Ask about this productRelated genes to: SOHLH2 antibody
- Gene:
- CCDC169-SOHLH2 NIH gene
- Name:
- CCDC169-SOHLH2 readthrough
- Previous symbol:
- C13orf38-SOHLH2
- Synonyms:
- -
- Chromosome:
- 13q13.3
- Locus Type:
- readthrough
- Date approved:
- 2011-02-21
- Date modifiied:
- 2014-11-19
- Gene:
- SOHLH2 NIH gene
- Name:
- spermatogenesis and oogenesis specific basic helix-loop-helix 2
- Previous symbol:
- -
- Synonyms:
- FLJ20449, TEB1, bHLHe81, SPATA28
- Chromosome:
- 13q13.3
- Locus Type:
- gene with protein product
- Date approved:
- 2006-03-16
- Date modifiied:
- 2019-03-19
Related products to: SOHLH2 antibody
Related articles to: SOHLH2 antibody
- Two datasets were used as training and validation cohorts to establish the predictive model. We used three types of screening criteria: background analysis, pathway analysis, and functional analysis provided by the cBioportal website. Fisher's exact test and multivariable logistic regression were performed to screen out related genes. Furthermore, we performed receiver operating characteristic (ROC) and Kaplan-Meier curve analyses to evaluate the correlation between the selected genes and overall survival. - Source: PubMed
Publication date: 2022/02/09
Li ShuxinMao QianqianZhang ZixuanWang YuqiChen DuoxuanChen ZhenwenLu Jianyi - Long-term balancing selection typically leaves narrow footprints of increased genetic diversity, and therefore most detection approaches only achieve optimal performances when sufficiently small genomic regions (i.e., windows) are examined. Such methods are sensitive to window sizes and suffer substantial losses in power when windows are large. Here, we employ mixture models to construct a set of five composite likelihood ratio test statistics, which we collectively term B statistics. These statistics are agnostic to window sizes and can operate on diverse forms of input data. Through simulations, we show that they exhibit comparable power to the best-performing current methods, and retain substantially high power regardless of window sizes. They also display considerable robustness to high mutation rates and uneven recombination landscapes, as well as an array of other common confounding scenarios. Moreover, we applied a specific version of the B statistics, termed B2, to a human population-genomic data set and recovered many top candidates from prior studies, including the then-uncharacterized STPG2 and CCDC169-SOHLH2, both of which are related to gamete functions. We further applied B2 on a bonobo population-genomic data set. In addition to the MHC-DQ genes, we uncovered several novel candidate genes, such as KLRD1, involved in viral defense, and SCN9A, associated with pain perception. Finally, we show that our methods can be extended to account for multiallelic balancing selection and integrated the set of statistics into open-source software named BalLeRMix for future applications by the scientific community. - Source: PubMed
Cheng XiaohengDeGiorgio Michael