Changes between Version 2 and Version 3 of Courses/ComputationalMolecularBiologyResearch2016/P4

Timestamp:

2016-02-03T22:45:20+01:00 (9 years ago)

Author:

Pieter Neerincx

Comment:

--

Courses/ComputationalMolecularBiologyResearch2016/P4

@@ -7 +7 @@
 == Introduction ==
 
+The Genome Analysis Facility of the dept. Genetics of the UMCG provides researchers and clinicians with state-of-the-art-resources for modern molecular genetic studies. Single Cell RNA sequencing is a new tool that the facility wants to add to their portfolio. We have developed a novel strategy for Single Cell RNAseq based on the original Smart-Seq2 protocol developed by Picelli et al. This new strategy is called barcoded single cell RNAseq. The method is highly cost effective and has special features that solves the PCR bias of the original protocol.
 
 == Project 4 ==
 
+To analyze the obtained next generation sequencing data from this new method, a special analysis pipeline should be developed. This includes writing code to detect the cell specific barcodes in order quantify the gene expression per individual cell. 
+
+== Refs ==
+ * '''Full-length RNA-seq from single cells using Smart-seq2''' [[BR]] 
+   Simone Picelli,Omid R Faridani, Åsa K Björklund, Gösta Winberg, Sven Sagasser & Rickard Sandberg. [[BR]] 
+   ''Nature Protocols 9, 171–181 (2014) doi:10.1038/nprot.2014.006 Published online 02 January 2014''
+ * '''Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.'''  [[BR]] 
+   Evan Z. Macosko, Anindita Basu, Rahul Satija, James Nemesh, Karthik Shekhar, Melissa Goldman, Itay Tirosh, Allison R. Bialas, Nolan Kamitaki, Emily M. Martersteck, John J. Trombetta, David A. Weitz, Joshua R. Sanes, Alex K. Shalek, Aviv Regev and Steven A. !McCarroll [[BR]] 
+   ''Cell, Volume 161, Issue 5, 21 May 2015, Pages 1202–1214'' [[BR]] 
+   http://mccarrolllab.com/dropseq/