Bioinformatics Monthly Workshop Series. Speaker: Fan Gao, Ph.D Bioinformatics Resource Office The Picower Institute for Learning and Memory

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1 Bioinformatics Monthly Workshop Series Speaker: Fan Gao, Ph.D Bioinformatics Resource Office The Picower Institute for Learning and Memory

2 Schedule for Fall, 2015 PILM Bioinformatics Web Server (09/21/2015) Regular RNA-Seq library preparation and data analysis (10/26/2015) Single-cell RNA-Seq library preparation and data analysis (11/20/2015) Statistical analysis using R-studio (12/14/2015)

4 Informatics approach to explore molecular mechanisms related to learning and memory!

6 PILM Bioinformatics Infrastructure End Users PILM Web Server PILM HPC System

7 PILM Bioinformatics Web Server (bioinfo5pilm46.mit.edu)

8 RNA-Seq library prep and differential expression analysis

9 RNA-Seq as a tool to profile the whole transcriptome Genome-wide unbiased; Higher sensitivity and dynamic range; Any organism that you can collect RNA; Alternative splicing; Novel transcribed regions; Gene fusion (genomic translocation); DNA recombination. Cost: ~$200-$400/sample (10M reads)

10 Experimental design for RNA-Seq Sample conditions; Sample replicates; Library type (total RNA, mrna or other); Sequencing type (paired-end vs. single-end); Read length (select the appropriate sequencer); Sequencing depth (multiplexing, pooling).

11 Key issues for experimental design Consider 3+ biological replicate samples; Minimize batch effects by preparing all sample libraries at once; Pool samples for sequencing (10M to 20M reads enough for differential expression analysis).

12 QC of total RNA Illumina TruSeq total RNA prep workflow Starting material: mg total RNA (check QC using the bioanalyzer at Biomicro center)

Illumina TruSeq total RNA prep workflow Key points: 1) Be patient when reading Illumina manual (140 pages); 2) Thaw all the reagents (except buffer) on ice; 3) Aliquot reagents in 1.

13 Illumina TruSeq total RNA prep workflow Key points: 1) Be patient when reading Illumina manual (140 pages); 2) Thaw all the reagents (except buffer) on ice; 3) Aliquot reagents in 1.5mL tubes recommended; 4) Mix magnetic beads well before use; 5) After RNA fragmentation, immediately proceed to the next step; 6) Be careful when using magnetic beads for isolation/wash (do not use vacuum).

14 BIOO stranded mrna prep workflow mrna CAPTURE Be patient, a lot of wash steps!

15 QC of amplified RNA-Seq library Key points: 1) Minimize primer dimers; 2) Quantity and size-distribution of amplicons. Good Bad

16 After QC, contact a sequencing core facility Gene quantification Novel splicing, gene fusion Price information from MIT Biomicro Center

17 Check MIT Biomicro center for details (

Illumina sequencing strategy https://en.wikipedia.

18 Illumina sequencing strategy

19 RNA-SEQ for DIFFERENTIAL EXPRESSION ANALYSIS Raw data (fastq ) from Illumina Sequencer (Biomicro center) Quality control, data preprocessing Read alignment to a reference genome Transcript Assembly Skipped from hands-on Gene quantification Expression normalization and differential analysis Result visualization

20 QC matrix from Biomicro Center Sample ID #Total Mapped% CDS UTR UTR5 UTR3 Intron flanking( +-3k) intergen ic exon/intr on 5/3utr exon/inte rgenic sense/an tisense rrna% D D % % % 5.001% % 6.694% 5.264% 5.080% % D D % % % 5.007% % 4.952% 5.374% 4.954% % D D % % % 5.074% % 5.629% 6.123% 5.646% % D D % % % 5.105% % 4.699% 5.407% 4.613% % D D % % % 4.975% % 4.801% 5.062% 4.521% % D D % % % 5.132% % 4.930% 5.660% 4.967% % Check Mapped%, exon/intron, exon/intergenic, rrna%.

21 Mac: open a terminal; PC: install and open a putty window. Hands-on practice Type the following command to access our bioinformatics server: ssh guest@bioinfopilm46.mit.edu Password:guest Commands to remember: tophat cuffquant cuffnorm cuffdiff For strand-specific data, add option --library-type fr-firststrand For library normalization, choose: -library-norm-method geometric fragment counts -library-norm-method classic-fpkm -library-norm-method quartile scaled via the median of the geometric means of no scaling applied to FPKM scaled to the upper quartile of fragments counts mapped to loci For user account registration, please me directly (fangao@mit.edu).

22 Sample Pipeline Mapping step: tophat -o tophat_out -p 4 --no-coverage-search -G directory/genes.gtf directory/bowtie2index/genome mydata.fastq Quantification step: cuffquant -o cuffquant_out -p 4 directory/genes.gtf tophat_out/accepted_hits.bam Normalization step: cuffnorm --use-sample-sheet -library-norm-method geometric -o cuffnorm_out -p 4 directory/genes.gtf sample_sheets.txt Differential analysis step: cuffdiff -o cuffdiff_out -p 4 directory/genes.gtf -L group1,group2 \ cuffquant_out1/abundances.cxb,cuffquant_out2/abundances.cxb \ cuffquant_out3/abundances.cxb,cuffquant_out4/abundances.cxb Use EXCEL to generate a tab-delimited file sample_sheets.txt sample_name cuffquant_out1/abundances.cxb cuffquant_out2/abundances.cxb cuffquant_out3/abundances.cxb cuffquant_out4/abundances.cxb group group1 group1 group2 group2

23 Dataset for practice RNA-Seq of affinity purified neurons: Excitatory pyramidal neurons; Parvalbumin-positive inhibitory neurons.

24 Sign-in to our RNA-Seq analysis server

25 Data Visualization R package: CummeRbund

SO YOU WANT TO DO A: RNA-SEQ EXPERIMENT MATT SETTLES, PHD UNIVERSITY OF CALIFORNIA, DAVIS

SO YOU WANT TO DO A: RNA-SEQ EXPERIMENT MATT SETTLES, PHD UNIVERSITY OF CALIFORNIA, DAVIS SETTLES@UCDAVIS.EDU Bioinformatics Core Genome Center UC Davis BIOINFORMATICS.UCDAVIS.EDU DISCLAIMER This talk/workshop