scholarly journals Horizontal and vertical integrative analysis methods for mental disorders omics data

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Shuaichao Wang ◽  
Xingjie Shi ◽  
Mengyun Wu ◽  
Shuangge Ma
Keyword(s):  
Mental Disorders ◽  
Mental Disorder ◽  
Copy Number ◽  
Principal Component ◽  
Copy Number Variations ◽  
Integrative Analysis ◽  
Single Type ◽  
Horizontal Integration ◽  
Gene Expressions ◽  
Disease Etiology

Abstract In recent biomedical studies, omics profiling has been extensively conducted on various types of mental disorders. In most of the existing analyses, a single type of mental disorder and a single type of omics measurement are analyzed. In the study of other complex diseases, integrative analysis, both vertical and horizontal integration, has been conducted and shown to bring significantly new insights into disease etiology, progression, biomarkers, and treatment. In this article, we showcase the applicability of integrative analysis to mental disorders. In particular, the horizontal integration of bipolar disorder and schizophrenia and the vertical integration of gene expression and copy number variation data are conducted. The analysis is based on the sparse principal component analysis, penalization, and other advanced statistical techniques. In data analysis, integration leads to biologically sensible findings, including the disease-related gene expressions, copy number variations, and their associations, which differ from the “benchmark” analysis. Overall, this study suggests the potential of integrative analysis in mental disorder research.

scholarly journals Set-Wise Differential Interaction between Copy Number Alterations and Gene Expressions of Lower-Grade Glioma Reveals Prognosis-Associated Pathways

Entropy ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. 1434
Author(s):  
Seong Beom Cho
Keyword(s):  
Density Estimation ◽  
Cancer Progression ◽  
Copy Number ◽  
Integrative Analysis ◽  
The Cancer Genome Atlas ◽  
Lower Grade ◽  
Gene Expressions ◽  
Survival Group ◽  
Lower Grade Glioma ◽  
The Impact

The integrative analysis of copy number alteration (CNA) and gene expression (GE) is an essential part of cancer research considering the impact of CNAs on cancer progression and prognosis. In this research, an integrative analysis was performed with generalized differentially coexpressed gene sets (gdCoxS), which is a modification of dCoxS. In gdCoxS, set-wise interaction is measured using the correlation of sample-wise distances with Renyi’s relative entropy, which requires an estimation of sample density based on omics profiles. To capture correlations between the variables, multivariate density estimation with covariance was applied. In the simulation study, the power of gdCoxS outperformed dCoxS that did not use the correlations in the density estimation explicitly. In the analysis of the lower-grade glioma of the cancer genome atlas program (TCGA-LGG) data, the gdCoxS identified 577 pathway CNAs and GEs pairs that showed significant changes of interaction between the survival and non-survival group, while other benchmark methods detected lower numbers of such pathways. The biological implications of the significant pathways were well consistent with previous reports of the TCGA-LGG. Taken together, the gdCoxS is a useful method for an integrative analysis of CNAs and GEs.

scholarly journals Chromosomal abnormalities and copy number variations in children with idiopathic mental illness

2019 ◽  
pp. 80-81
Author(s):  
O. S. Kurinnaia ◽  
I. Y. Iourov ◽  
S. G. Vorsanova
Keyword(s):  
Mental Illness ◽  
Mental Disorders ◽  
Copy Number ◽  
Genetic Factors ◽  
Chromosomal Abnormalities ◽  
Copy Number Variations ◽  
Molecular Karyotyping ◽  
Correct Data

Genetic factors of mental illness are generally recognized. Here, it is shown that molecular karyotyping in combination with original bioinformatics methods offers the opportunity for effective uncovering genomic pathology, which may provide correct data on genetic factors for mental disorders in children.

