A complete rewrite of split-monitor-workspaces that attempts to fix the issues I experienced with it.

Allows you to add one or two additional borders to your windows. The borders added are static.

Example Config:

plugin 
    borders-plus-plus 
        add_borders = 1 # 0 - 9

        # you can add up to 9 borders
        col.border_1 = rgb(ffffff)
        col.border_2 = rgb(2222ff)

        # -1 means "default" as in the one defined in general:border_size
        border_size_1 = 10
        border_size_2 = -1

        # makes outer edges match rounding of the parent. Turn on / off to better understand. Default = on.
        natural_rounding = yes
    

A qml style provider for hypr* qt apps. Launch a qt/qmp app with QT_QUICK_CONTROLS_STYLE=org.hyprland.style.

Originally meant for csgo / cs2, but can work with any app, really.

csgo-vulkan-fix is a way to force apps to a fake resolution without them realizing it.

If you want to play CS2, you're locked to your native res. Other resolutions (especially not 16:9) are wonky.

With this plugin, you aren't anymore.

A tiny qt6/qml application to display information about the running system, or copy diagnostics data, without the terminal.

An application to enable a blue-light filter on Hyprland. It does not have a timer on its own, but has to be controlled using Hyprland's hyprctl.

A clone of xwinwrap for Hyprland. This lets you use any program as your desktop background.

This neat, useless plugin adds trails behind windows. It even lets you change the colors.

This is the VM used by Pharo.

Deploy your testing VM in a couple of seconds.

Based on a large miRNA dilution study, this package provides tools to read in the raw amplification data and use these data to assess the performance of methods that estimate expression from the amplification curves.

FHCRC Nelson Lab mpedbarray Annotation Data (mpedbarray) assembled using data from public repositories.

This package provides a package containing an environment representing the MG_U74Bv2.CDF file.

The MsQuality provides functionality to calculate quality metrics for mass spectrometry-derived, spectral data at the per-sample level. MsQuality relies on the mzQC framework of quality metrics defined by the Human Proteom Organization-Proteomics Standards Initiative (HUPO-PSI). These metrics quantify the quality of spectral raw files using a controlled vocabulary. The package is especially addressed towards users that acquire mass spectrometry data on a large scale (e.g. data sets from clinical settings consisting of several thousands of samples). The MsQuality package allows to calculate low-level quality metrics that require minimum information on mass spectrometry data: retention time, m/z values, and associated intensities. MsQuality relies on the Spectra package, or alternatively the MsExperiment package, and its infrastructure to store spectral data.

Identification of diferentially methylated regions (DMRs) in predefined regions (promoters, CpG islands...) from the human genome using Illumina's 450K or EPIC microarray data. Provides methods to rank CpG probes based on linear models and includes plotting functions.

The MSstatsLOBD package allows calculation and visualization of limit of blac (LOB) and limit of detection (LOD). We define the LOB as the highest apparent concentration of a peptide expected when replicates of a blank sample containing no peptides are measured. The LOD is defined as the measured concentration value for which the probability of falsely claiming the absence of a peptide in the sample is 0.05, given a probability 0.05 of falsely claiming its presence. These functionalities were previously a part of the MSstats package. The methodology is described in Galitzine (2018) <doi:10.1074/mcp.RA117.000322>.

Example data for MEDIPS and QSEA packages, consisting of chromosome 22 MeDIP and control/Input sample data. Additionally, the package contains MeDIP seq data from 3 NSCLC samples and adjacent normal tissue (chr 20-22). All data has been aligned to human genome hg19.

This package provides an interface to several normalization and statistical testing packages for RNA-Seq gene expression data. Additionally, it creates several diagnostic plots, performs meta-analysis by combinining the results of several statistical tests and reports the results in an interactive way.

Affymetrix Affymetrix Mu19KsubA Array annotation data (chip mu19ksuba) assembled using data from public repositories.

This package provides a set of tools for network analysis using mass spectrometry-based proteomics data and network databases. The package takes as input the output of MSstats differential abundance analysis and provides functions to perform enrichment analysis and visualization in the context of prior knowledge from past literature. Notably, this package integrates with INDRA, which is a database of biological networks extracted from the literature using text mining techniques.

MaAsLin 3 refines and extends generalized multivariate linear models for meta-omicron association discovery. It finds abundance and prevalence associations between microbiome meta-omics features and complex metadata in population-scale epidemiological studies. The software includes multiple analysis methods (including support for multiple covariates, repeated measures, and ordered predictors), filtering, normalization, and transform options to customize analysis for your specific study.

"Methylation-Aware Genotype Association in R" (MAGAR) computes methQTL from DNA methylation and genotyping data from matched samples. MAGAR uses a linear modeling stragety to call CpGs/SNPs that are methQTLs. MAGAR accounts for the local correlation structure of CpGs.

The Molecular Degree of Perturbation webtool quantifies the heterogeneity of samples. It takes a data.frame of omic data that contains at least two classes (control and test) and assigns a score to all samples based on how perturbed they are compared to the controls. It is based on the Molecular Distance to Health (Pankla et al. 2009), and expands on this algorithm by adding the options to calculate the z-score using the modified z-score (using median absolute deviation), change the z-score zeroing threshold, and look at genes that are most perturbed in the test versus control classes.