RNA-Seq analysis with Astrocyte Differential expression and transcriptome assembly

Transcription

1 RNA-Seq analysis with Astrocyte Differential expression and transcriptome assembly Beibei Chen Ph.D BICF 9/28/2016

2 Agenda Launch Workflows using Astrocyte BICF Workflows BICF RNA-seq Workflow Experimental Design Affecting Your Analysis Required Inputs Astrocyte demo Outputs Common Errors Visualization of Results using Vizapps Vizapp Demo

3 Agenda Launch Workflows using Astrocyte BICF Workflows BICF RNA-seq Workflow Experimental Design Affecting Your Analysis Required Inputs Astrocyte demo Outputs Common Errors Visualization of Results using Vizapps Vizapp Demo

4 Astrocyte BioHPC Workflow Platform Allows groups to give easy-access to their analysis pipelines via the web Standardized Workflows Simple Web Forms Online documentation & results visualization* Workflows run on HPC cluster without developer or user needing cluster knowledge astrocyte.biohpc.swmed.edu Slide contribution: David

5 Agenda Launch Workflows using Astrocyte BICF Workflows BICF RNA-seq Workflow Experimental Design Affecting Your Analysis Required Inputs Astrocyte demo Outputs Visualization of Results using Vizapps Common Errors Vizapp Demo

6 Browse workflows

7 BICF Workflows RNASeq Differential Expression Analysis Germline Variation Fastq to annotated VCF DNA RNA Somatic Variation Fastq to annotated VCF

8 Workflow for Genome Analysis

9 Annotation Sources Gene Annotation (Genes, Regulation and TFBS) dbsnp, ExAC clinvar, gwas catalog cosmic dbnsfp SIFT, Polyphen2, LRT, MutationTaster, MutationAssessor, FATHMM, VEST3, CADD, MetaLR, MetaSVM, PROVEAN, DANN, fathmm-mkl, fitcons PhyloP x 2, phastcons x 2, GERP++ and SiPhy Allele frequencies in 1000 Genomes Project phase 3 data, UK10K cohorts data, ExAC consortium data and the NHLBI Exome Sequencing Project ESP6500 data genesets (MSigDB) CIVIC BROAD Target

10 Agenda Launch Workflows using Astrocyte BICF Workflows BICF RNA-seq Workflow Experimental Design Affecting Your Analysis Required Inputs Astrocyte demo Outputs Visualization of Results using Vizapps Common Errors Vizapp Demo

11 Everything's connected slide by Dündar et al. (2015)

12 General RNA-seq Workflow

13 Experimental Design Affecting Your Analysis Whole transcriptome vs mrna Single end vs paired ends Paired-end produces more accurate alignments Paired-end allows for alternative transcript analysis Single-end is cheaper Number of Reads 10-50M is a good range Read Length Longer reads produce better alignments, min 50 bp paired or 100bp single

14 Experimental Design Affecting Your Analysis Number of Samples Your power to detect an effect depends on Effect size (difference between group means) Within group variance Sample size More Samples the better, min 3 per group Five samples sequenced to 20M reads each offer more power than 2 samples sequenced to 50M reads Stranded Can distinguish expression of overlapping genes

15 Strand-specific RNA-seq image from GATC Biotech

16 How to decide strand Reverse stranded Stranded

17 RNASeq Analysis Pipeline

18 Create a new project

19 Add data to your project

20 Add data to your project For NGS experiment, this is recommended.

21 Make your design file

22 Make your design file Use tab as delimiter Excel save as Text (tab delimited) If no SubjectID, use same number/character for all rows If no FqR2, leave them empty For all contents, no - For all contents, no spaces Columns names MUST be exactly the same as documented

23 Comparisons Comparisons are based on SampleGroup All pair-wise comparisons Could be identified by file name A_B.edgeR.txt Log fold change will be A/B If you want B/A, -1*logFC

24 Select your data files and submit SELECT YOUR FILES

25 Project is running

26 Timeline of the whole run

27 Download/visualize your results Vizapp need about 30s to start if there is no queue. You need to refresh the page. You can also choose individual files to download to your local computer

28 Agenda Launch Workflows using Astrocyte BICF Workflows BICF RNA-seq Workflow Experimental Design Affecting Your Analysis Required Inputs Astrocyte demo Outputs Common Errors Visualization of Results using Vizapps Vizapp Demo

29 Common errors and solutions Make sure the delimiter is tab Make sure the column name are the same as mentioned in documentation Make sure the file names match

30 Common errors and solutions Not all files are uploaded It s about the proxy setting Use auto-detect proxy

31 Agenda Launch Workflows using Astrocyte BICF Workflows BICF RNA-seq Workflow Experimental Design Affecting Your Analysis Required Inputs Astrocyte demo Outputs Common Errors Visualization of Results using Vizapps Vizapp Demo

32 Vizapp: QC general stat

33 Vizapp: QC MSD and PCA

34 Vizapp: Gene Compare

35 Uses edger results Filter gene list by different parameters Sort by different columns Data table downloading Vizapp: DEA

36 Vizapp: DEA heatmap Filter gene list by different parameters Choose different comparisons Support user define gene list (gene official symbol) Support pathway

37 Vizapp: alternative splicing

38 Vizapp: alternative splicing Different transcripts expression in sample groups

39 Vizapp: alternative splicing

40 Vizapp: QuSAGE

41 Introduction to BioHPC 10/5/2016 NL6.215 Please attend so you can get an account to try this out

42 Acknowledgement Brandi Cantarel David Trudgian BioHPC team BICF team

43 Agenda Launch Workflows using Astrocyte BICF Workflows BICF RNA-seq Workflow Experimental Design Affecting Your Analysis Required Inputs Astrocyte demo Outputs Visualization of Results using Vizapps Common Errors Vizapp Demo