ArticlePloS one2015
elPrep: High-Performance Preparation of Sequence Alignment/Map Files for Variant Calling.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed.
- Genetic Heterogeneity of Autism Spectrum Disorder: Identification of Five Novel Mutations (RIMS2, FOXG1, AUTS2, ZCCHC17, and SPTBN5) in Iranian Families via Whole-Exome and Whole-Genome Sequencing.Biochemical genetics · 2026Article
- Article
- Assessing and assuring interoperability of a genomics file format.Bioinformatics (Oxford, England) · 2022Article
- From molecules to genomic variations: Accelerating genome analysis via intelligent algorithms and architectures.Computational and structural biotechnology journal · 2022Review
- SamQL: a structured query language and filtering tool for the SAM/BAM file format.BMC bioinformatics · 2021Article
- Single-cell RNA sequencing of developing maize ears facilitates functional analysis and trait candidate gene discovery.Developmental cell · 2021Article
- Multithreaded variant calling in elPrep 5.PloS one · 2021Article
- Optimizing performance of GATK workflows using Apache Arrow In-Memory data framework.BMC genomics · 2020Article
- A comparison of three programming languages for a full-fledged next-generation sequencing tool.BMC bioinformatics · 2019Article
- Preeclampsia is Associated with Sex-Specific Transcriptional and Proteomic Changes in Fetal Erythroid Cells.International journal of molecular sciences · 2019Article
- Comparing Ease of Programming in C++, Go, and Java for Implementing a Next-Generation Sequencing Tool.Evolutionary bioinformatics online · 2019Article
- elPrep 4: A multithreaded framework for sequence analysis.PloS one · 2019Article
- How the strengths of Lisp-family languages facilitate building complex and flexible bioinformatics applications.Briefings in bioinformatics · 2018Article
- Evaluating the necessity of PCR duplicate removal from next-generation sequencing data and a comparison of approaches.BMC bioinformatics · 2016Article
- Unmasking genetic etiologies in neurodevelopmental disorders characterized by Cerebral Palsy: insights from integrative genomic approaches.Frontiers in neurologyArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
elPrep is a high-performance tool for preparing sequence alignment/map files for variant calling in sequencing pipelines. It can be used as a replacement for SAMtools and Picard for preparation steps such as filtering, sorting, marking duplicates, reordering contigs, and so on, while producing identical results. What sets elPrep apart is its software architecture that allows executing preparation pipelines by making only a single pass through the data, no matter how many preparation steps are used in the pipeline. elPrep is designed as a multithreaded application that runs entirely in memory, avoids repeated file I/O, and merges the computation of several preparation steps to significantly speed up the execution time. For example, for a preparation pipeline of five steps on a whole-exome BAM file (NA12878), we reduce the execution time from about 1:40 hours, when using a combination of SAMtools and Picard, to about 15 minutes when using elPrep, while utilising the same server resources, here 48 threads and 23GB of RAM. For the same pipeline on whole-genome data (NA12878), elPrep reduces the runtime from 24 hours to less than 5 hours. As a typical clinical study may contain sequencing data for hundreds of patients, elPrep can remove several hundreds of hours of computing time, and thus substantially reduce analysis time and cost.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.