scholarly journals HotSpotAnnotations—a database for hotspot mutations and annotations in cancer

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Victor Trevino
Keyword(s):  
Statistical Model ◽  
False Discovery Rate ◽  
Biomedical Research ◽  
Manual Annotation ◽  
False Discovery Rate Correction ◽  
Dna Hairpins ◽  
Novel Treatments ◽  
False Discovery ◽  
Cancer Types ◽  
Hotspot Mutations

Abstract Hotspots, recurrently mutated DNA positions in cancer, are thought to be oncogenic drivers because random chance is unlikely and the knowledge of clear examples of oncogenic hotspots in genes like BRAF, IDH1, KRAS and NRAS among many other genes. Hotspots are attractive because provide opportunities for biomedical research and novel treatments. Nevertheless, recent evidence, such as DNA hairpins for APOBEC3A, suggests that a considerable fraction of hotspots seem to be passengers rather than drivers. To document hotspots, the database HotSpotsAnnotations is proposed. For this, a statistical model was implemented to detect putative hotspots, which was applied to TCGA cancer datasets covering 33 cancer types, 10 182 patients and 3 175 929 mutations. Then, genes and hotspots were annotated by two published methods (APOBEC3A hairpins and dN/dS ratio) that may inform and warn researchers about possible false functional hotspots. Moreover, manual annotation from users can be added and shared. From the 23 198 detected as possible hotspots, 4435 were selected after false discovery rate correction and minimum mutation count. From these, 305 were annotated as likely for APOBEC3A whereas 442 were annotated as unlikely. To date, this is the first database dedicated to annotating hotspots for possible false functional hotspots.

scholarly journals Service environment link and false discovery rate correction: Methodological considerations in population and health facility surveys

PLoS ONE ◽  
2019 ◽  
Vol 14 (7) ◽  
pp. e0219860 ◽  
Author(s):  
Teketo Kassaw Tegegne ◽  
Catherine Chojenta ◽  
Theodros Getachew ◽  
Roger Smith ◽  
Deborah Loxton
Keyword(s):  
False Discovery Rate ◽  
Health Facility ◽  
False Discovery Rate Correction ◽  
Service Environment ◽  
False Discovery ◽  
Methodological Considerations

scholarly journals RNA Sequencing Keloid Transcriptome Associates Keloids With Th2, Th1, Th17/Th22, and JAK3-Skewing

2020 ◽  
Vol 11 ◽  
Author(s):  
Jianni Wu ◽  
Ester Del Duca ◽  
Michael Espino ◽  
Alyssa Gontzes ◽  
Inna Cueto ◽  
...  
Keyword(s):  
False Discovery Rate ◽  
T Cell Activation ◽  
Cell Activation ◽  
Normal Skin ◽  
Treatment Options ◽  
Lesional Skin ◽  
Novel Treatments ◽  
False Discovery ◽  
Stat Signaling ◽  
Therapeutic Development

Keloids are disfiguring, fibroproliferative growths and their pathogenesis remains unclear, inhibiting therapeutic development. Available treatment options have limited efficacy and harbor safety concerns. Thus, there is a great need to clarify keloid pathomechanisms that may lead to novel treatments. In this study, we aimed to elucidate the profile of lesional and non-lesional keloid skin compared to normal skin. We performed gene (RNAseq, qRT-PCR) and protein (immunohistochemistry) expression analyses on biopsy specimens obtained from lesional and non-lesional skin of African American (AA) keloid patients compared to healthy skin from AA controls. Fold-change≥2 and false-discovery rate (FDR)<0.05 was used to define significance. We found that lesional versus normal skin showed significant up-regulation of markers of T-cell activation/migration (ICOS, CCR7), Th2- (IL-4R, CCL11, TNFSF4/OX40L), Th1- (CXCL9/CXCL10/CXCL11), Th17/Th22- (CCL20, S100As) pathways, and JAK/STAT-signaling (JAK3) (false-discovery rate [FDR]<0.05). Non-lesional skin also exhibited similar trends. We observed increased cellular infiltrates in keloid tissues, including T-cells, dendritic cells, mast cells, as well as greater IL-4rα+, CCR9+, and periostin+ immunostaining. In sum, comprehensive molecular profiling demonstrated that both lesional and non-lesional skin show significant immune alternations, and particularly Th2 and JAK3 expression. This advocates for the investigation of novel treatments targeting the Th2 axis and/or JAK/STAT-signaling in keloid patients.

scholarly journals Regional variations in adverse event reporting rates and ACR responses in placebo/standard-of-care arms of rheumatoid arthritis trials

