Showing 13 of total 13 results (show query)
bioc
Maaslin2:"Multivariable Association Discovery in Population-scale Meta-omics Studies"
MaAsLin2 is comprehensive R package for efficiently determining multivariable association between clinical metadata and microbial meta'omic features. MaAsLin2 relies on general linear models to accommodate most modern epidemiological study designs, including cross-sectional and longitudinal, and offers a variety of data exploration, normalization, and transformation methods. MaAsLin2 is the next generation of MaAsLin.
Maintained by Lauren McIver. Last updated 5 months ago.
metagenomicssoftwaremicrobiomenormalizationbiobakerybioconductordifferential-abundance-analysisfalse-discovery-ratemultiple-covariatespublicrepeated-measurestools
133 stars 11.03 score 532 scripts 3 dependents
filzmoserp
chemometrics:Multivariate Statistical Analysis in Chemometrics
R companion to the book "Introduction to Multivariate Statistical Analysis in Chemometrics" written by K. Varmuza and P. Filzmoser (2009).
Maintained by Peter Filzmoser. Last updated 2 years ago.
4 stars 6.72 score 213 scripts 4 dependents
dgrun
FateID:Quantification of Fate Bias in Multipotent Progenitors
Application of 'FateID' allows computation and visualization of cell fate bias for multi-lineage single cell transcriptome data. Herman, J.S., Sagar, Grün D. (2018) <DOI:10.1038/nmeth.4662>.
Maintained by Dominic Grün. Last updated 3 years ago.
22 stars 6.50 score 48 scripts 1 dependentsbioc
CAGEr:Analysis of CAGE (Cap Analysis of Gene Expression) sequencing data for precise mapping of transcription start sites and promoterome mining
The _CAGEr_ package identifies transcription start sites (TSS) and their usage frequency from CAGE (Cap Analysis Gene Expression) sequencing data. It normalises raw CAGE tag count, clusters TSSs into tag clusters (TC) and aggregates them across multiple CAGE experiments to construct consensus clusters (CC) representing the promoterome. CAGEr provides functions to profile expression levels of these clusters by cumulative expression and rarefaction analysis, and outputs the plots in ggplot2 format for further facetting and customisation. After clustering, CAGEr performs analyses of promoter width and detects differential usage of TSSs (promoter shifting) between samples. CAGEr also exports its data as genome browser tracks, and as R objects for downsteam expression analysis by other Bioconductor packages such as DESeq2, CAGEfightR, or seqArchR.
Maintained by Charles Plessy. Last updated 5 months ago.
preprocessingsequencingnormalizationfunctionalgenomicstranscriptiongeneexpressionclusteringvisualization
6.12 score 73 scriptsbioc
benchdamic:Benchmark of differential abundance methods on microbiome data
Starting from a microbiome dataset (16S or WMS with absolute count values) it is possible to perform several analysis to assess the performances of many differential abundance detection methods. A basic and standardized version of the main differential abundance analysis methods is supplied but the user can also add his method to the benchmark. The analyses focus on 4 main aspects: i) the goodness of fit of each method's distributional assumptions on the observed count data, ii) the ability to control the false discovery rate, iii) the within and between method concordances, iv) the truthfulness of the findings if any apriori knowledge is given. Several graphical functions are available for result visualization.
Maintained by Matteo Calgaro. Last updated 4 months ago.
metagenomicsmicrobiomedifferentialexpressionmultiplecomparisonnormalizationpreprocessingsoftwarebenchmarkdifferential-abundance-methods
8 stars 5.78 score 8 scriptsdgrun
RaceID:Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data
Application of 'RaceID' allows inference of cell types and prediction of lineage trees by the 'StemID2' algorithm (Herman, J.S., Sagar, Grun D. (2018) <DOI:10.1038/nmeth.4662>). 'VarID2' is part of this package and allows quantification of biological gene expression noise at single-cell resolution (Rosales-Alvarez, R.E., Rettkowski, J., Herman, J.S., Dumbovic, G., Cabezas-Wallscheid, N., Grun, D. (2023) <DOI:10.1186/s13059-023-02974-1>).
Maintained by Dominic Grün. Last updated 4 months ago.
4.74 score 110 scriptsbioc
MMUPHin:Meta-analysis Methods with Uniform Pipeline for Heterogeneity in Microbiome Studies
MMUPHin is an R package for meta-analysis tasks of microbiome cohorts. It has function interfaces for: a) covariate-controlled batch- and cohort effect adjustment, b) meta-analysis differential abundance testing, c) meta-analysis unsupervised discrete structure (clustering) discovery, and d) meta-analysis unsupervised continuous structure discovery.
Maintained by Siyuan MA. Last updated 5 months ago.
metagenomicsmicrobiomebatcheffect
4.44 score 46 scriptsbioc
Macarron:Prioritization of potentially bioactive metabolic features from epidemiological and environmental metabolomics datasets
Macarron is a workflow for the prioritization of potentially bioactive metabolites from metabolomics experiments. Prioritization integrates strengths of evidences of bioactivity such as covariation with a known metabolite, abundance relative to a known metabolite and association with an environmental or phenotypic indicator of bioactivity. Broadly, the workflow consists of stratified clustering of metabolic spectral features which co-vary in abundance in a condition, transfer of functional annotations, estimation of relative abundance and differential abundance analysis to identify associations between features and phenotype/condition.
Maintained by Sagun Maharjan. Last updated 5 months ago.
sequencingmetabolomicscoveragefunctionalpredictionclustering
4.41 score 13 scriptsbioc
CINdex:Chromosome Instability Index
The CINdex package addresses important area of high-throughput genomic analysis. It allows the automated processing and analysis of the experimental DNA copy number data generated by Affymetrix SNP 6.0 arrays or similar high throughput technologies. It calculates the chromosome instability (CIN) index that allows to quantitatively characterize genome-wide DNA copy number alterations as a measure of chromosomal instability. This package calculates not only overall genomic instability, but also instability in terms of copy number gains and losses separately at the chromosome and cytoband level.
Maintained by Yuriy Gusev. Last updated 5 months ago.
softwarecopynumbervariationgenomicvariationacghmicroarraygeneticssequencing
4.08 score 2 scripts
vdakos
earlywarnings:Early Warning Signals for Critical Transitions in Time Series
The Early-Warning-Signals Toolbox provides methods for estimating statistical changes in time series that can be used for identifying nearby critical transitions.
Maintained by Vasilis Dakos. Last updated 2 years ago.
3.88 score 75 scripts
andreasdominik
som.nn:Topological k-NN Classifier Based on Self-Organising Maps
A topological version of k-NN: An abstract model is build as 2-dimensional self-organising map. Samples of unknown class are predicted by mapping them on the SOM and analysing class membership of neurons in the neighbourhood.
Maintained by Andreas Dominik. Last updated 12 months ago.
2.40 score 28 scripts
deisygysi
NetSci:Calculates Basic Network Measures Commonly Used in Network Medicine
Calculates network measures commonly used in Network Medicine. Measures such as the Largest Connected Component, the Relative Largest Connected Component, Proximity and Separation are calculated along with their statistical significance. Significance can be computed both using a degree-preserving randomization and non-degree preserving.
Maintained by Deisy Morselli Gysi. Last updated 6 months ago.
1.70 score 9 scripts
