R packages
ROTS: Reproducibility-optimized test statistic for differential expression analysis
SIVS: Iterative feature selection to shrink down the feature space into a small, yet robust set
PASI: Pathway Analysis for Sample-level Information utilizing pathway structures
ILoReg: High-resolution cell population identification from single-cell RNA-seq data
DCeN: Dynamically Co-expressed Neighborhoods for ranking genes in time-resolved gene expression profiling studies
EBSEA: Exon Based Strategy for differential Expression Analysis of genes in RNA-seq studies
scShaper: Linear trajectory inference from single-cell RNA-seq data
RODEO: Robust Deconvolution of cell-type specific gene expression profiles from bulk expression data
Phosphonormalizer: Compensation for normalization bias in phosphoproteomics
PowerExplorer: Power and sample size estimation tool for RNA-seq and quantitative proteomics studies
PAL: Pathway analysis of longitudinal transcriptomics and proteomics data
RepViz: Replicate oriented Visualization of chromatin and other genomic data
PECA: Peptide-level Expression Change Averaging for differential expression analysis in proteomics
RolDE: Robust longitudinal differential expression for proteomics
Totem: A user-friendly tool for inferring tree-shaped trajectories from single cell data
Other software
glaDIAtor: Untargeted analysis of data-independent acquisition mass spectrometry metaproteomics data
DIAtools: Toolset for analyzing data-independent acquisition mass spectrometry data
LC: Likelihood Contrasts for binary classification of longitudinal data
SimPhospho: Simulation of phosphopeptide spectra for confident phosphosite assignment
PhosPiR: Automated pipeline for analyzing phosphoproteomics data
VarSCAT: Variant sequence context annotation toolkit
Webtools
COVID-19 browser: Exploring COVID-19 specific gene signature across multiple bulk and single-cell datasets
AHT risk calculator: Comparing the predicted risks of cardiovascular events and acute kidney injury between standard and intensive antihypertensive treatment
u-PA: Predicting biochemical recurrence of prostate cancer from longitudinal ultrasensitive-PSA data
Weightloss predictor: Predicting long-term weight changes from self-reported weight data