Bioinformatics in next generation sequencing projectssandberg.cmb.ki.se/.../data/courses/bioinfocell/NGS... · Computational analyses is the bottleneck • Rapid improvement in sequencing

Bioinformatics in next generation sequencing projects

Rickard SandbergAssistant ProfessorDepartment of Cell and Molecular BiologyKarolinska Institutet

May 2012

Thursday, May 24, 12

Standard sequence library generation


Illumina Sequencing Technology


Illumina (Solexa) Sequencing


Illumina paired-end and index-read sequencing


Once sequenced the problembecomes computational

Computational analyses is the bottleneck• Rapid improvement in sequencing• Still need for customized analysis for most projects


Overview of computational analyses

Image analysisBase calling

Primary Analyses: Mapping(Assembly)

Data typespeci!c analyses(e.g. peak calling,

calculate expression)

Custom projectspeci!c analyses

ChIP-Seq peak calling

RNA-Seq expression levelsgenome sequence

assembled contig


Preliminary Analyses

Raw Image (TB)

Platform-specific analysis using the vendors programs

Sequences and Quality scoresText File (GB)

Real Time Analysis


Sequenced reads

>EAS54_6_R1_2_1_413_324CCCTTCTTGTCTTCAGCGTTTCTCC

Fasta file:

Fastq file:

SOLiD

csfasta file>1_39_146_F3T22100200202311030112002022222002021>1_39_194_F3T11022322003020303320012223122202221

SOLiD, QV file>1_39_146_F314 6 21 27 5 18 6 15 22 27 18 17 14 18 26 15 24 19 18 18 8 20 17 12 20 6 14 13 23 6 11 12 7 13 4 >1_39_194_F326 27 16 27 23 22 23 25 22 10 5 21 4 17 20 26 26 17 25 27 23 25 14 24 26 4 4 4 4 4 4 4 4 4 14

GAACTCTGCCTTTTTCAGTGATGAGGAAAGGAGTTCTCTCTGGTCCCCAG

aaab^_U_aa [U [ _Z ] a `WU_^X`GT^_ \ TM^ ^ \ ___ \ Z \ YQVVXUBBBB

Read identifier

Quality scores

@HWI - EAS269:1:120:1786:18#0/1

+HWI - EAS269:1:120:1786:18#0/1


Phred Quality Score, Q

Each base call has an estimate of the probability of being wrong (error probability, p)

Q = -10 * log10(p)

Phred Quality Score Probability of incorrect base call Base call accuracy10 1 in 10 90 %20 1 in 100 99 %30 1 in 1000 99.9 %40 1 in 10000 99.99 %50 1 in 100000 99.999 %


FastQ encodings

• Sanger FastQ: Phred score from 0-93 using the ASCII characters 33 – 126

• Solexa (+1.3 pipeline): Phred score from 0-62 using the ASCII characters 0-62

• Solexa (older pipelines): Solexa score using ASCII characters -5 to 62

SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS..................................................... ...............................IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII...................... ..........................XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~ | | | | | | 33 59 64 73 104 126

S - Sanger Phred+33, 41 values (0, 40) I - Illumina 1.3 Phred+64, 41 values (0, 40) X - Solexa Solexa+64, 68 values (-5, 62)


Fastq quality control (FastQC)

http://www.youtube.com/watch?v=bz93ReOv87YVideo tutorial:




Primary Analyses: MappingAssembly






assembled contig


Short Read AssemblyVelvet and SOAPdenovode novo genomic assembler specially designed for short read sequencing technologies

Nature 2009


Human Genome Assembly

UCSC Genome Browser


Mapping of readsTask: Map millions of short sequences (25-100 nt) onto a genome (3 000 Mbp ) or transcriptome

Computationally feasible

Mismatches (sequencing errors and SNPs)

Unique / Repetitive matches

Indels (Normal variation, CNVs)

Large rearrangements (translocations)

BLAST, BLAT tools not designed for these tasks


MAQ bowtie


Commonly used programs

Program Approach Comments

Bowtie / Bowtie2Burrow-Wheeler

Transformation (BWT) Illumina, (SOLiD), fast

MAQ Spaced Seed Indexing Illumina, (SOLiD), SNPs

BWA Burrow-Wheeler Transformation (BWT)

Illumina, (SOLiD), indels

NovoalignNeedleman-Wunch

AlignmentIllumina, indels, slower, free (single proc mode)

ZOOM Designed spaced seeds Illumina, fast, indels, not free

Mappers from Illumina (ELAND) and SOLiD (bioscope/mapreads)

http://en.wikipedia.org/wiki/List_of_sequence_alignment_software#Short-Read_Sequence_Alignment


Storing mapped Alignments

Formats for storing alignments should include:

genomic coordinates

mismatches, insertion, deletions etc.

quality information


Samtools

Sequence Alignment Map (SAM)