Rheumatology ◽  
2020 ◽  
Vol 59 (10) ◽  
pp. 3023-3031 ◽  
Author(s):  
Daniel Keebler ◽  
Edmond Teng ◽  
Jenny Chia ◽  
Joshua Galanter ◽  
Jodie Peake ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Latin America ◽  
False Discovery Rate ◽  
Western Europe ◽  
Standard Of Care ◽  
Response Rates ◽  
False Discovery Rate Correction ◽  
False Discovery ◽  
Geographical Regions ◽  
Reporting Rates

Abstract Objective Clinical trials are increasingly globalized, and adverse event (AE) rates and treatment responses may differ by geographical region. This study assessed regional differences in AE reporting rates and ACR response rates (ACR20/50) in patients with RA who received placebo/standard-of-care treatment in clinical trials. Methods Patients from the placebo arms of 7 RA trials in the TransCelerate Biopharma Inc database were grouped into 5 geographical regions (Asia, Latin America, Russian Federation and Eastern Europe [RFEE], USA, and Western Europe). Differences in demographics, AE reporting rates and ACR response were evaluated using descriptive statistics and omnibus tests for significance; pairwise comparisons were made between regions, with false discovery rate correction for multiple comparisons. Results Among 970 patients included, week 12 AE rates were significantly lower in the RFEE than in Asia, Latin America and the USA (22% vs 51%, 49% and 53%, respectively; P < 0.05 after false discovery rate correction). Similar differences in AE rates across geographical regions were seen at week 52. Among 747 patients with ACR data, the lowest response rates were observed in the USA (ACR20, 22%) and RFEE (ACR50, 3%); the highest response rates were seen in Western Europe (ACR20, 43%) and Latin America (ACR50, 15%). Only the differences in ACR50 response between the RFEE and Latin America remained significant after false discovery rate correction. Conclusion These placebo/standard-of-care arm data revealed significant regional differences in AE reporting rates and ACR50 response rates. Regional distribution of patients should be considered when conducting RA clinical trials, particularly during recruitment.

scholarly journals Association between C-Maf-inducing protein gene rs2287112 polymorphism and schizophrenia

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11907
Author(s):  
Yingli Fu ◽  
Xiaojun Ren ◽  
Wei Bai ◽  
Qiong Yu ◽  
Yaoyao Sun ◽  
...  
Keyword(s):  
Linkage Disequilibrium ◽  
False Discovery Rate ◽  
Chinese Population ◽  
Multiple Comparisons ◽  
Han Chinese ◽  
Type I ◽  
Healthy Controls ◽  
False Discovery Rate Correction ◽  
Han Chinese Population ◽  
False Discovery

Background Schizophrenia is a severely multifactorial neuropsychiatric disorder, and the majority of cases are due to genetic variations. In this study, we evaluated the genetic association between the C-Maf-inducing protein (CMIP) gene and schizophrenia in the Han Chinese population. Methods In this case-control study, 761 schizophrenia patients and 775 healthy controls were recruited. Tag single-nucleotide polymorphisms (SNPs; rs12925980, rs2287112, rs3751859 and rs77700579) from the CMIP gene were genotyped via matrix-assisted laser desorption/ionization time of flight mass spectrometry. We used logistic regression to estimate the associations between the genotypes/alleles of each SNP and schizophrenia in males and females, respectively. The in-depth link between CMIP and schizophrenia was explored through linkage disequilibrium (LD) and further haplotype analyses. False discovery rate correction was utilized to control for Type I errors caused by multiple comparisons. Results There was a significant difference in rs287112 allele frequencies between female schizophrenia patients and healthy controls after adjusting for multiple comparisons (χ2 = 12.296, Padj = 0.008). Females carrying minor allele G had 4.445 times higher risk of schizophrenia compared with people who carried the T allele (OR = 4.445, 95% CI [1.788–11.046]). Linkage-disequilibrium was not observed in the subjects, and people with haplotype TTGT of rs12925980–rs2287112–rs3751859–rs77700579 had a lower risk of schizophrenia (OR = 0.42, 95% CI [0.19–0.94]) when compared with CTGA haplotypes. However, the association did not survive false discovery rate correction. Conclusion This study identified a potential CMIP variant that may confer schizophrenia risk in the female Han Chinese population.

scholarly journals False Discovery Rate Control Under General Dependence By Symmetrized Data Aggregation