22q11-q13 as a hot spot for prediction of disease-free survival in bile duct cancer: integrative analysis of copy number variations

2014 ◽  
Vol 207 (3) ◽  
pp. 57-69 ◽  
Author(s):  
Mee Joo Kang ◽  
Jayoun Kim ◽  
Jin-Young Jang ◽  
Taesung Park ◽  
Kyoung Bun Lee ◽  
...  
Keyword(s):  
Bile Duct ◽  
Bile Duct Cancer ◽  
Copy Number ◽  
Hot Spot ◽  
Disease Free Survival ◽  
Copy Number Variations ◽  
Integrative Analysis ◽  
Free Survival ◽  
Duct Cancer ◽  
Disease Free

scholarly journals Integrative Analysis and Identification of an Excellent lncRNA Signature to Predict Prognosis in Patients with COAD

2021 ◽  
Author(s):  
ZhiHua Chen ◽  
YiLin Lin ◽  
SuYong Lin ◽  
Ji Gao ◽  
Shao-Qin Chen
Keyword(s):  
Copy Number ◽  
Cox Regression ◽  
Gene Expression Omnibus ◽  
Copy Number Variations ◽  
Integrative Analysis ◽  
Transcriptome Data ◽  
Cox Regression Analysis ◽  
Number Variation ◽  
Cancer Genome Atlas ◽  
Internal Mechanism

Abstract Backgroud: Tumour recurrence and metastasis lead to poor prognosis incolon cancer(COAD). Therefore We aimed to identify a lncRNA signature through an integrative analysis of copy number variation, mutation and transcriptome data to predict prognosis and explore its internal mechanism.Methods: The lncRNA expression profile were collected fromThe Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). TCGA data was randomly divided 3:1 intotraining andtesting cohort. In the training, weperformed integrated analyses of three candidate lncRNA sets that correlated with prognosis, copy number variations and mutations to establish a signature through Cox regression analysis. The robustness was determined in the testing and GEO.Results: An 11-lncRNA signature that was significantly associated with prognosiswas constructed in the training (P<0.0001, HR=2.014) , And this signature was validated in the testing(P=0.0019, HR=3.374) and GSE17536(P=0.0076, HR=1.864). The signature is significantly related to MSI status and clinical prognostic factors. The prognostic-relatedrisk scores were significantly excellent than the other five models have been reported. Furthermore, GSEA suggested that the signature was involved in COAD development and metastasis-related pathways.Conclusions: We identifiedansignature has strong robustness and can stably predict the prognosis of COAD in different platformsand may be implicated in COAD pathogenesis and metastasis and applied clinically as a prognostic marker.

scholarly journals Integrative Analysis and Identification of an Excellent lncRNA Signature to Predict Prognosis in Patients With Colon Cancer

2021 ◽  
Author(s):  
ZhiHua Chen ◽  
YiLin Lin ◽  
SuYong Lin ◽  
YiSu Liu ◽  
Yan Zheng ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Copy Number ◽  
Cox Regression ◽  
Gene Expression Omnibus ◽  
Copy Number Variations ◽  
Integrative Analysis ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Cox Regression Analysis ◽  
Number Variation

Abstract Backgroud: Tumour recurrence and metastasis lead to poor prognosis in colon cancer (COAD). Therefore We aimed to identify a lncRNA signature through an integrative analysis of copy number variation, mutation and transcriptome data to predict prognosis and explore its internal mechanism.Methods: The lncRNA expression profile were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). TCGA data was randomly divided 3:1 into training and testing cohort. In the training, we performed integrated analyses of three candidate lncRNA sets that correlated with prognosis, copy number variations and mutations to establish a signature through Cox regression analysis. The robustness was determined in the testing and GEO. Results: An 11-lncRNA signature that was significantly associated with prognosis was constructed in the training (P<0.0001, HR=2.014) , And this signature was validated in the testing (P=0.0019, HR=3.374) and GSE17536 (P=0.0076, HR=1.864). The signature is significantly related to MSI status and clinical prognostic factors. The prognostic-related risk scores were significantly excellent than the other five models have been reported. Furthermore, GSEA suggested that the signature was involved in COAD development and metastasis-related pathways.Conclusions: We identified an signature has strong robustness and can stably predict the prognosis of COAD in different platforms and may be implicated in COAD pathogenesis and metastasis and applied clinically as a prognostic marker.

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