Generic Alignment format

Supports long and short reads

Human readable, !exible and compact

Emerging standard

h"p://samtools.sourceforge.net/

Li6H.*,6Handsaker6B.*,6Wysoker6A.,6Fennell6T.,6Ruan6J.,6Homer6N.,6Marth6G.,6Abecasis6G.,6Durbin6R.6and610006Genome6Project6Data6Processing6Subgroup6(2009)6The6Sequence6alignment/map6(SAM)6format6and6SAMtools.6BioinformaScs,625,62078W9.6[PMID:619505943]


SAM Example

16 chr Y 616000 255 22M731N28M* 0 0 ATTTCGACCATGATCATCGAACCTTCCCCTGGATCCACTTCCACGATCAC#9 ; -7 +2@4 : 2=20 - 14= : ><?< ; : BB? : 4<BB?ABBBBABCBBBBC=BB NM: i : 0XS: A:-

Bit field, where 16 means reverse strand

Start position

Alignment structure. Here: 22 aligned bases,then 731 bases intron, then 28 aligned bases

HWI - EAS269:1:114:1242:1582#0


CIGAR Format

M, match/mismatch

I, insertion

D, deletion

S, softclip

...

Ref: GCATTCAGATGCAGTACGC

Read: ccTCAG--GCAGTAgtg

Pos: 5

CIGAR: 2S4M3D6M3S


Samtools for SAM/BAM !les

Library and software package (C, Java)

Creating, sorting, indexing SAM & BAM

Visualizing alignments in command

SNP calling

Short indel detection

BAM (Binary representation of SAM) ~25% "le size reduction




Primary Analyses: MappingAssembly






assembled contig


Visualization

Integrated Genome Viewer (Broad Inst.)

Custom tracks at UCSC Genome Browser


Visualization


Integrated Genome Viewer

Imports many mentioned formats (SAM, BAM, BED etc)

Excellent for visualization of RNA-Sequencing or ChIP-sequencing data

Can also download/visualize data from public or private servers


UCSC Genome Browser

Recently introduced new formats for e#cient viewing of large data sets:

- BedGraph

- BigWig

Add as custom tracks (slower)


Peak characteristics di"er with signal


Peak characteristics di"er with signal

H3K4me3: Sharp promoter peaksH3K36me3: Broad transcription elongation signal


Important !le formats

Sequences: FastQ

Aligned reads: SAM/BAM

Genome annotations: Bed, G$

Coverage: Wig, (Tdf )

http://genome.ucsc.edu/FAQ/FAQformat.html


BED format

chrom6W6The6name6of6the6chromosome6(e.g.6chr3,6chrY,6chr2_random)6or6scaffold6(e.g.6scaffold10671).

chromStart6W6The6starSng6posiSon6of6the6feature6in6the6chromosome6or6scaffold.6The6first6base6in6a6chromosome6is6numbered60.

chromEnd6W6The6ending6posiSon6of6the6feature6in6the6chromosome6or6scaffold.6The6chromEnd6base6is6not6included6in6the6display6of6the6feature.6

For6example,6the6first61006bases6of6a6chromosome6are6defined6as6chromStart=0,6chromEnd=100,6and6span6the6bases6numbered60W99.

http://genome.ucsc.edu/FAQ/FAQformat.html

track name=pairedReads description="Clone Paired Reads" useScore=1chr22 1000 5000


BED continued

strand - Defines the strand - either '+' or '-'.thickStart - The starting position at which the feature is drawn thickly (for example, the start codon in gene displays).thickEnd - The ending position at which the feature is drawn thickly (for example, the stop codon in gene displays).itemRgb - An RGB value of the form R,G,B (e.g. 255,0,0). If the track line itemRgb attribute is set to "On", this RBG value will determine the display color of the data contained in this BED line. NOTE: It is recommended that a simple color scheme (eight colors or less) be used with this attribute to avoid overwhelming the color resources of the Genome Browser and your Internet browser.blockCount - The number of blocks (exons) in the BED line.blockSizes - A comma-separated list of the block sizes. The number of items in this list should correspond to blockCount.blockStarts - A comma-separated list of block starts. All of the blockStart positions should be calculated relative to chromStart. The number of items in this list should correspond to blockCount.

track name=pairedReads description="Clone Paired Reads" useScore=1chr22 2000 6000 cloneB 900 - 2000 6000 0 2 433,399, 0,3601


Variable step Fixed step

variableStep chrom=chr2300701 12.5300702 12.5300703 12.5300704 12.5300705 12.5is equivalent to:variableStep chrom=chr2 span=5300701 12.5

fixedStep chrom=chr3 start=400601 step=100112233

WIG format

Wiggle format (WIG) allows the display of continuous-valued data in a track format


Data Repositories

Short Read Archive (fastq) [discontinued!]http://www.ncbi.nlm.nih.gov/sraEuropean Nucleotide Archive

Gene Expression Omnibus (bed, wig, fastq)http://www.ncbi.nlm.nih.gov/geo/


SEQAnswers, an active forum for discussions on next-generation sequencing methods and bioinformatics

http://seqanswers.com/Thursday, May 24, 12


Documents

Bioinformatics in next generation sequencing projectssandberg.cmb.ki.se/.../data/courses/bioinfocell/NGS... · Computational analyses is the bottleneck • Rapid improvement in sequencing