Skip to main content

Correction: PaCBAM: fast and scalable processing of whole exome and targeted sequencing data

The Original Article was published on 26 December 2019

Correction: BMC Genomics 20, 1018 (2019)

https://doi.org/10.1186/s12864-019-6386-6


The wrong Supplementary file was originally published with this article [1]; it has now been replaced with the correct file.

The correct Additional file 1 is also included in this Correction and the original article has been updated.

Reference

  1. Valentini, et al. PaCBAM: fast and scalable processing of whole exome and targeted sequencing data. BMC Genomics. 2019;20:1018. https://doi.org/10.1186/s12864-019-6386-6.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alessandro Romanel.

Supplementary Information

Additional file 1:

 Figure S1. Genomic region mean coverage computation. Figure S2. Cumulative coverage distribution report. Figure S3.Variant allelic fraction distribution report. Figure S4. SNP allelic fraction distribution report. Figure S5. Alternative bases distribution report. Figure S6. Strand bias distribution report. Figure S7. Genomic regions depth of coverage distribution report. Figure S8. Genomic regions GC content distribution report. Figure S9. Run time comparison at 150X depth of coverage. Figure S10. Run time comparison at 230X depth of coverage. Figure S11. Run time comparison at 300X depth of coverage. Figure S12. Memory usage comparison at 150X depth of coverage. Figure S13. Memory usage comparison at 230X depth of coverage. Figure S14. Memory usage comparison at 300X depth of coverage. Figure S15. Memory usage comparison among PaCBAM pileup and pileup module of ASEQ. Figure S16. Comparison of PaCBAM duplicates filtering strategy to Sambamba markdup and Picard MarkDuplicates modules. Figure S17. Performance of PaCBAM duplicated reads filtering. Table S1. Mean depth of coverage and target sizes of all BAM files used to test PaCBAM performance. Table S2. Time and memory usage of duplicates filtering performance analyses. Table S3. Versions of the tools used in performance evaluation analysis.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Valentini, S., Fedrizzi, T., Demichelis, F. et al. Correction: PaCBAM: fast and scalable processing of whole exome and targeted sequencing data. BMC Genomics 25, 463 (2024). https://doi.org/10.1186/s12864-024-10348-5

Download citation

  • Published:

  • DOI: https://doi.org/10.1186/s12864-024-10348-5