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[PDF] Top 20 Differential correlation for sequencing data

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Differential correlation for sequencing data

Differential correlation for sequencing data

... makes the method more computationally tractable, but also solves the problem of dependencies between pairs. There were some inconsistencies, such as the higher posterior probabilities for subsampling compared to the ... See full document

9

A tail-based test for differential expression analysis and pathway analysis in RNA-sequencing  data

A tail-based test for differential expression analysis and pathway analysis in RNA-sequencing data

... RNA sequencing data have been abundantly generated in biomedical research for biomarker discovery and pathway ...Such data at the exon-level are usually heavily tailed and ...for differential ... See full document

126

Differential expression analysis of RNA sequencing data by incorporating non-exonic mapped reads

Differential expression analysis of RNA sequencing data by incorporating non-exonic mapped reads

... for sequencing library ...nation, sequencing errors, or unprocessed RNAs, like pre-mRNAs [17], or even non-coding RNAs ...RNA-seq data set, the non-exo- nic read counts for all genes are mostly less ... See full document

13

limma powers differential expression analyses for RNA-sequencing and microarray studies

limma powers differential expression analyses for RNA-sequencing and microarray studies

... RNA-seq data, the voomWithQualityWeights function combines observation-level and sample-specific weights for use in the subsequent linear ...sensus correlation. The correlation structure is then ... See full document

13

limma powers differential expression analyses for RNA-sequencing and microarray studies

limma powers differential expression analyses for RNA-sequencing and microarray studies

... RNA-seq data, the voomWithQualityWeights function combines observation-level and sample-specific weights for use in the subsequent linear ...sensus correlation. The correlation structure is then ... See full document

14

Erythrocyte microRNA sequencing reveals differential expression in relapsing-remitting multiple sclerosis

Erythrocyte microRNA sequencing reveals differential expression in relapsing-remitting multiple sclerosis

... unpublished data, see reference [6]), and showed great stability in a hepatic study ...Pearson correlation coeffi- cients between confirmed miRNA and recorded disease outcome measures (Table 1) were ... See full document

12

Copy-number-aware differential analysis of quantitative DNA sequencing data

Copy-number-aware differential analysis of quantitative DNA sequencing data

... We have developed a flexible approach called ABCD-DNA (Affinity Based Copy-number-aware Differential quantitative DNA sequenc- ing analyses) that integrates CNV and other systematic facto[r] ... See full document

35

Trajectory-based differential expression analysis for single-cell sequencing data

Trajectory-based differential expression analysis for single-cell sequencing data

... trajectory-based differential expression analysis for sequencing ...of differential expression pattern along a lineage or between lineages, leading to clear interpretation of the results ...simulated ... See full document

13

Data compression for sequencing data

Data compression for sequencing data

... of sequencing, taken from the NHGRI Web page [5], reflect not only reagent costs like some studies show, but also include labor, administration, amortization of sequencing instruments, submission of ... See full document

13

Troubleshooting Sequencing Data

Troubleshooting Sequencing Data

... Not enough DNA in the sequencing reactions Use more DNA in the sequencing reactions. Load or inject more of the resuspended sequencing reactions. See “Preparing and Loading Samples for Gel ... See full document

5

aFold – using polynomial uncertainty modelling for differential gene expression estimation from RNA sequencing data

aFold – using polynomial uncertainty modelling for differential gene expression estimation from RNA sequencing data

... count data across genes and treatment ...simulated data sets, we demonstrate that aFold is at least as efficient as and often better in discriminating DE and non-DE, espe- cially in the presence of outliers ... See full document

17

Correcting the Mean-Variance Dependency for Differential Variability Testing Using Single-Cell RNA Sequencing Data.

Correcting the Mean-Variance Dependency for Differential Variability Testing Using Single-Cell RNA Sequencing Data.

... In general, stable gene-specific variability estimates ideally require a large and deeply sequenced dataset containing a homogeneous cell population (the use of unique molecular identifiers for quantifying transcript ... See full document

24

Deep Sequencing Data Analysis

Deep Sequencing Data Analysis

... in sequencing to answer their experimental questions should prepare themselves to join a fast-moving field and embrace the tools being developed specifically for ... See full document

53

Cloud scale RNA sequencing differential expression analysis with Myrna

Cloud scale RNA sequencing differential expression analysis with Myrna

... Discussion Myrna is a computational pipeline for RNA-Seq differ- ential expression analysis using cloud computing. We used Myrna to analyze a large publicly available RNA- Seq dataset with over 1 billion reads. The ... See full document

11

Statistical Methods for Gene Differential Expression Analysis of RNA-Sequencing

Statistical Methods for Gene Differential Expression Analysis of RNA-Sequencing

... determine differential expression, and have traditionally be divided into gene-level methods and transcript-level ...comparative differential expression analysis, demonstrating that many differential ... See full document

140

Statistical Methods for Gene Differential Expression Analysis of RNA-Sequencing

Statistical Methods for Gene Differential Expression Analysis of RNA-Sequencing

... depicted in Supplementary Figure 2a,b was used to benchmark different parameters. In (a), three different normalization methods: transcript counts, size factor normalization from DESEq2, and transcript-per-million (TPM) ... See full document

22

Correlation in the Data University

Correlation in the Data University

... We need new ways to understand university management in the twenty-first century. Although the literature diagnosing the neoliberalisation of universities is invaluable in helping us comprehend the increasing ... See full document

23

Differential gene expression analysis tools exhibit substandard performance for long non coding RNA sequencing data

Differential gene expression analysis tools exhibit substandard performance for long non coding RNA sequencing data

... expression data only Results presented up to this point came from simulating, normalizing, and analyzing lncRNAs and mRNAs to- ...lncRNA data, using the same simulation ... See full document

16

XRay: Enhancing the Web s Transparency with Differential Correlation

XRay: Enhancing the Web s Transparency with Differential Correlation

... To evaluate XRay’s extensibility, we instantiated it on Gmail, YouTube, and Amazon. The engine, about 3,000 lines of Ruby, was first developed for Gmail. We then ex- tended it to YouTube and Amazon, without any changes ... See full document

17

Whole-exome sequencing in the differential diagnosis of primary adrenal insufficiency in children

Whole-exome sequencing in the differential diagnosis of primary adrenal insufficiency in children

... Adrenal insufficiency is a rare, but potentially fatal medical condition. In children, the cause is most commonly congenital and in recent years a growing number of causative gene mutations have been identified resulting ... See full document

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