATISTICAL-METHODS; DISCOVERY; PARAMETER; GENE; SSMD;
D O I
10.1371/journal.pone.0049386
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: High-throughput RNA interference (RNAi) screening has become a widely used approach to elucidating gene functions. However, analysis and annotation of large data sets generated from these screens has been a challenge for researchers without a programming background. Over the years, numerous data analysis methods were produced for plate quality control and hit selection and implemented by a few open-access software packages. Recently, strictly standardized mean difference (SSMD) has become a widely used method for RNAi screening analysis mainly due to its better control of false negative and false positive rates and its ability to quantify RNAi effects with a statistical basis. We have developed GUItars to enable researchers without a programming background to use SSMD as both a plate quality and a hit selection metric to analyze large data sets. Results: The software is accompanied by an intuitive graphical user interface for easy and rapid analysis workflow. SSMD analysis methods have been provided to the users along with traditionally-used z-score, normalized percent activity, and t-test methods for hit selection. GUItars is capable of analyzing large-scale data sets from screens with or without replicates. The software is designed to automatically generate and save numerous graphical outputs known to be among the most informative high-throughput data visualization tools capturing plate-wise and screen-wise performances. Graphical outputs are also written in HTML format for easy access, and a comprehensive summary of screening results is written into tab-delimited output files. Conclusion: With GUItars, we demonstrated robust SSMD-based analysis workflow on a 3840-gene small interfering RNA (siRNA) library and identified 200 siRNAs that increased and 150 siRNAs that decreased the assay activities with moderate to stronger effects. GUItars enables rapid analysis and illustration of data from large- or small-scale RNAi screens using SSMD and other traditional analysis methods. The software is freely available at http://sourceforge.net/projects/guitars/.
引用
收藏
页数:8
相关论文
共 50 条
  • [21] Use of Cryopreserved Cell Aliquots in the High-Throughput Screening of Small Interfering RNA Libraries
    Swearingen, Elissa A.
    Fajardo, Flordeliza
    Wang, Xiangyun
    Watson, J. E. Vivienne
    Quon, Kim C.
    Kassner, Paul D.
    JOURNAL OF BIOMOLECULAR SCREENING, 2010, 15 (05) : 469 - 477
  • [22] Transcriptome Analysis of the Silkworm (Bombyx mori) by High-Throughput RNA Sequencing
    Li, Yinu
    Wang, Guozeng
    Tian, Jian
    Liu, Huifen
    Yang, Huipeng
    Yi, Yongzhu
    Wang, Jinhui
    Shi, Xiaofeng
    Jiang, Feng
    Yao, Bin
    Zhang, Zhifang
    PLOS ONE, 2012, 7 (08):
  • [23] The mammalian two-hybrid system as a powerful tool for high-throughput drug screening
    Patricio, Daniela
    Fardilha, Margarida
    DRUG DISCOVERY TODAY, 2020, 25 (04) : 764 - 771
  • [24] BioAssay Ontology Annotations Facilitate Cross-Analysis of Diverse High-Throughput Screening Data Sets
    Schuerer, Stephan C.
    Vempati, Uma
    Smith, Robin
    Southern, Mark
    Lemmon, Vance
    JOURNAL OF BIOMOLECULAR SCREENING, 2011, 16 (04) : 415 - 426
  • [25] High-Throughput Screening Approach for Nanoporous Materials Genome Using Topological Data Analysis: Application to Zeolites
    Lee, Yongjin
    Barthel, Senja D.
    Dlotko, Pawel
    Moosavi, Seyed Mohamad
    Hess, Kathryn
    Smit, Berend
    JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2018, 14 (08) : 4427 - 4437
  • [26] Bayesian Multi-Plate High-Throughput Screening of Compounds
    Shterev, Ivo D.
    Dunson, David B.
    Chan, Cliburn
    Sempowski, Gregory D.
    SCIENTIFIC REPORTS, 2018, 8
  • [27] Comprehensive analysis of high-throughput screens with HiTSeekR
    List, Markus
    Schmidt, Steffen
    Christiansen, Helle
    Rehmsmeier, Marc
    Tan, Qihua
    Mollenhauer, Jan
    Baumbach, Jan
    NUCLEIC ACIDS RESEARCH, 2016, 44 (14) : 6639 - 6648
  • [28] High-throughput screening technologies for enzyme engineering
    Longwell, Chelsea K.
    Labanieh, Louai
    Cochran, Jennifer R.
    CURRENT OPINION IN BIOTECHNOLOGY, 2017, 48 : 196 - 202
  • [29] Functional annotation of lncRNA in high-throughput screening
    Yip, Chi Wai
    Sivaraman, Divya M.
    Prabhu, Anika V.
    Shin, Jay W.
    NON-CODING GENOME, 2021, 65 (04): : 761 - 773
  • [30] A constitutive expression system for high-throughput screening
    Aerts, Dirk
    Verhaeghe, Tom
    De Mey, Marjan
    Desmet, Tom
    Soetaert, Wim
    ENGINEERING IN LIFE SCIENCES, 2011, 11 (01): : 10 - 19