next-generation sequencing & analysis - Chagall

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FASTQ format @SEQ_ID GATTTGGGGTTCAAAGCAGTATCGATCAAATAGTAAATCC + !''*((((***+))%%%++)(%%%%).1***-+*''))**
Illumina sequence identifiers (CASAVA 1.8.2) @PC140529:266:C1THYACXX:6:2213:9313:32696 1:N:0:TAATGCGCGGCTCTGA @:::::: ::: Illumina CASAVA 1.8.2 User Guide PC140529 Instrument name 266 Run # on instrument C1THYACXX Flowcell ID 6 Lane # 2213 Tile # 9313 X coordinate of cluster 32696 Y coordinate of cluster 1 Read number N Y if the read is filtered 0 0 unless read idenIfied as control TAATGCGCGGCTCTGA Barcode sequence
Page 1 and 2: Next-‐gen. sequencing and an
Page 3 and 4: Two major (interconnected) theme
Page 5 and 6: Chain termination DeoxynucleoIdes
Page 7: Sanger sequencing - simple exam
Page 10 and 11: Sequencing by ligation (ABI Sol
Page 12 and 13: Metzker, Nat Rev Gene1cs, 11(1)
Page 14 and 15: Ion semiconductor sequencing (Io
Page 16 and 17: Single-‐molecule real-‐tim
Page 18 and 19: Cluster amplificaIon 1st cut FL
Page 20 and 21: Barcoding ì © Illumina
Page 22 and 23: Different chemistries yield diff
Page 24 and 25: (Pre-‐)Phasing a source of
Page 26 and 27: CLC Bio, Annual Survey (2012)
Page 28 and 29: NGS mostly applied toward basic
Page 32 and 33: Phred quality scores are linked
Page 34 and 35: Wikipedia Quality scores vary b
Page 36 and 37: Hash table Hash FuncIon Key 1
Page 38 and 39: Spaced-‐seed • Cut each po
Page 40 and 41: Ambiguous reads read reference
Page 42 and 43: 0-‐based vs. 1-‐based co
Page 44 and 45: Direct comparison of aligners d
Page 46 and 47: Simulated 2 mil . C. elegans
Page 48 and 49: cross_match & NovoAlign PE plac
Page 50 and 51: Repeated with real data from t
Page 52 and 53: Top Performing Aligners Alignmen
Page 54 and 55: Bioo Scien1fic Corp. Whole geno
Page 56 and 57: Read depth as a function of f
Page 58 and 59: Genotype Calling -‐ GATK
Page 60 and 61: GATK vs. Illumina
Page 62 and 63: ChIP sequencing
Page 64 and 65: Two fundamental types of peaks
Page 66 and 67: Different number of peaks ident
Page 68 and 69: Lister et al., Genome Research,
Page 70 and 71: Conversion yields up to four p
Page 72 and 73: Akalin et al., Genome Biology,
Page 74 and 75: Definitions ì RNA = class of
Page 76 and 77: RNA molecules 1. fragmentation of R
Page 78 and 79: Composition of RNA depends upon
Page 80 and 81:
Silica membrane enriches for RN
Page 82 and 83:
Zeugin JA & Hartley JL, Focus
Page 84 and 85:
Genebody coverage across degrade
Page 86 and 87:
Gene-‐expression comparison o
Page 88 and 89:
Capturing stem-‐loop mRNA 20
Page 90 and 91:
Bogdanova et al., Molecular Bio
Page 92 and 93:
Abundant transcript measurements
Page 94 and 95:
Fragmentation of oligo-‐dT p
Page 96 and 97:
Positional bias caused by choic
Page 98 and 99:
Quality assesment ì Levin et
Page 100 and 101:
Did you QC the data? no yes QC the
Page 102 and 103:
Dobin et al., Bioinforma1cs, 29
Page 104 and 105:
STAR vs Tophat ì ì ì STAR ma
Page 106 and 107:
Mar1n et al., Nature Reviews G
Page 108 and 109:
Methods of quantifying gene exp
Page 110 and 111:
Accurate quantification requires
Page 112 and 113:
More sophisticated normalization
Page 114 and 115:
Different normalization methods
Page 116 and 117:
DEGs in common for each of th
Page 118 and 119:
GAPDH isn’t much of a ‘hou
Page 120 and 121:
'The property of being one and
Page 122 and 123:
Script limitations 1) Linear exe
Page 124 and 125:
Maintain a bioinformatics journa
Page 126 and 127:
Empirical dialectical method p
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