Posts

Tangram: Stitching the Cellular Map Back Together

The Tangram algorithm uses deep learning to align dissociated single-cell RNA-seq data onto spatial transcriptomics data, enabling …

The Blueprint for Causal Biology: CROP-seq Links Gene to Function at Scale

Datlinger et al. introduce CROP-seq, a method that captures both a CRISPR guide RNA and its resulting single-cell transcriptome, …

Perturb-Seq: Moving from 'What Is' to 'What If' in a Single Experiment

Perturb-seq combines pooled CRISPR screens with single-cell transcriptomics to systematically link genetic perturbations to their …

Busting the Myth of the scRNA-seq "Dropout"

This analysis elegantly demonstrates that the high number of zeros in droplet-based scRNA-seq is not a technical artifact but is …

Run EPIC

The EPIC toolkit was initially published here: Hu, L. Z., et al. “EPIC: software toolkit for elution profile-based inference of …

Statistical Modelling of AP-MS Data (SMAD)

This R package implements statistical modelling of affinity purification–mass spectrometry (AP-MS) data to compute confidence scores to …

Awsome affinity purification mass spectrometry (AP-MS)

A collection of resources regarding affinity purification mass spectrometry proteomics for the identification of protein-protein …

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