NikolayOskolkov

ClusteringHighDimensions

Here I demonstrate how to automatically detect the number of clusters in scRNAseq data

DeepLearningAncientDNA

Here I show how to use Convolutional Neural Networks (CNNs) for Ancient DNA analysis

DeepLearningDataIntegration

Here I show how to use Deep Learning for biological and biomedical Data Integration.

DeepLearningMicrobiome

DeepLearningSingleCellBiology

Here I show how to use Deep Autoencoders for single cell RNA sequencing data analysis

HowUMAPWorks

Here I explain the math behind UMAP and show how to program it from scratch in Python

LSTMNeanderthalDNA

Implementation of LSTM for detecting regions of Neanderthal introgression in modern human genomes

NormalizeSingleCell

Comparison of single cell normalization strategies

tSNE_vs_UMAP_GlobalStructure

Here we address the global structure preservation by tSNE and UMAP

UMAPDataIntegration

Graph based data integration with UMAP

NikolayOskolkov/tSNE_vs_UMAP_GlobalStructure

Here we address the global structure preservation by tSNE and UMAP

NikolayOskolkov/HowUMAPWorks

Here I explain the math behind UMAP and show how to program it from scratch in Python

NikolayOskolkov/DeepLearningDataIntegration

Here I show how to use Deep Learning for biological and biomedical Data Integration.

NikolayOskolkov/NormalizeSingleCell

Comparison of single cell normalization strategies

NikolayOskolkov/UMAPDataIntegration

Graph based data integration with UMAP

NikolayOskolkov/DeepLearningMicrobiome

NikolayOskolkov/LSTMNeanderthalDNA

Implementation of LSTM for detecting regions of Neanderthal introgression in modern human genomes

NikolayOskolkov/UnivariteVsMultivariteModels

Here we compare a few multivarite and univarite feature selection models

NikolayOskolkov/aMeta

NikolayOskolkov/DeepLearningNeanderthalIntrogression

Here I deposite input files and Jupyter notebooks on detecting Neanderthal introgression analysis

NikolayOskolkov/GenomicsNewClothes

Here I discuss common pitfalls in Genetics research due to the high-dimensional nature of genetic variation data that suffers from the Curse of Dimensionality

NikolayOskolkov/IntegrativeOmicsWorkflow

Here we provide a primer-workflow for biological data integration analysis.

NikolayOskolkov/LMMFromScratch

Deriving and coding Linear Mixed Model (LMM) from scratch

NikolayOskolkov/Physalia_EnvMetagenomics_2024

NikolayOskolkov/HowToBatchCorrectSingleCell

Here I explain batch-effects correction techniques for scRNAseq experiments

NikolayOskolkov/HowToInitializeUMAPtSNE

Checking how tSNE and UMAP depend on different initialization scenarios

NikolayOskolkov/OsloBioinfoWeek2022

NikolayOskolkov/SBW2022

This is a teaching material for scRNAseq workshop within SBW2022

NikolayOskolkov/tSNELargePerplexityLimit

Here we investigate the degradation of tSNE to PCA / MDS at large perplexity values

NikolayOskolkov/UMAP_VarianceExplained

Here I show a simple way to estimate data variance explained by UMAP and tSNE components

NikolayOskolkov/WhyPCALooksTriangular

Here I provide some insights on the peculiar triangular shape of PCA plots that can often be found in Life Science projects

NikolayOskolkov/COVID19

Corona infection related computations

NikolayOskolkov/HowLinearMixedModelWorks

NikolayOskolkov/REML

Deriving and coding Linear Mixed Model in Restricted Maximum Likelihood (REML) approach

NikolayOskolkov/Xgboost-for-scRNAseq

A workflow for applying tree-based machine learning algorithms such as Random forest and Xgboost to scRNAseq data

NikolayOskolkov/AMDirT

Check validity of AncientMetagenomeDir dataset

NikolayOskolkov/AncientMetagenomeDir

Repository containing lists of all published ancient metagenome samples (and related)

NikolayOskolkov/Iceman_fungi

Here we provide scripts used for analysis of fungal community in Iceman metagenomic data

NikolayOskolkov/Physalia_EnvMetagenomics_2023

Environmental metagenomics, Spring 2023, Physalia Courses

NikolayOskolkov/PlagueRandomSample