<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>isglobal-exposomehub.r-universe.dev</title><link>https://isglobal-exposomehub.r-universe.dev</link><description>Recent package updates in isglobal-exposomehub</description><generator>R-universe</generator><image><url>https://github.com/isglobal-exposomehub.png</url><title>R packages by isglobal-exposomehub</title><link>https://isglobal-exposomehub.r-universe.dev</link></image><lastBuildDate>Mon, 08 Jun 2026 16:31:51 GMT</lastBuildDate><item><title>[isglobal-exposomehub] BigDataStatMeth 2.0.2</title><author>dolors.pelegri@isglobal.org (Dolors Pelegri-Siso)</author><description>A framework for 'scalable' statistical computing on large
on-disk matrices stored in 'HDF5' files. It provides efficient
block-wise implementations of core linear-algebra operations
(matrix multiplication, SVD, PCA, QR decomposition, and
canonical correlation analysis) written in C++ and R. These
building blocks are designed not only for direct use, but also
as foundational components for developing new statistical
methods that must operate on datasets too large to fit in
memory. The package supports data provided either as 'HDF5'
files or standard R objects, and is intended for
high-dimensional applications such as 'omics' and
precision-medicine research.</description><link>https://github.com/r-universe/isglobal-exposomehub/actions/runs/27164936474</link><pubDate>Mon, 08 Jun 2026 16:31:51 GMT</pubDate><r:package>BigDataStatMeth</r:package><r:version>2.0.2</r:version><r:status>success</r:status><r:repository>https://isglobal-exposomehub.r-universe.dev</r:repository><r:upstream>https://github.com/cran/BigDataStatMeth</r:upstream><r:article><r:source>BigDataStatMeth.Rmd</r:source><r:filename>BigDataStatMeth.html</r:filename><r:title>Working with HDF5-Backed Matrices in BigDataStatMeth</r:title><r:created>2025-11-29 13:30:28</r:created><r:modified>2026-06-08 16:31:51</r:modified></r:article></item><item><title>[bioc] epimutacions 1.17.0</title><author>dolors.pelegri@isglobal.org (Dolors Pelegri-Siso)</author><description>The package includes some statistical outlier detection
methods for epimutations detection in DNA methylation data. The
methods included in the package are MANOVA, Multivariate linear
models, isolation forest, robust mahalanobis distance, quantile
and beta. The methods compare a case sample with a suspected
disease against a reference panel (composed of healthy
individuals) to identify epimutations in the given case sample.
It also contains functions to annotate and visualize the
identified epimutations.</description><link>https://github.com/r-universe/bioc/actions/runs/26676640993</link><pubDate>Tue, 28 Apr 2026 12:58:12 GMT</pubDate><r:package>epimutacions</r:package><r:version>1.17.0</r:version><r:status>failure</r:status><r:repository>https://bioc.r-universe.dev</r:repository><r:upstream>https://github.com/bioc/epimutacions</r:upstream></item><item><title>[bioc] methylclock 1.19.0</title><author>dolors.pelegri@isglobal.org (Dolors Pelegri-Siso)</author><description>This package allows to estimate chronological and
gestational DNA methylation (DNAm) age as well as biological
age using different methylation clocks. Chronological DNAm age
(in years) : Horvath's clock, Hannum's clock, BNN, Horvath's
skin+blood clock, PedBE clock and Wu's clock. Gestational DNAm
age : Knight's clock, Bohlin's clock, Mayne's clock and Lee's
clocks. Biological DNAm clocks : Levine's clock and Telomere
Length's clock.</description><link>https://github.com/r-universe/bioc/actions/runs/26675867982</link><pubDate>Tue, 28 Apr 2026 12:56:26 GMT</pubDate><r:package>methylclock</r:package><r:version>1.19.0</r:version><r:status>success</r:status><r:repository>https://bioc.r-universe.dev</r:repository><r:upstream>https://github.com/bioc/methylclock</r:upstream><r:article><r:source>methylclock.Rmd</r:source><r:filename>methylclock.html</r:filename><r:title>Chronological and gestational DNAm age estimation using different methylation-based clocks</r:title><r:created>2019-03-15 08:20:49</r:created><r:modified>2022-07-11 11:37:12</r:modified></r:article></item><item><title>[bioc] scoreInvHap 1.35.0</title><author>dolors.pelegri@isglobal.org (Dolors Pelegri-Siso)</author><description>scoreInvHap can get the samples' inversion status of known
inversions. scoreInvHap uses SNP data as input and requires the
following information about the inversion: genotype frequencies
in the different haplotypes, R2 between the region SNPs and
inversion status and heterozygote genotypes in the reference.