2021 ◽  
pp. 1-34
Author(s):  
Lilun Du ◽  
Xu Guo ◽  
Wenguang Sun ◽  
Changliang Zou
Keyword(s):  
False Discovery Rate ◽  
Rate Control ◽  
Data Aggregation ◽  
False Discovery Rate Control ◽  
False Discovery

scholarly journals False Discovery Rate in Linkage and Association Genome Screens for Complex Disorders

Genetics ◽  
2003 ◽  
Vol 164 (2) ◽  
pp. 829-833
Author(s):  
Chiara Sabatti ◽  
Susan Service ◽  
Nelson Freimer
Keyword(s):  
Gene Mapping ◽  
False Discovery Rate ◽  
Disease Gene ◽  
Susceptibility Genes ◽  
Complex Disorders ◽  
Disease Gene Mapping ◽  
False Discovery ◽  
Simple Step ◽  
Multiple Comparison Procedure ◽  
Step Down

Abstract We explore the implications of the false discovery rate (FDR) controlling procedure in disease gene mapping. With the aid of simulations, we show how, under models commonly used, the simple step-down procedure introduced by Benjamini and Hochberg controls the FDR for the dependent tests on which linkage and association genome screens are based. This adaptive multiple comparison procedure may offer an important tool for mapping susceptibility genes for complex diseases.

scholarly journals P14.21 Tehila Kaisman-Elbaz MD/PhD

2019 ◽  
Vol 21 (Supplement_3) ◽  
pp. iii71-iii71
Author(s):  
T Kaisman-Elbaz ◽  
Y Elbaz ◽  
V Merkin ◽  
L Dym ◽  
A Noy ◽  
...  
Keyword(s):  
Overall Survival ◽  
Multivariate Analysis ◽  
False Discovery Rate ◽  
Medical Center ◽  
Tumor Resection ◽  
Multiple Hypothesis Testing ◽  
Hemoglobin Level ◽  
Distribution Width ◽  
False Discovery ◽  
Dismal Prognosis

Abstract BACKGROUND Glioblastoma is known for its dismal prognosis though its dependency on patients’ readily available RBCs parameters defining the patient’s anemic status such as hemoglobin level and Red blood cells distribution Width (RDW) is not fully established. Several works demonstrated a connection between low hemoglobin level or high RDW values to overall glioblastoma patient’s survival, but in other works, a clear connection was not found. This study addresses this unclarity. MATERIAL AND METHODS In this work, 170 glioblastoma patients, diagnosed and treated in Soroka University Medical Center (SUMC) in the last 12 years were retrospectively inspected for their survival dependency on pre-operative RBCs parameters using multivariate analysis followed by false discovery rate procedure due to the multiple hypothesis testing. A survival stratification tree and Kaplan-Meier survival curves that indicate the patient’s prognosis according to these parameters were prepared. RESULTS Beside KPS>70 and tumor resection supplemented by oncological treatment, age<70 (HR=0.4, 95% CI 0.24–0.65), low hemoglobin level (HR=1.79, 95% CI 1.06–2.99) and RDW<14% (HR=0.57, 95% CI 0.37–0.88) were found to be prognostic to patients’ overall survival in multivariate analysis, accounting for false discovery rate of less than 5%. CONCLUSION A survival stratification highlighted a non-anemic subgroup of nearly 30% of the cohort’s patients whose median overall survival was 21.1 months (95% CI 16.2–27.2) - higher than the average Stupp protocol overall median survival of about 15 months. A discussion on the beneficial or detrimental effect of RBCs parameters on glioblastoma prognosis and its possible causes is given.

scholarly journals Associations Between Genetically Predicted Protein Levels and COVID-19 Severity

2020 ◽  
Vol 223 (1) ◽  
pp. 19-22
Author(s):  
Jingjing Zhu ◽  
Chong Wu ◽  
Lang Wu
Keyword(s):  
False Discovery Rate ◽  
Drug Repurposing ◽  
Bonferroni Correction ◽  
Host Genetics ◽  
Protein Levels ◽  
False Discovery

Abstract It is critical to identify potential causal targets for SARS-CoV-2, which may guide drug repurposing options. We assessed the associations between genetically predicted protein levels and COVID-19 severity. Leveraging data from the COVID-19 Host Genetics Initiative comparing 6492 hospitalized COVID-19 patients and 1 012 809 controls, we identified 18 proteins with genetically predicted levels to be associated with COVID-19 severity at a false discovery rate of &lt;0.05, including 12 that showed an association even after Bonferroni correction. Of the 18 proteins, 6 showed positive associations and 12 showed inverse associations. In conclusion, we identified 18 candidate proteins for COVID-19 severity.

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