Accurate spliced alignment of long RNA sequencing reads

Abstract

Motivation Long-read RNA sequencing technologies are establishing themselves as the primary techniques to detect novel isoforms, and many such analyses are dependent on read alignments. However, the error rate and sequencing length of the reads create new challenges for accurately aligning them, particularly around small exons. Results We present an alignment method uLTRA for long RNA sequencing reads based on a novel two-pass collinear chaining algorithm. We show that uLTRA produces higher accuracy over state-of-the-art aligners with substantially higher accuracy for small exons on simulated and synthetic data. On simulated data, uLTRA achieves an accuracy of about 60% for exons of length 10 nucleotides or smaller and close to 90% accuracy for exons of length between 11 to 20 nucleotides. On biological data where true read location is unknown, we show several examples where uLTRA aligns to known and novel isoforms containing small exons that are not detected with other aligners. While uLTRA obtains its accuracy using annotations, it can also be used as a wrapper around minimap2 to align reads outside annotated regions. Availability uLTRA is available at https://github.com/ksahlin/ultra. Supplementary information Supplementary data are available at Bioinformatics online.

Nanopore sequencing technology, bioinformatics and applications

“…289 ), NanoBLASTer 290 , mapAlign 291 , GraphAligner 292 , smsmap 293 , lordFAST 294 , S-conLSH 295 , QAlign 296 Splice-aware minimap2, Graphmap2 (ref. 102 ), GmAP 100 , STAR 101 , deSALT 103 , magic-BLAST 297 , Deep-Long 298 , uLTRA 299 Genome assembly Canu, miniasm 107 , Flye 110 , Redbean/wtdbg2 (ref. 111 ), Falcon-Unzip 300 , Shasta 164 , Raven 301 , NextDenovo (https://github.com/Nextomics/NextDenovo), Peregrine 302 , HINGe 303 , TULIP 304 , NeCAT 305 metagenome tailored metaFlye 306 , OPeRA-mS (hybrid) 106 Haplotype-aware Hifiasm 307 Genome polishing Nanopolish, Racon 308 , medaka (https://github.com/nanoporetech/medaka), NeuralPolish 309 , PePPeR-margin-DeepVariant 310 , NextPolish (https://github.com/Nextomics/NextPolish), POLCA 311 , HomoPolish 38 SV detection Sniffles 98 , SVIm 312 , NanoSV 112 , Picky 33 , NanoVar 113 , Dysgu 313 , SeNSV 314 , cuteSV 315 SNV detection LongShot 116 , DeepVariant 310 , iGDA 316 , Nanopanel2 (ref.…”

Clearance of Persistent SARS-CoV-2 RNA Detection in a NFκB-Deficient Patient in Association with the Ingestion of Human Breast Milk: A Case Report

“…The reads were aligned against the reference genome Wuhan-Hu-1 (GenBank accession No. MN908947.3) using the minimap2 software, version 2.17.r941 (Cambridge, MA, USA) [ 15 ], and converted into a sorted BAM file using the SAMtools software (Cambridge, MA, USA) [ 16 ]. Length filtering (minimum and maximum sizes of 400 bp and 700 bp, respectively), quality testing, primer trimming, variant calling, and consensus sequencing were performed for each barcode using guppyplex and the ARTIC nanopolish pipeline ( , accessed on 26 April 2022).…”

Safety in Multi-Assembly via Paths Appearing in All Path Covers of a DAG

“…While long reads hold the potential to sequence through the full transcripts, thus resolving the full transcript structure, there are inherent biases in the protocols which makes them unable to sequence longer transcripts [51], [52]. In addition, long-read alignment software have been shown to produce inaccurate alignments [53], [54] on which the assembly methods rely on. Moreover, current state-of-the-art longread transcript assembly methods are still in active development, with precision below 50% on biological data [55].…”