scholarly journals Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting

2017 ◽  
Author(s):  
Francesco Iorio ◽  
Fiona M Behan ◽  
Emanuel Gonçalves ◽  
Shriram G Bhosle ◽  
Elisabeth Chen ◽  
...  
Keyword(s):  
Copy Number ◽  
Large Scale ◽  
False Positive Rate ◽  
Essential Genes ◽  
Driver Genes ◽  
Cancer Driver ◽  
Guide Rna ◽  
Genome Wide ◽  
Positive Rate ◽  
Downstream Analysis

AbstractBackground: Genome editing by CRISPR-Cas9 technology allows large-scale screening of gene essentiality in cancer. A confounding factor when interpreting CRISPR-Cas9 screens is the high false-positive rate in detecting essential genes within copy number amplified regions of the genome. We have developed the computational tool CRISPRcleanR which is capable of identifying and correcting gene-independent responses to CRISPR-Cas9 targeting. CRISPRcleanR uses an unsupervised approach based on the segmentation of single-guide RNA fold change values across the genome, without making any assumption about the copy number status of the targeted genes.Results Applying our method to existing and newly generated genome-wide essentiality profiles from 15 cancer cell lines, we demonstrate that CRISPRcleanR reduces false positives when calling essential genes, correcting biases within and outside of amplified regions, while maintaining true positive rates. Established cancer dependencies and essentiality signals of amplified cancer driver genes are detectable post-correction. CRISPRcleanR reports sgRNA fold changes and normalised read counts, is therefore compatible with downstream analysis tools, and works with multiple sgRNA libraries.Conclusions CRISPRcleanR is a versatile open-source tool for the analysis of CRISPR-Cas9 knockout screens to identify essential genes.

scholarly journals Understanding How Genetic Mutations Collaborate with Genomic Instability in Cancer

Cells ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 342
Author(s):  
Laura J. Jilderda ◽  
Lin Zhou ◽  
Floris Foijer
Keyword(s):  
Cancer Cells ◽  
Chromosomal Instability ◽  
Large Scale ◽  
Small Scale ◽  
Genetic Screens ◽  
Driver Genes ◽  
Cancer Driver ◽  
The Past ◽  
Cancer Models ◽  
Genome Wide

Chromosomal instability is the process of mis-segregation for ongoing chromosomes, which leads to cells with an abnormal number of chromosomes, also known as an aneuploid state. Induced aneuploidy is detrimental during development and in primary cells but aneuploidy is also a hallmark of cancer cells. It is therefore believed that premalignant cells need to overcome aneuploidy-imposed stresses to become tumorigenic. Over the past decade, some aneuploidy-tolerating pathways have been identified through small-scale screens, which suggest that aneuploidy tolerance pathways can potentially be therapeutically exploited. However, to better understand the processes that lead to aneuploidy tolerance in cancer cells, large-scale and unbiased genetic screens are needed, both in euploid and aneuploid cancer models. In this review, we describe some of the currently known aneuploidy-tolerating hits, how large-scale genome-wide screens can broaden our knowledge on aneuploidy specific cancer driver genes, and how we can exploit the outcomes of these screens to improve future cancer therapy.

scholarly journals Genome-wide CRISPR-Cas9 screen in E. coli identifies design rules for efficient targeting

2018 ◽  
Author(s):  
Belen Gutierrez ◽  
Jérôme Wong Ng ◽  
Lun Cui ◽  
Christophe Becavin ◽  
David Bikard
Keyword(s):  
Copy Number ◽  
Large Scale ◽  
Mixed Population ◽  
Target Sequence ◽  
Guide Rna ◽  
E Coli ◽  
Genome Wide ◽  
A Genome

AbstractThe main outcome of efficient CRISPR-Cas9 cleavage in the chromosome of bacteria is cell death. This can be conveniently used to eliminate specific genotypes from a mixed population of bacteria, which can be achieved both in vitro, e.g. to select mutants, or in vivo as an antimicrobial strategy. The efficiency with which Cas9 kills bacteria has been observed to be quite variable depending on the specific target sequence, but little is known about the sequence determinants and mechanisms involved. Here we performed a genome-wide screen of Cas9 cleavage in the chromosome of E. coli to determine the efficiency with which each guide RNA kills the cell. Surprisingly we observed a large-scale pattern where guides targeting some regions of the chromosome are more rapidly depleted than others. Unexpectedly, this pattern arises from the influence of degrading specific chromosomal regions on the copy number of the plasmid carrying the guide RNA library. After taking this effect into account, it is possible to train a neural network to predict Cas9 efficiency based on the target sequence. We show that our model learns different features than previous models trained on Eukaryotic CRISPR-Cas9 knockout libraries. Our results highlight the need for specific models to design efficient CRISPR-Cas9 tools in bacteria.

