Showing 12 of total 12 results (show query)
bioc
RankProd:Rank Product method for identifying differentially expressed genes with application in meta-analysis
Non-parametric method for identifying differentially expressed (up- or down- regulated) genes based on the estimated percentage of false predictions (pfp). The method can combine data sets from different origins (meta-analysis) to increase the power of the identification.
Maintained by Francesco Del Carratore. Last updated 5 months ago.
differentialexpressionstatisticalmethodsoftwareresearchfieldmetabolomicslipidomicsproteomicssystemsbiologygeneexpressionmicroarraygenesignaling
11.0 match 6.46 score 81 scripts 6 dependentsbioc
sRACIPE:Systems biology tool to simulate gene regulatory circuits
sRACIPE implements a randomization-based method for gene circuit modeling. It allows us to study the effect of both the gene expression noise and the parametric variation on any gene regulatory circuit (GRC) using only its topology, and simulates an ensemble of models with random kinetic parameters at multiple noise levels. Statistical analysis of the generated gene expressions reveals the basin of attraction and stability of various phenotypic states and their changes associated with intrinsic and extrinsic noises. sRACIPE provides a holistic picture to evaluate the effects of both the stochastic nature of cellular processes and the parametric variation.
Maintained by Mingyang Lu. Last updated 19 days ago.
researchfieldsystemsbiologymathematicalbiologygeneexpressiongeneregulationgenetargetcpp
11.0 match 4 stars 6.40 score 209 scriptsbioc
INDEED:Interactive Visualization of Integrated Differential Expression and Differential Network Analysis for Biomarker Candidate Selection Package
An R package for integrated differential expression and differential network analysis based on omic data for cancer biomarker discovery. Both correlation and partial correlation can be used to generate differential network to aid the traditional differential expression analysis to identify changes between biomolecules on both their expression and pairwise association levels. A detailed description of the methodology has been published in Methods journal (PMID: 27592383). An interactive visualization feature allows for the exploration and selection of candidate biomarkers.
Maintained by Ressom group. Last updated 5 months ago.
immunooncologysoftwareresearchfieldbiologicalquestionstatisticalmethoddifferentialexpressionmassspectrometrymetabolomics
11.0 match 4 stars 5.92 score 10 scriptsbioc
MetID:Network-based prioritization of putative metabolite IDs
This package uses an innovative network-based approach that will enhance our ability to determine the identities of significant ions detected by LC-MS.
Maintained by Zhenzhi Li. Last updated 5 months ago.
assaydomainbiologicalquestioninfrastructureresearchfieldstatisticalmethodtechnologyworkflowstepnetworkkegg
11.0 match 1 stars 5.74 score 110 scriptsbioc
PhosR:A set of methods and tools for comprehensive analysis of phosphoproteomics data
PhosR is a package for the comprenhensive analysis of phosphoproteomic data. There are two major components to PhosR: processing and downstream analysis. PhosR consists of various processing tools for phosphoproteomics data including filtering, imputation, normalisation, and functional analysis for inferring active kinases and signalling pathways.
Maintained by Taiyun Kim. Last updated 5 months ago.
softwareresearchfieldproteomics
11.0 match 4.71 score 51 scriptsbioc
scoup:Simulate Codons with Darwinian Selection Modelled as an OU Process
An elaborate molecular evolutionary framework that facilitates straightforward simulation of codon genetic sequences subjected to different degrees and/or patterns of Darwinian selection. The model is built upon the fitness landscape paradigm of Sewall Wright, as popularised by the mutation-selection model of Halpern and Bruno. This enables realistic evolutionary process of living organisms to be reproducible seamlessly. For example, an Ornstein-Uhlenbeck fitness update algorithm is incorporated herein. Consequently, otherwise complex biological processes, such as the effect of the interplay between genetic drift and fitness landscape fluctuations on the inference of diversifying selection, may now be investigated with minimal effort. Frequency-dependent and stochastic fitness landscape update techniques are available.
Maintained by Hassan Sadiq. Last updated 2 months ago.
alignmentclassificationcomparativegenomicsdataimportgeneticsmathematicalbiologyresearchfieldsequencingsequencematchingsoftwarestatisticalmethodworkflowstep
11.0 match 4.60 score 8 scriptsbioc
CIMICE:CIMICE-R: (Markov) Chain Method to Inferr Cancer Evolution
CIMICE is a tool in the field of tumor phylogenetics and its goal is to build a Markov Chain (called Cancer Progression Markov Chain, CPMC) in order to model tumor subtypes evolution. The input of CIMICE is a Mutational Matrix, so a boolean matrix representing altered genes in a collection of samples. These samples are assumed to be obtained with single-cell DNA analysis techniques and the tool is specifically written to use the peculiarities of this data for the CMPC construction.
