MOTIVATION: Oxford Nanopore technologies (ONT) add miniaturization and real time to high-throughput sequencing. All available software for ONT data analytics run on cloud/clusters or personal computers. Instead, a linchpin to true portability is software that works on mobile devices of internet connections. Smartphones' and tablets' chipset/memory/operating systems differ from desktop computers, but software can be recompiled. We sought to understand how portable current ONT analysis methods are. RESULTS: Several tools, from base-calling to genome assembly, were ported and benchmarked on an Android smartphone. Out of 23 programs, 11 succeeded. Recompilation failures included lack of standard headers and unsupported instruction sets. Only DSK, BCALM2 and Kraken were able to process files up to 16 GB, with linearly scaling CPU-times. However, peak CPU temperatures were high. In conclusion, the portability scenario is not favorable. Given the fast market growth, attention of developers to ARM chipsets and Android/iOS is warranted, as well as initiatives to implement mobile-specific libraries. AVAILABILITY AND IMPLEMENTATION: The source code is freely available at: https://github.com/marco-oliva/portable-nanopore-analytics.
MOTIVATION: Oxford Nanopore technologies (ONT) add miniaturization and real time to high-throughput sequencing. All available software for ONT data analytics run on cloud/clusters or personal computers. Instead, a linchpin to true portability is software that works on mobile devices of internet connections. Smartphones' and tablets' chipset/memory/operating systems differ from desktop computers, but software can be recompiled. We sought to understand how portable current ONT analysis methods are. RESULTS: Several tools, from base-calling to genome assembly, were ported and benchmarked on an Android smartphone. Out of 23 programs, 11 succeeded. Recompilation failures included lack of standard headers and unsupported instruction sets. Only DSK, BCALM2 and Kraken were able to process files up to 16 GB, with linearly scaling CPU-times. However, peak CPU temperatures were high. In conclusion, the portability scenario is not favorable. Given the fast market growth, attention of developers to ARM chipsets and Android/iOS is warranted, as well as initiatives to implement mobile-specific libraries. AVAILABILITY AND IMPLEMENTATION: The source code is freely available at: https://github.com/marco-oliva/portable-nanopore-analytics.
Authors: Prashant Pandey; Fatemeh Almodaresi; Michael A Bender; Michael Ferdman; Rob Johnson; Rob Patro Journal: Cell Syst Date: 2018-06-20 Impact factor: 10.304
Authors: Sarah L Castro-Wallace; Charles Y Chiu; Kristen K John; Sarah E Stahl; Kathleen H Rubins; Alexa B R McIntyre; Jason P Dworkin; Mark L Lupisella; David J Smith; Douglas J Botkin; Timothy A Stephenson; Sissel Juul; Daniel J Turner; Fernando Izquierdo; Scot Federman; Doug Stryke; Sneha Somasekar; Noah Alexander; Guixia Yu; Christopher E Mason; Aaron S Burton Journal: Sci Rep Date: 2017-12-21 Impact factor: 4.379
Authors: Sophie C Prendergast; Anna-Christina Strobl; William Cross; Nischalan Pillay; Sandra J Strauss; Hongtao Ye; Daniel Lindsay; Roberto Tirabosco; Jane Chalker; Shazia S Mahamdallie; Alona Sosinsky; Adrienne M Flanagan; Fernanda Amary Journal: J Pathol Clin Res Date: 2020-06-23