R packages
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_ROTS.png)
ROTS: Reproducibility-optimized test statistic for differential expression analysis
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_SIVS.png)
SIVS: Iterative feature selection to shrink down the feature space into a small, yet robust set
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_PASI.png)
PASI: Pathway Analysis for Sample-level Information utilizing pathway structures
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_ILoReg.png)
ILoReg: High-resolution cell population identification from single-cell RNA-seq data
![](https://elolab.utu.fi/wp-content/uploads/2022/08/logo_DCeN.png)
DCeN: Dynamically Co-expressed Neighborhoods for ranking genes in time-resolved gene expression profiling studies
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_EBSEA.png)
EBSEA: Exon Based Strategy for differential Expression Analysis of genes in RNA-seq studies
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_scShaper.png)
scShaper: Linear trajectory inference from single-cell RNA-seq data
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_RODEO.png)
RODEO: Robust Deconvolution of cell-type specific gene expression profiles from bulk expression data
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_Phosphonormalizer.png)
Phosphonormalizer: Compensation for normalization bias in phosphoproteomics
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_PowerExplorer.png)
PowerExplorer: Power and sample size estimation tool for RNA-seq and quantitative proteomics studies
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_PAL.png)
PAL: Pathway analysis of longitudinal transcriptomics and proteomics data
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_RepViz.png)
RepViz: Replicate oriented Visualization of chromatin and other genomic data
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_PECA.png)
PECA: Peptide-level Expression Change Averaging for differential expression analysis in proteomics
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_RolDE.png)
RolDE: Robust longitudinal differential expression for proteomics
![](http://elolab.utu.fi/wp-content/uploads/2022/10/logo_Totem.png)
Totem: A user-friendly tool for inferring tree-shaped trajectories from single cell data
Other software
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_glaDIAtor.png)
glaDIAtor: Untargeted analysis of data-independent acquisition mass spectrometry metaproteomics data
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_DIAtools.png)
DIAtools: Toolset for analyzing data-independent acquisition mass spectrometry data
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_LC.png)
LC: Likelihood Contrasts for binary classification of longitudinal data
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_SimPhospho.png)
SimPhospho: Simulation of phosphopeptide spectra for confident phosphosite assignment
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_PhosPiR.png)
PhosPiR: Automated pipeline for analyzing phosphoproteomics data
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_VarSCAT.png)
VarSCAT: Variant sequence context annotation toolkit
Webtools
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_COVID.png)
COVID-19 browser: Exploring COVID-19 specific gene signature across multiple bulk and single-cell datasets
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_AHT.png)
AHT risk calculator: Comparing the predicted risks of cardiovascular events and acute kidney injury between standard and intensive antihypertensive treatment
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_u-PA.png)
u-PA: Predicting biochemical recurrence of prostate cancer from longitudinal ultrasensitive-PSA data
![](http://elolab.utu.fi/wp-content/uploads/2022/08/logo_Weightloss.png)
Weightloss predictor: Predicting long-term weight changes from self-reported weight data