FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2991379968> ?p ?o ?g. }

• W2991379968 endingPage "2010" @default.
• W2991379968 startingPage "2000" @default.
• W2991379968 abstract "Identification of differentially expressed genes (DEGs) under two or more experimental conditions is an important task for elucidating the molecular basis of phenotypic variation. In the recent years, next generation sequencing (RNA-seq) has become very attractive and competitive alternative to the microarrays because of reducing the cost of sequencing and limitations of microarrays. A number of methods have been developed for detecting the DEGs from RNA-seq data. Most of these methods are based on either Poisson distribution or negative binomial (NB) distribution. However, identification of DEGs based on read count data using skewed distribution is inflexible and complicated of in presence of outliers or extreme values. Most of the existing DEGs selection methods produce lower accuracies and higher false discoveries in presence of outliers. There are some robust approaches such as edgeR_robust and DEseq2 perform well in presence of outliers for large sample case. But they show weak performance for small-sample case, in presence of outliers. To address this issues an alternative approach has emerged by transforming the RNA-seq data into microarray like data. Among various transformation methods voom using limma pipeline is proven better for RNA-seq data. However, limma by voom transformation is sensitive to outliers for small-sample case. Therefore, in this paper, we robustify the voom approach using the minimum β-divergence method. We demonstrate the performance of the proposed method in a comparison of seven popular biomarkers selection methods: DEseq, DEseq2, SAMseq, Bayseq, limma (voom), edgeR and edgeR_robust using both simulated and real dataset. Both types of experimental results show that the performance of the proposed method improve over the competing methods, in presence of outliers and in absence of outliers it keeps almost equal performance with these methods. We observe the improved performance of the proposed method from simulation and real RNA-seq count data analysis for both small-and large-sample cases, in presence of outliers. Therefore, our proposal is to use the proposed method instead of existing methods to obtain the better performance for selecting the DEGs." @default.
• W2991379968 created "2019-12-05" @default.
• W2991379968 creator A5022121090 @default.
• W2991379968 creator A5028741163 @default.
• W2991379968 creator A5046850375 @default.
• W2991379968 creator A5070055467 @default.
• W2991379968 creator A5081661969 @default.
• W2991379968 date "2020-03-01" @default.
• W2991379968 modified "2023-10-01" @default.
• W2991379968 title "Robust identification of differentially expressed genes from RNA-seq data" @default.
• W2991379968 cites W1545338101 @default.
• W2991379968 cites W1980548655 @default.
• W2991379968 cites W1981509058 @default.
• W2991379968 cites W1989367702 @default.
• W2991379968 cites W1994018858 @default.
• W2991379968 cites W1996968822 @default.
• W2991379968 cites W2027455260 @default.
• W2991379968 cites W2056786014 @default.
• W2991379968 cites W2066303883 @default.
• W2991379968 cites W2068392526 @default.
• W2991379968 cites W2072602203 @default.
• W2991379968 cites W2098734857 @default.
• W2991379968 cites W2107018762 @default.
• W2991379968 cites W2112058982 @default.
• W2991379968 cites W2114104545 @default.
• W2991379968 cites W2119034410 @default.
• W2991379968 cites W2124097252 @default.
• W2991379968 cites W2137526110 @default.
• W2991379968 cites W2141425631 @default.
• W2991379968 cites W2152239989 @default.
• W2991379968 cites W2154431984 @default.
• W2991379968 cites W2156631105 @default.
• W2991379968 cites W2159675211 @default.
• W2991379968 cites W2179438025 @default.
• W2991379968 cites W2741148388 @default.
• W2991379968 cites W2907180417 @default.
• W2991379968 cites W4245806510 @default.
• W2991379968 cites W640119782 @default.
• W2991379968 doi "https://doi.org/10.1016/j.ygeno.2019.11.012" @default.
• W2991379968 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31756426" @default.
• W2991379968 hasPublicationYear "2020" @default.
• W2991379968 type Work @default.
• W2991379968 sameAs 2991379968 @default.
• W2991379968 citedByCount "18" @default.
• W2991379968 countsByYear W29913799682021 @default.
• W2991379968 countsByYear W29913799682022 @default.
• W2991379968 countsByYear W29913799682023 @default.
• W2991379968 crossrefType "journal-article" @default.
• W2991379968 hasAuthorship W2991379968A5022121090 @default.
• W2991379968 hasAuthorship W2991379968A5028741163 @default.
• W2991379968 hasAuthorship W2991379968A5046850375 @default.
• W2991379968 hasAuthorship W2991379968A5070055467 @default.
• W2991379968 hasAuthorship W2991379968A5081661969 @default.
• W2991379968 hasBestOaLocation W29913799681 @default.
• W2991379968 hasConcept C100906024 @default.
• W2991379968 hasConcept C104317684 @default.
• W2991379968 hasConcept C105795698 @default.
• W2991379968 hasConcept C124101348 @default.
• W2991379968 hasConcept C150194340 @default.
• W2991379968 hasConcept C154945302 @default.
• W2991379968 hasConcept C199335787 @default.
• W2991379968 hasConcept C33643355 @default.
• W2991379968 hasConcept C33923547 @default.
• W2991379968 hasConcept C41008148 @default.
• W2991379968 hasConcept C54355233 @default.
• W2991379968 hasConcept C70721500 @default.
• W2991379968 hasConcept C79337645 @default.
• W2991379968 hasConcept C86803240 @default.
• W2991379968 hasConcept C95371953 @default.
• W2991379968 hasConceptScore W2991379968C100906024 @default.
• W2991379968 hasConceptScore W2991379968C104317684 @default.
• W2991379968 hasConceptScore W2991379968C105795698 @default.
• W2991379968 hasConceptScore W2991379968C124101348 @default.
• W2991379968 hasConceptScore W2991379968C150194340 @default.
• W2991379968 hasConceptScore W2991379968C154945302 @default.
• W2991379968 hasConceptScore W2991379968C199335787 @default.
• W2991379968 hasConceptScore W2991379968C33643355 @default.
• W2991379968 hasConceptScore W2991379968C33923547 @default.
• W2991379968 hasConceptScore W2991379968C41008148 @default.
• W2991379968 hasConceptScore W2991379968C54355233 @default.
• W2991379968 hasConceptScore W2991379968C70721500 @default.
• W2991379968 hasConceptScore W2991379968C79337645 @default.
• W2991379968 hasConceptScore W2991379968C86803240 @default.
• W2991379968 hasConceptScore W2991379968C95371953 @default.
• W2991379968 hasIssue "2" @default.
• W2991379968 hasLocation W29913799681 @default.
• W2991379968 hasOpenAccess W2991379968 @default.
• W2991379968 hasPrimaryLocation W29913799681 @default.
• W2991379968 hasRelatedWork W1562077703 @default.
• W2991379968 hasRelatedWork W172675283 @default.
• W2991379968 hasRelatedWork W1825921272 @default.
• W2991379968 hasRelatedWork W1849881158 @default.
• W2991379968 hasRelatedWork W1971627635 @default.
• W2991379968 hasRelatedWork W2005599694 @default.
• W2991379968 hasRelatedWork W3174403465 @default.
• W2991379968 hasRelatedWork W3210390693 @default.
• W2991379968 hasRelatedWork W4283692479 @default.
• W2991379968 hasRelatedWork W4319841362 @default.

• next