PMID- 28724352
OWN - NLM
STAT- MEDLINE
DCOM- 20180313
LR  - 20240104
IS  - 1471-2164 (Electronic)
IS  - 1471-2164 (Linking)
VI  - 18
IP  - 1
DP  - 2017 Jul 19
TI  - A permutation-based non-parametric analysis of CRISPR screen data.
PG  - 545
LID - 10.1186/s12864-017-3938-5 [doi]
LID - 545
AB  - BACKGROUND: Clustered regularly-interspaced short palindromic repeats (CRISPR) 
      screens are usually implemented in cultured cells to identify genes with critical 
      functions. Although several methods have been developed or adapted to analyze 
      CRISPR screening data, no single specific algorithm has gained popularity. Thus, 
      rigorous procedures are needed to overcome the shortcomings of existing 
      algorithms. METHODS: We developed a Permutation-Based Non-Parametric Analysis 
      (PBNPA) algorithm, which computes p-values at the gene level by permuting sgRNA 
      labels, and thus it avoids restrictive distributional assumptions. Although PBNPA 
      is designed to analyze CRISPR data, it can also be applied to analyze genetic 
      screens implemented with siRNAs or shRNAs and drug screens. RESULTS: We compared 
      the performance of PBNPA with competing methods on simulated data as well as on 
      real data. PBNPA outperformed recent methods designed for CRISPR screen analysis, 
      as well as methods used for analyzing other functional genomics screens, in terms 
      of Receiver Operating Characteristics (ROC) curves and False Discovery Rate (FDR) 
      control for simulated data under various settings. Remarkably, the PBNPA 
      algorithm showed better consistency and FDR control on published real data as 
      well. CONCLUSIONS: PBNPA yields more consistent and reliable results than its 
      competitors, especially when the data quality is low. R package of PBNPA is 
      available at: https://cran.r-project.org/web/packages/PBNPA/ .
FAU - Jia, Gaoxiang
AU  - Jia G
AD  - Department of Statistical Science, Southern Methodist University, Dallas, TX, 
      75205, USA.
AD  - Quantitative Biomedical Research Center, Department of Clinical Sciences, 
      University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
FAU - Wang, Xinlei
AU  - Wang X
AD  - Department of Statistical Science, Southern Methodist University, Dallas, TX, 
      75205, USA. swang@smu.edu.
FAU - Xiao, Guanghua
AU  - Xiao G
AUID- ORCID: 0000-0001-9387-9883
AD  - Quantitative Biomedical Research Center, Department of Clinical Sciences, 
      University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA. 
      guanghua.xiao@utsouthwestern.edu.
AD  - Department of Bioinformatics, University of Texas Southwestern Medical Center, 
      Dallas, TX, 75390, USA. guanghua.xiao@utsouthwestern.edu.
AD  - Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical 
      Center, Dallas, TX, 75390, USA. guanghua.xiao@utsouthwestern.edu.
LA  - eng
GR  - R15 GM113157/GM/NIGMS NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
DEP - 20170719
PL  - England
TA  - BMC Genomics
JT  - BMC genomics
JID - 100965258
RN  - 0 (RNA, Guide, CRISPR-Cas Systems)
SB  - IM
MH  - *Algorithms
MH  - Clustered Regularly Interspaced Short Palindromic Repeats/*genetics
MH  - RNA, Guide, CRISPR-Cas Systems/genetics
MH  - Statistics, Nonparametric
PMC - PMC5518132
OTO - NOTNLM
OT  - False discovery rate
OT  - Functional genomics
OT  - Negative selection
OT  - Next generation sequencing
OT  - Positive selection
OT  - RNA interference
COIS- ETHICS APPROVAL AND CONSENT TO PARTICIPATE: Not applicable. CONSENT FOR 
      PUBLICATION: Not applicable. COMPETING INTERESTS: The authors declare that they 
      have no competing interests. PUBLISHER'S NOTE: Springer Nature remains neutral 
      with regard to jurisdictional claims in published maps and institutional 
      affiliations.
EDAT- 2017/07/21 06:00
MHDA- 2018/03/14 06:00
PMCR- 2017/07/19
CRDT- 2017/07/21 06:00
PHST- 2017/01/19 00:00 [received]
PHST- 2017/07/12 00:00 [accepted]
PHST- 2017/07/21 06:00 [entrez]
PHST- 2017/07/21 06:00 [pubmed]
PHST- 2018/03/14 06:00 [medline]
PHST- 2017/07/19 00:00 [pmc-release]
AID - 10.1186/s12864-017-3938-5 [pii]
AID - 3938 [pii]
AID - 10.1186/s12864-017-3938-5 [doi]
PST - epublish
SO  - BMC Genomics. 2017 Jul 19;18(1):545. doi: 10.1186/s12864-017-3938-5.