The package include this data for 21 inversions.</description><link>https://github.com/r-universe/bioc/actions/runs/26677153073</link><pubDate>Tue, 28 Apr 2026 12:45:54 GMT</pubDate><r:package>scoreInvHap</r:package><r:version>1.35.0</r:version><r:status>success</r:status><r:repository>https://bioc.r-universe.dev</r:repository><r:upstream>https://github.com/bioc/scoreInvHap</r:upstream><r:article><r:source>scoreInvHap.Rmd</r:source><r:filename>scoreInvHap.html</r:filename><r:title>Inversion genotyping with scoreInvHap</r:title><r:created>2017-06-22 10:22:00</r:created><r:modified>2019-06-07 09:00:18</r:modified></r:article></item><item><title>[bioc] tweeDEseq 1.59.0</title><author>dolors.pelegri@isglobal.org (Dolors Pelegri-Siso)</author><description>Differential expression analysis of RNA-seq using the
Poisson-Tweedie (PT) family of distributions. PT distributions
are described by a mean, a dispersion and a shape parameter and
include Poisson and NB distributions, among others, as
particular cases. An important feature of this family is that,
while the Negative Binomial (NB) distribution only allows a
quadratic mean-variance relationship, the PT distributions
generalizes this relationship to any orde.</description><link>https://github.com/r-universe/bioc/actions/runs/28051512129</link><pubDate>Tue, 28 Apr 2026 12:36:03 GMT</pubDate><r:package>tweeDEseq</r:package><r:version>1.59.0</r:version><r:status>success</r:status><r:repository>https://bioc.r-universe.dev</r:repository><r:upstream>https://github.com/bioc/tweeDEseq</r:upstream><r:article><r:source>tweeDEseq.Rnw</r:source><r:filename>tweeDEseq.pdf</r:filename><r:title>tweeDEseq: analysis of RNA-seq data using the Poisson-Tweedie family of distributions</r:title><r:created>2013-11-01 20:22:22</r:created><r:modified>2023-07-05 15:45:15</r:modified></r:article></item><item><title>[isglobal-brge] SNPassoc 2.3.1</title><author>dolors.pelegri@isglobal.org (Dolors Pelegri)</author><description>Functions to perform most of the common analysis in genome
association studies are implemented. These analyses include
descriptive statistics and exploratory analysis of missing
values, calculation of Hardy-Weinberg equilibrium, analysis of
association based on generalized linear models (either for
quantitative or binary traits), and analysis of multiple SNPs
(haplotype and epistasis analysis). Permutation test and
related tests (sum statistic and truncated product) are also
implemented. Max-statistic and genetic risk-allele score exact
distributions are also possible to be estimated. The methods
are described in Gonzalez JR et al., 2007 &lt;doi:
10.1093/bioinformatics/btm025&gt;. This version includes internal
copies of functions from the archived 'haplo.stats' package to
maintain functionality.</description><link>https://github.com/r-universe/isglobal-brge/actions/runs/28657303595</link><pubDate>Mon, 13 Apr 2026 08:38:45 GMT</pubDate><r:package>SNPassoc</r:package><r:version>2.3.1</r:version><r:status>success</r:status><r:repository>https://isglobal-brge.r-universe.dev</r:repository><r:upstream>https://github.com/isglobal-brge/snpassoc</r:upstream><r:article><r:source>SNPassoc.Rmd</r:source><r:filename>SNPassoc.html</r:filename><r:title>SNPassoc: an R package to perform whole genome association studies</r:title><r:created>2017-08-31 12:55:40</r:created><r:modified>2026-03-24 07:15:20</r:modified></r:article></item></channel></rss>