Maintained by Nicolò Rossi. Last updated 5 months ago.
softwarebiologicalquestionnetworkinferenceresearchfieldphylogeneticsstatisticalmethodgraphandnetworktechnologysinglecell
11.0 match 4.30 score 5 scriptsbioc
pram:Pooling RNA-seq datasets for assembling transcript models
Publicly available RNA-seq data is routinely used for retrospective analysis to elucidate new biology. Novel transcript discovery enabled by large collections of RNA-seq datasets has emerged as one of such analysis. To increase the power of transcript discovery from large collections of RNA-seq datasets, we developed a new R package named Pooling RNA-seq and Assembling Models (PRAM), which builds transcript models in intergenic regions from pooled RNA-seq datasets. This package includes functions for defining intergenic regions, extracting and pooling related RNA-seq alignments, predicting, selected, and evaluating transcript models.
Maintained by Peng Liu. Last updated 5 months ago.
softwaretechnologysequencingrnaseqbiologicalquestiongenepredictiongenomeannotationresearchfieldtranscriptomicsbioconductor-packagegenome-annotationrna-seqtranscript-model
11.0 match 1 stars 4.18 score 3 scriptsbioc
SCANVIS:SCANVIS - a tool for SCoring, ANnotating and VISualizing splice junctions
SCANVIS is a set of annotation-dependent tools for analyzing splice junctions and their read support as predetermined by an alignment tool of choice (for example, STAR aligner). SCANVIS assesses each junction's relative read support (RRS) by relating to the context of local split reads aligning to annotated transcripts. SCANVIS also annotates each splice junction by indicating whether the junction is supported by annotation or not, and if not, what type of junction it is (e.g. exon skipping, alternative 5' or 3' events, Novel Exons). Unannotated junctions are also futher annotated by indicating whether it induces a frame shift or not. SCANVIS includes a visualization function to generate static sashimi-style plots depicting relative read support and number of split reads using arc thickness and arc heights, making it easy for users to spot well-supported junctions. These plots also clearly delineate unannotated junctions from annotated ones using designated color schemes, and users can also highlight splice junctions of choice. Variants and/or a read profile are also incoroporated into the plot if the user supplies variants in bed format and/or the BAM file. One further feature of the visualization function is that users can submit multiple samples of a certain disease or cohort to generate a single plot - this occurs via a "merge" function wherein junction details over multiple samples are merged to generate a single sashimi plot, which is useful when contrasting cohorots (eg. disease vs control).
Maintained by Phaedra Agius. Last updated 5 months ago.
softwareresearchfieldtranscriptomicsworkflowstepannotationvisualization
11.0 match 4.00 score 2 scriptsbioc
cbaf:Automated functions for comparing various omic data from cbioportal.org
This package contains functions that allow analysing and comparing omic data across various cancers/cancer subgroups easily. So far, it is compatible with RNA-seq, microRNA-seq, microarray and methylation datasets that are stored on cbioportal.org.
Maintained by Arman Shahrisa. Last updated 5 months ago.
softwareassaydomaindnamethylationgeneexpressiontranscriptionmicroarrayresearchfieldbiomedicalinformaticscomparativegenomicsepigeneticsgeneticstranscriptomics
11.0 match 3.78 score 1 scriptsbioc
iGC:An integrated analysis package of Gene expression and Copy number alteration
This package is intended to identify differentially expressed genes driven by Copy Number Alterations from samples with both gene expression and CNA data.
Maintained by Liang-Bo Wang. Last updated 5 months ago.
softwarebiological questiondifferentialexpressiongenomicvariationassaydomaincopynumbervariationgeneexpressionresearchfieldgeneticstechnologymicroarraysequencingworkflowstepmultiplecomparison
11.0 match 1 stars 3.78 score 1 scriptsbioc
MethTargetedNGS:Perform Methylation Analysis on Next Generation Sequencing Data
Perform step by step methylation analysis of Next Generation Sequencing data.
Maintained by Muhammad Ahmer Jamil. Last updated 5 months ago.
researchfieldgeneticssequencingalignmentsequencematchingdataimport
11.0 match 3.48 score 1 scripts