PPT-Pathway-based Single-Cell RNA-Seq Classification, Clustering, and Construction of Gene-Gene

Hailun Wang Pak Sham Tiejun Tong and Herbert Pang Rocky 2019 December 7 th Saturday 2 W hy scRNA Seq data Propose a pathwaybased analytic framework using Random Forests Identify discriminative functional pathways related to cellular heterogeneity . . Analysis. Team . McGill . University. and . Genome. . Quebec. Innovation Center. bioinformatics.service@mail.mcgill.ca. RNAseq. . analysis. 2. Module #: Title of Module. Why sequence RNA?. Functional studies. . Analysis. Team . McGill . University. and . Genome. . Quebec. Innovation Center. bioinformatics.service@mail.mcgill.ca. RNAseq. . analysis. 2. Module #: Title of Module. Why sequence RNA?. Functional studies. A (soon to be outdated) Tutorial. A Brief History of Sequencing and Gene Expression. Limitations of Sanger Sequencing. Low throughput. Inconsistent base quality. Expensive. Not quantitative. Frederick “. July 13, 2015. Goal of the . course. To be able to effectively design, and interpret genomic studies of gene expression.. We will focus on RNA-seq, but the class will provide a foothold into other functional genomics assays.. Sequence Differences in the. Human . Transcriptome. Mingyao. Li. , Isabel . X. Wang. , . Yun. Li, . Alan . Bruzel. , . Allison L. Richards. ,. Jonathan M. . Toung. , . Vivian G. . Cheung. Mahnaz. . Understanding the RNA-Seq evidence tracks on . the GEP UCSC Genome Browser. Wilson Leung. . 08/2016. Introduction to RNA-Seq. RNA-Seq: Massively parallel . RNA. . Seq. uencing using second or third generation sequencing technologies. UNIT . 5. Gene expression – A misnomer ?. In reality, gene expression can only be quantified by looking at protein products in the cell (. via. proteomic approaches).. T. he . term has been co-opted to describe differences in transcript (mRNA) levels.. data for Peptide and Protein Identification. ABRF 2013, Palm Springs, CA. 3/02-05/2013. iPRG2013 Study:. DESIGN. Study Goals. Primary. : Evaluate how many extra peptide sequence identifications can be determined using databases derived from RNA-. Seq. Sequenced reads. cells. sequencer. cDNA. ChIP. genome. read coverage. Alignment. Once sequenced the problem becomes . computational. Considerations and assumptions. High library complexity. #molecules in library >> #sequenced molecules. He. 2019-10-31. The Core of Biology Is All About One Cell. Forward Approaching. The Nobel Prize in Physiology or Medicine 2004. Dr. Richard Axel . Dr. Linda Buck. The odorant receptors are likely to belong to the superfamily of receptor proteins that transduce intracellular signals by coupling to GTP-binding proteins.. Jessica . Podnar. Outline. Overview of RNA-. Seq. methods. Tag-. Seq. SOP. Cost Breakdown. Submitting Samples. RNA-. Seq. Methods. RNA-. Seq. Methods. GSAF has primarily used . two methods for . RNA-. Genomics Lesson . 8_1. Hardison. 3/16/15. 1. transcriptomes. 3/16/15. 2. Transcriptome. . All the DNA that is transcribed in all the cells in an organism. Protein-coding genes. Both primary transcript and mature mRNA. Jessica . Podnar. Outline. RNA. Quality check of the RNA. Types of RNA used for library prep. Library Prep Methods used in the GSAF. Ligation Based. dUTP. method. Tag-. Seq. RNA, the Starting Material . John Kenny. Centre for Genomic Research, University of Liverpool.. CGR. CGR. Experimental Design, Bioinformatics.. Library production/sequence generation:. RNA-Seq, . SAGE, . Fragment, . Mate-pair, .