Identification of and Correction for Publication Bias: Comment

2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson
Keyword(s):  
Publication Bias ◽  
False Positive ◽  
Large Scale ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Effect Sizes ◽  
Replication Studies ◽  
Moderate Reduction ◽  
Positive Rate ◽  
Meta Analyses

Andrews & Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

scholarly journals Genetic effect estimates in case-control studies when a continuous variable is omitted from the model

2019 ◽  
Author(s):  
Ying Sheng ◽  
Chiung-Yu Huang ◽  
Siarhei Lobach ◽  
Lydia Zablotska ◽  
Iryna Lobach ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
False Positive Rate ◽  
Continuous Variable ◽  
Genetic Effects ◽  
Data Availability ◽  
Conditional Density ◽  
Link Type ◽  
Genome Wide

ABSTRACTLarge-scale genome-wide analyses scans provide massive volumes of genetic variants on large number of cases and controls that can be used to estimate the genetic effects. Yet, the sets of non-genetic variables available in publicly available databases are often brief. It is known that omitting a continuous variable from a logistic regression model can result in biased estimates of odds ratios (OR) (e.g., Gail et al (1984), Neuhaus et al (1993), Hauck et al (1991), Zeger et al (1988)). We are interested to assess what information is needed to recover the bias in the OR estimate of genotype due to omitting a continuous variable in settings when the actual values of the omitted variable are not available. We derive two estimating procedures that can recover the degree of bias based on a conditional density of the omitted variable or knowing the distribution of the omitted variable. Importantly, our derivations show that omitting a continuous variable can result in either under- or over-estimation of the genetic effects. We performed extensive simulation studies to examine bias, variability, false positive rate, and power in the model that omits a continuous variable. We show the application to two genome-wide studies of Alzheimer’s disease.Data Availability StatementThe data that support the findings of this study are openly available in the Database of Genotypes and Phenotypes at [https://www.ncbi.nlm.nih.gov/projects/gap/cgibin/study.cgi?study_id=phs000372.v1.p1], reference number [phs000372.v1.p1] and at the Alzheimer’s Disease Neuroimaging Initiative http://adni.loni.usc.edu/.

scholarly journals Efficient Detection of Large-Scale Multimedia Network Information Data Anomalies Based on the Rule-Extracting Matrix Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Jie Zhao
Keyword(s):  
Large Scale ◽  
False Positive Rate ◽  
Detection Accuracy ◽  
Network Information ◽  
Matrix Algorithm ◽  
Efficient Detection ◽  
Sample Data ◽  
Multimedia Social Networks ◽  
Positive Rate ◽  
Rule Extracting

With the continuous development of multimedia social networks, online public opinion information is becoming more and more popular. The rule extraction matrix algorithm can effectively improve the probability of information data to be tested. The network information data abnormality detection is realized through the probability calculation, and the prior probability is calculated, to realize the detection of abnormally high network data. Practical results show that the rule-extracting matrix algorithm can effectively control the false positive rate of sample data, the detection accuracy is improved, and it has efficient detection performance.

scholarly journals Systematic identification of mutations and copy number alterations associated with cancer patient prognosis

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Joan C Smith ◽  
Jason M Sheltzer
Keyword(s):  
Copy Number ◽  
Meta Analysis ◽  
Gene Copy Number ◽  
Gene Copy ◽  
Driver Genes ◽  
Cancer Driver ◽  
Molecular Alterations ◽  
Patient Prognosis ◽  
Almost All ◽  
Systematic Identification

Successful treatment decisions in cancer depend on the accurate assessment of patient risk. To improve our understanding of the molecular alterations that underlie deadly malignancies, we analyzed the genomic profiles of 17,879 tumors from patients with known outcomes. We find that mutations in almost all cancer driver genes contain remarkably little information on patient prognosis. However, CNAs in these same driver genes harbor significant prognostic power. Focal CNAs are associated with worse outcomes than broad alterations, and CNAs in many driver genes remain prognostic when controlling for stage, grade, TP53 status, and total aneuploidy. By performing a meta-analysis across independent patient cohorts, we identify robust prognostic biomarkers in specific cancer types, and we demonstrate that a subset of these alterations also confer specific therapeutic vulnerabilities. In total, our analysis establishes a comprehensive resource for cancer biomarker identification and underscores the importance of gene copy number profiling in assessing clinical risk.

scholarly journals A systems genomics approach to uncover the molecular properties of cancer genes

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Felix Grassmann ◽  
Yudi Pawitan ◽  
Kamila Czene
Keyword(s):  
Cancer Survival ◽  
Association Studies ◽  
Gc Content ◽  
Molecular Properties ◽  
Molecular Profile ◽  
Genome Wide Association Studies ◽  
Cancer Genes ◽  
Driver Genes ◽  
Cancer Driver ◽  
Genome Wide

