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Here you will find useful websites and tools that can help you on the experimental design of your single-cell experiments.

Single-Cell Planning Check List

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Single Cell Genomics Library Structure

Collections of library structure and sequence of popular single cell genomic methods (mainly scRNA-seq). Most single cell sequencing methods are developed to be sequenced on the Illumina platforms. If you are not familiar with the general structure of Illumina sequencing libraries, check some general information about Illumina library structures and the nature of library preparation.

Image by Sergi Kabrera
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Five keys to writing a reproducible lab protocol.

More than 60% of respondents to a 2016 Nature survey said they had tried to repeat other scientists’ experiments and been unable to do so. Here are some tools for making methods reproducible.

SCOPIT, v1.1.4

This tool is for estimating the number of cells that must be sequenced to observe cell types in a single-cell sequencing experiment. It is intended for rough "napkin calculations", since it is uses information about type frequencies that an experimenter typically will not know. For single-cell DNA sequencing, or single-cell RNA sequencing.

Image by National Cancer Institute
Image by Markus Spiske

Different bioinformatic trainning courses. It includes single-cell. One will be  on Wed 18 Jan, Wed 25 Jan, Wed 1 Feb 2023

Multimodal Single-Cell Analysis

The goal of this book is to teach newcomers and advanced professionals alike, the best practices of single-cell sequencing analysis. This book will teach you the most common analysis steps ranging from preprocessing to visualization to statistical evaluation and beyond. A read through the entire book will enable you to analyze unimodal and multimodal single-cell sequencing data on your own. 

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LIANA enables the use of any combination of ligand-receptor methods and resources, and their consensus. 

Open Problems in Single-Cell Analysis

Benchmarking formalized challenges in single-cell analysis.  The goal is to provide an open source, community driven, extensible platform for continuously updated benchmarking of formalized tasks in single-cell analysis.

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