Showing 4 of total 4 results (show query)
bioc
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 scriptsbioc
CNVPanelizer:Reliable CNV detection in targeted sequencing applications
A method that allows for the use of a collection of non-matched normal tissue samples. Our approach uses a non-parametric bootstrap subsampling of the available reference samples to estimate the distribution of read counts from targeted sequencing. As inspired by random forest, this is combined with a procedure that subsamples the amplicons associated with each of the targeted genes. The obtained information allows us to reliably classify the copy number aberrations on the gene level.
Maintained by Thomas Wolf. Last updated 5 months ago.
classificationsequencingnormalizationcopynumbervariationcoverage
5.23 score 12 scriptsbioc
broadSeq:broadSeq : for streamlined exploration of RNA-seq data
This package helps user to do easily RNA-seq data analysis with multiple methods (usually which needs many different input formats). Here the user will provid the expression data as a SummarizedExperiment object and will get results from different methods. It will help user to quickly evaluate different methods.
Maintained by Rishi Das Roy. Last updated 5 months ago.
geneexpressiondifferentialexpressionrnaseqtranscriptomicssequencingcoveragegenesetenrichmentgo
4 stars 5.00 score 7 scriptsbioc
metaSeq:Meta-analysis of RNA-Seq count data in multiple studies
The probabilities by one-sided NOISeq are combined by Fisher's method or Stouffer's method
Maintained by Koki Tsuyuzaki. Last updated 5 months ago.
rnaseqdifferentialexpressionsequencingimmunooncology
3.30 score 2 scripts