Spliced Spliced Transcripts Transcripts STAR STAR Alignment - - PowerPoint PPT Presentation

Spliced Spliced Transcripts Transcripts Alignment & Alignment & Reconstruction Reconstruction

CSHL CSHL

STAR STAR

using high throughput using high throughput RNA-seq data RNA-seq data

Alexander Dobin Alexander Dobin, Philippe Batut, Sudipto Chakrabortty, Carrie Davis, , Philippe Batut, Sudipto Chakrabortty, Carrie Davis, Delphine Fagegaltier, Sonali Jha, Wei Lin, Delphine Fagegaltier, Sonali Jha, Wei Lin, Felix Schlesinger, Chenghai Xue, Christopher Zaleski, Felix Schlesinger, Chenghai Xue, Christopher Zaleski, Thomas Gingeras Thomas Gingeras

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STAR: spliced transcript STAR: spliced transcript alignment and reconstruction alignment and reconstruction

• 'Ab initio' splice junctions

– un-annotated, non-canonical, distal exons, chimeric ...

• Unique and multiple mappers
• Any read length, any number of SJs per read
• Any (reasonable) number of mismatches and indels
• Alignment scoring utilizing reads quality scores
• "Auto" trimming of poor quality ends
• poly-A tails detection
• Very Fast: human 75-mer reads: 60 Million read per hour
• Memory: RAM~9*(Genome length) bytes: 25GB for human
• II. Algorithm

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Splitting the reads Splitting the reads

• Split the read at poor quality bases (QS<10), 'N'
• Map each good piece separately
• Detect mismatches caused by poor SNR
• Avoid erroneous mapping caused by sequencing errors:

just 1 SNP can cause mis-mapping from paralog to paralog

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Suffix array based search Suffix array based search

For each good piece

• find maximum exactly mappable length (could be a multiple mapper)
• if a long portion of the good piece is still unmapped - repeat
• repeat this procedure backwards (from 3' to 5' of a good piece)

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• Typical short read aligner: does the read map entirely, i.e. at full length?
• What is the maximum mappable length?

– can detect many mismatches – can precisely "trim" poor quality tails – can detect splice junctions

• With suffix arrays we find maximum mappable length in no extra time

Maximum mappable length Maximum mappable length

Map Extend Map Map Map again

• II. Algorithm

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• Similar to local alignment scoring,

but penalties have probabilistic meaning

• Illumina quality score:
• +QS for matches; -QS for mismatches
• Penalty for gap opening:
• Total score
• A more elaborate iterative penalty system is being developed

– gap penalty is calculated from mapped gap length distribution – mismatch penalties vs QS scores are re-calibrated after mapping

• Choose the alignment(s) with highest score

Scoring with quality scores Scoring with quality scores

∑ ∑ ∑

= = =

− − + =

gap i gap mismatch i i match i i

P Q Q S

• II. Algorithm

( )

error

• base

10 P

log 10

• QS

⋅ =

( )

SJ gap

P

• P

10

log 10 ⋅

=

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Stitch and extend mapped pieces Stitch and extend mapped pieces

• Select anchors and alignment windows
• Collect all mapped pieces within an alignment window
• Consider all collinear transcripts of mapped pieces within a window
• Stitch all pieces together
• Extend the transcripts through the un-mapped 5' and 3' ends

Extend Extend Stitch

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Comparison with exhaustive search Comparison with exhaustive search

Exhaustively mapped Only in STAR Missed by STAR Exact 5,125,614 2,425 1MM 1,353,709 94 3,217 2MM 417,225 23 4,172 Multiple mappers by exhaustive search, <0.002% of all reads STAR maps 99.8% of all exhaustively mapped reads poor quality reads which did not have a single unique "anchor" Fly embryo 76mer RNA seq 1 Illumina lane: 8,930,945 total reads, good quality

• III. Application

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Reads mapped by STAR Reads mapped by STAR

• III. Application

77% overlap with exhaustive search 11% STAR >2MM or shorter length 0.2% STAR InDels 8.5% STAR splice junctions 1.5% multi-mappers 1.8% not mapped by STAR

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STAR alignments STAR alignments

Distribution of mapped lengths mean length = 72 Distribution of mismatches

poor quality tails spliced portions

• III. Application

~1,000,000 alignments found by STAR and not by exhaustive search

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Benchmarks Benchmarks

Single thread benchmarks 75-mer reads Bowtie (-v2 -k1) only reports non-spliced alignments with 0-2 MM, 1 or 2 alignments per read BLAT and STAR report >2MM and spliced alignments, and all the multiple alignments

BLAT Bowtie STAR Fly 13 19 91 Human 1 13 58

Million of reads aligned per hour

• III. Application

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percentile

Human total RNA Human total RNA

uniquely mapped reads mean mapped length (bases) 0-2 MM 51M 76 0-2MM & trim to 50 72M 50 STAR 106M 64.8

• III. Application

270M reads (76-mer)

• K562 human cell line
• Quality scores vs cycle

Poor quality tails!

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Splice junctions Splice junctions

Canonical GT/AG 3.6M (96%) Non-Canonical 150k (4%) All spliced reads: 3.75M Splice junctions with 3 or more reads per junction: 87k Annotated Canonical 78k (90%) Un-Annotated Canonical 6k (7%) Non- Canonical 2.8k (3%) ~0.5% of mapped reads are chimeric: inter-chromosome or inter-strand

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Summary Summary

• STAR: ab initio splice junction detection
• Maximum mappable length search with suffix arrays
• Alignment scoring uses quality scores of the reads
• Very fast: 60M/hour for 75-mer reads in human,

requires large amount of RAM (~25GB for human)