Abstract Genes involved in cancer are under constant evolutionary pressure, potentially resulting in diverse molecular properties. In this study, we explore 23 omic features from publicly available databases to define the molecular profile of different classes of cancer genes. Cancer genes were grouped according to mutational landscape (germline and somatically mutated genes), role in cancer initiation (cancer driver genes) or cancer survival (survival genes), as well as being implicated by genome-wide association studies (GWAS genes). For each gene, we also computed feature scores based on all omic features, effectively summarizing how closely a gene resembles cancer genes of the respective class. In general, cancer genes are longer, have a lower GC content, have more isoforms with shorter exons, are expressed in more tissues and have more transcription factor binding sites than non-cancer genes. We found that germline genes more closely resemble single tissue GWAS genes while somatic genes are more similar to pleiotropic cancer GWAS genes. As a proof-of-principle, we utilized aggregated feature scores to prioritize genes in breast cancer GWAS loci and found that top ranking genes were enriched in cancer related pathways. In conclusion, we have identified multiple omic features associated with different classes of cancer genes, which can assist prioritization of genes in cancer gene discovery.

scholarly journals Spontaneous mutations in maize pollen are frequent in some lines and arise mainly from retrotranspositions and deletions

2019 ◽  
Vol 116 (22) ◽  
pp. 10734-10743 ◽  
Author(s):  
Hugo K. Dooner ◽  
Qinghua Wang ◽  
Jun T. Huang ◽  
Yubin Li ◽  
Limei He ◽  
...  
Keyword(s):  
Copy Number ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Ltr Retrotransposons ◽  
Spontaneous Mutations ◽  
Maize Pollen ◽  
Genome Wide ◽  
Autonomous Element ◽  
Low Copy Number ◽  
Female Germline

While studying spontaneous mutations at the maizebronze(bz) locus, we made the unexpected discovery that specific low-copy number retrotransposons are mobile in the pollen of some maize lines, but not of others. We conducted large-scale genetic experiments to isolate newbzmutations from severalBzstocks and recovered spontaneous stable mutations only in the pollen parent in reciprocal crosses. Most of the new stablebzmutations resulted from either insertions of low-copy number long terminal repeat (LTR) retrotransposons or deletions, the same two classes of mutations that predominated in a collection of spontaneouswxmutations [Wessler S (1997)The Mutants of Maize, pp 385–386]. Similar mutations were recovered at the closely linkedshlocus. These events occurred with a frequency of 2–4 × 10−5in two lines derived from W22 and in 4Co63, but not at all in B73 or Mo17, two inbreds widely represented in Corn Belt hybrids. Surprisingly, the mutagenic LTR retrotransposons differed in the active lines, suggesting differences in the autonomous element make-up of the lines studied. Some active retrotransposons, likeHopscotch,Magellan, andBs2, aBs1variant, were described previously; others, likeFotoandFocouin 4Co63, were not. By high-throughput sequencing of retrotransposon junctions, we established that retrotranposition ofHopscotch,Magellan, andBs2occurs genome-wide in the pollen of active lines, but not in the female germline or in somatic tissues. We discuss here the implications of these results, which shed light on the source, frequency, and nature of spontaneous mutations in maize.

scholarly journals Bloom Filter-Based Secure Data Forwarding in Large-Scale Cyber-Physical Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-12
Author(s):  
Siyu Lin ◽  
Hao Wu
Keyword(s):  
False Positive ◽  
Large Scale ◽  
False Positive Rate ◽  
Bloom Filter ◽  
Cyber Physical Systems ◽  
Security Requirements ◽  
Data Forwarding ◽  
Physical Systems ◽  
Secure Data ◽  
Positive Rate

Cyber-physical systems (CPSs) connect with the physical world via communication networks, which significantly increases security risks of CPSs. To secure the sensitive data, secure forwarding is an essential component of CPSs. However, CPSs require high dimensional multiattribute and multilevel security requirements due to the significantly increased system scale and diversity, and hence impose high demand on the secure forwarding information query and storage. To tackle these challenges, we propose a practical secure data forwarding scheme for CPSs. Considering the limited storage capability and computational power of entities, we adopt bloom filter to store the secure forwarding information for each entity, which can achieve well balance between the storage consumption and query delay. Furthermore, a novel link-based bloom filter construction method is designed to reduce false positive rate during bloom filter construction. Finally, the effects of false positive rate on the performance of bloom filter-based secure forwarding with different routing policies are discussed.

scholarly journals Detection of de novo copy number deletions from targeted sequencing of trios

2018 ◽  
Author(s):  
Jack M. Fu ◽  
Elizabeth J. Leslie ◽  
Alan F. Scott ◽  
Jeffrey C. Murray ◽  
Mary L. Marazita ◽  
...  
Keyword(s):  
Open Source Software ◽  
Copy Number ◽  
Minimum Distance ◽  
Formal Method ◽  
De Novo ◽  
False Positive Rate ◽  
Targeted Sequencing ◽  
Lower False Positive Rate ◽  
Positive Rate ◽  
Sequencing Platforms

AbstractDe novo copy number deletions have been implicated in many diseases, but there is no formal method to date however that identifies de novo deletions in parent-offspring trios from capture-based sequencing platforms. We developed Minimum Distance for Targeted Sequencing (MDTS) to fill this void. MDTS has similar sensitivity (recall), but a much lower false positive rate compared to less specific CNV callers, resulting in a much higher positive predictive value (precision). MDTS also exhibited much better scalability, and is available as open source software at github.com/JMF47/MDTS.

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