Multithreaded variant calling in elPrep 5

Herzeel, Charlotte; Costanza, Pascal; Decap, Dries; Fostier, Jan; Wuyts, Roel; Verachtert, Wilfried

doi:10.1371/journal.pone.0244471

Cited by 12 publications

(5 citation statements)

References 15 publications

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“…Paired-end short reads from each pool or individual were first filtered and trimmed by fastp version 0.20.0 63 with the argument “-q 30 -u 30 -n 10 -l 20 -t 1 -T 1”. The filtered reads were then mapped to the P. clarkii genome assembly 64 by BWA-MEM2 2.0pre2, 66 sorted by SAMtools version 1.10, 60 and then processed with elPrep version 5.1.3, 65 which removed duplicate reads or reads with mapping quality less than 20.…”

Section: Methodsmentioning

confidence: 99%

Genomic adaptive potential to cold environments in the invasive red swamp crayfish

et al. 2023

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Section: Methodsmentioning

confidence: 99%

Genomic adaptive potential to cold environments in the invasive red swamp crayfish

et al. 2023

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“…Reads were aligned to the human reference genome (hg19) with BWA-mem2 (2.2.1). Sorting and duplicate marking were performed using elPrep (5.0.2) [ 26 ] and SAMtools (1.13) [ 27 ] for the indexing of the bam files. To simplify the use of our method, read filtering was integrated in the proposed DeltaMSI script.…”

Section: Methodsmentioning

confidence: 99%

DeltaMSI: artificial intelligence-based modeling of microsatellite instability scoring on next-generation sequencing data

et al. 2023

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Background DNA mismatch repair deficiency (dMMR) testing is crucial for detection of microsatellite unstable (MSI) tumors. MSI is detected by aberrant indel length distributions of microsatellite markers, either by visual inspection of PCR-fragment length profiles or by automated bioinformatic scoring on next-generation sequencing (NGS) data. The former is time-consuming and low-throughput while the latter typically relies on simplified binary scoring of a single parameter of the indel distribution. The purpose of this study was to use machine learning to process the full complexity of indel distributions and integrate it into a robust script for screening of dMMR on small gene panel-based NGS data of clinical tumor samples without paired normal tissue. Methods Scikit-learn was used to train 7 models on normalized read depth data of 36 microsatellite loci in a cohort of 133 MMR proficient (pMMR) and 46 dMMR tumor samples, taking loss of MLH1/MSH2/PMS2/MSH6 protein expression as reference method. After selection of the optimal model and microsatellite panel the two top-performing models per locus (logistic regression and support vector machine) were integrated into a novel script (DeltaMSI) for combined prediction of MSI status on 28 marker loci at sample level. Diagnostic performance of DeltaMSI was compared to that of mSINGS, a widely used script for MSI detection on unpaired tumor samples. The robustness of DeltaMSI was evaluated on 1072 unselected, consecutive solid tumor samples in a real-world setting sequenced using capture chemistry, and 116 solid tumor samples sequenced by amplicon chemistry. Likelihood ratios were used to select result intervals with clinical validity. Results DeltaMSI achieved higher robustness at equal diagnostic power (AUC = 0.950; 95% CI 0.910–0.975) as compared to mSINGS (AUC = 0.876; 95% CI 0.823–0.918). Its sensitivity of 90% at 100% specificity indicated its clinical potential for high-throughput MSI screening in all tumor types. Clinical Trial Number/IRB B1172020000040, Ethical Committee, AZ Delta General Hospital.

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“…Trimmed reads were aligned to the B. dorsalis reference genome (GenBank assembly accession: GCA_020283865.1) using the bwa‐mem command from the burrows‐wheeler aligner tool (Li & Durbin, 2009 ). Variant calling was performed using the GATK Haplotypecaller algorithm implemented in “Elprep” (Herzeel et al, 2021 ). “ElPrep” is a tool designed as an in‐memory and multithreaded toolset to fully take advantage of the processing power available with modern servers and consists of a 5‐step variant calling best practices pipeline.…”

Section: Methodsmentioning

confidence: 99%

Bactrocera dorsalis in the Indian Ocean: A tale of two invasions

Deschepper

Vanbergen

Zhang

et al. 2022

Evolutionary Applications

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An increasing number of invasive fruit fly pests are colonizing new grounds. With this study, we aimed to uncover the invasion pathways of the oriental fruit fly, Bactrocera dorsalis into the islands of the Indian Ocean. By using genome-wide SNP data and a multipronged approach consisting of PCA, ancestry analysis, phylogenetic inference, and kinship networks, we were able to resolve two independent invasion pathways. A western invasion pathway involved the stepping-stone migration of B. dorsalis from the east African coast into the Comoros, along Mayotte and into Madagascar with a decreasing genetic diversity. The Mascarene islands (Reunion and Mauritius), on the contrary, were colonized directly from Asia and formed a distinct cluster. The low nucleotide diversity suggests that only a few genotypes invaded the Mascarenes. The presence of many long runs of homozygosity (ROH) in the introduced populations is indicative of population bottlenecks, with evidence of a more severe bottleneck for populations along the western migration pathway than on the Mascarene islands. More strict phytosanitary regulations are recommended in order to prevent the further spread of B. dorsalis.

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Multithreaded variant calling in elPrep 5

Cited by 12 publications

References 15 publications

Genomic adaptive potential to cold environments in the invasive red swamp crayfish

Genomic adaptive potential to cold environments in the invasive red swamp crayfish

DeltaMSI: artificial intelligence-based modeling of microsatellite instability scoring on next-generation sequencing data

Bactrocera dorsalis in the Indian Ocean: A tale of two invasions

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