Alfred: interactive multi-sample BAM alignment statistics, feature counting and feature annotation for long- and short-read sequencing

Bioinformatics. 2019 Jul 15;35(14):2489-2491. doi: 10.1093/bioinformatics/bty1007.

Abstract

Summary: Harmonizing quality control (QC) of large-scale second and third-generation sequencing datasets is key for enabling downstream computational and biological analyses. We present Alfred, an efficient and versatile command-line application that computes multi-sample QC metrics in a read-group aware manner, across a wide variety of sequencing assays and technologies. In addition to standard QC metrics such as GC bias, base composition, insert size and sequencing coverage distributions it supports haplotype-aware and allele-specific feature counting and feature annotation. The versatility of Alfred allows for easy pipeline integration in high-throughput settings, including DNA sequencing facilities and large-scale research initiatives, enabling continuous monitoring of sequence data quality and characteristics across samples. Alfred supports haplo-tagging of BAM/CRAM files to conduct haplotype-resolved analyses in conjunction with a variety of next-generation sequencing based assays. Alfred's companion web application enables interactive exploration of results and comparison to public datasets.

Availability and implementation: Alfred is open-source and freely available at https://tobiasrausch.com/alfred/.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Data Accuracy
  • High-Throughput Nucleotide Sequencing*
  • Quality Control
  • Software*