BCOOL-Trans Accurate and variant-preserving correction for RNA-seq - - PowerPoint PPT Presentation

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Jul 09, 2023 270 likes •542 views

BCOOL-Trans Accurate and variant-preserving correction for RNA-seq Camille Marchet and Antoine Limasset Univ. Lille, CNRS, Inria, UMR 9189 - CRIStAL SeqBio 2018 Rouen 1 / 25 Introduction Tools to study RNA-seq: Most assembly/quantification

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BCOOL-Trans Accurate and variant-preserving correction for RNA-seq

Camille Marchet and Antoine Limasset

Univ. Lille, CNRS, Inria, UMR 9189 - CRIStAL

SeqBio 2018 Rouen

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Introduction

Tools to study RNA-seq: Most assembly/quantification and some variant calling methods are k-mer based Correctors are mostly k-mer based Rely on "solidity"

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Introduction: RNA-seq correction challenges

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Introduction: RNA-seq correction challenges

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Motivations

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Motivations

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Motivations

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Motivations

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State of the art: k-mer spectrum

Main idea

Find abundant/trusted kmers in dataset Replace untrusted kmers in reads by trusted ones

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State of the art: RNA correction

Strategy included in assemblers/KISSPLICE[Sacomoto et al. 2012]/Rcorrector[Song et al. 2015]:

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BCOOL [Limasset et al. 2018]: main concepts

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BCOOL: improvements in read correction

Map reads on unitigs: better handle close errors (distant of less than k) Use large k: handle repeated region Results after correction of genomic reads: *Correction ratio = by how much the number of errors was divided

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BCOOL-Trans enhancements

1- Work with all k-mers Graph construction scale to dozen billions kmers Keep rare k-mer Easier to find overlaps

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BCOOL-Trans enhancements

2- Work with large k-mers and remove only tips

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BCOOL-Trans enhancements

2- Work with large k-mers and remove only tips

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BCOOL-Trans enhancements

3- Advanced tip removal

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BCOOL-Trans enhancements

4- Mapping strategy

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BCOOL-Trans enhancements

4- Mapping strategy

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BCOOL-Trans enhancements

5- Paired-end reads merging

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Correction quality proof of concept

Data

Mouse transcriptome 100M reads with FluxSimulator[Griebel et al. 2012] 1% error rate

Mock BCOOL-Trans

"cleaned" graph + BCOOL’s mapping module BCOOL-TransN means: all true k-mers + erroneous k-mers of occurence > N in cleaned graph

Corrector Recall Precision Ratio correction* % Erroneous reads BFC 58.76 96.16 2.34 30.18 Rcorrector 93.37 99.80 14.68 4.34 BCOOL-Trans5 92.75 97.75 10.64 5.58 BCOOL-Trans7 94.20 98.41 13.7 4.17

*Correction ratio = by how much the number of errors was divided 20 / 25

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Results: paired-end merging

Data

Mouse transcriptome Paired-end reads (2x150 nt) 4,422,720 reads with Flux Simulator Results: Percentage of merged pairs: 97.3454 Not trivial pair-mapping rate: 76%

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Discussion: expected outcomes

After Bcool-Trans correction: Speedup Scaling Less errors in data More signal to detect rare and significant Longer "merged-reads": more context for assembly, variant calling...

Other applications

Meta-genomic data Meta-transcriptomic data

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Future work: development

Graph construction

Relative abundance tipping, adaptative threshold (cf Rcorrector) Distance related tipping (cf RNASpades [Bushmanova et al. 2018 BiorXiv])

Graph alignment

Use partial read mapping Multiple starting anchors

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Future work: experiments

Benchmark versus main SOTA methods (Rcorrector, BayesHammer [Nikolenko et al. 2013], BFC [Li 2015] . . . ) Assess impacts on assembly, variant calling, quantification, differential expression Assess impact (in particular merged reads) on hybrid long read correction

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Conclusion

BCOOL-Trans is a work-in-progress RNA-seq corrector. It is scalable, and it uses new strategies to well-preserve variants.

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