HTSFilter - Filter replicated high-throughput transcriptome sequencing data

This package implements a filtering procedure for replicated transcriptome sequencing data based on a global Jaccard similarity index in order to identify genes with low, constant levels of expression across one or more experimental conditions.

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sequencingrnaseqpreprocessingdifferentialexpressiongeneexpressionnormalizationimmunooncology

6.41 score 2 dependents 43 scripts 552 downloads

coseq - Co-Expression Analysis of Sequencing Data

Co-expression analysis for expression profiles arising from high-throughput sequencing data. Feature (e.g., gene) profiles are clustered using adapted transformations and mixture models or a K-means algorithm, and model selection criteria (to choose an appropriate number of clusters) are provided.

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geneexpressionrnaseqsequencingsoftwareimmunooncology

5.51 score 1 dependents 18 scripts 496 downloads

HTSCluster - Clustering High-Throughput Transcriptome Sequencing (HTS) Data

A Poisson mixture model is implemented to cluster genes from high- throughput transcriptome sequencing (RNA-seq) data. Parameter estimation is performed using either the EM or CEM algorithm, and the slope heuristics are used for model selection (i.e., to choose the number of clusters).

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5.32 score 2 dependents 7 scripts 410 downloads

padma - Individualized Multi-Omic Pathway Deviation Scores Using Multiple Factor Analysis

Use multiple factor analysis to calculate individualized pathway-centric scores of deviation with respect to the sampled population based on multi-omic assays (e.g., RNA-seq, copy number alterations, methylation, etc). Graphical and numerical outputs are provided to identify highly aberrant individuals for a particular pathway of interest, as well as the gene and omics drivers of aberrant multi-omic profiles.

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softwarestatisticalmethodprincipalcomponentgeneexpressionpathwaysrnaseqbiocartamethylseq

4.78 score 3 stars 6 scripts 382 downloads

ebdbNet - Empirical Bayes Estimation of Dynamic Bayesian Networks

Infer the adjacency matrix of a network from time course data using an empirical Bayes estimation procedure based on Dynamic Bayesian Networks.

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openblas

4.28 score 4 stars 19 scripts 262 downloads