Human_Read_Removal_Investigation___Viral_Read_Sets
Teams within the Wellcome Sanger Institute have been collaborating to investigate the performance of multiple Human Read Removal (HRR) methods. To this end, a synthetic titration dataset was produced, comprising read sets derived from viral reads arising from a bait capture experiment artificially mixed with equal proportions of 27 human read sets derived from samples in the 30X Illumina Coverage study under the 1000 Genomes Project (PRJEB31736). Viral and human reads were mixed in varying proportions ranging from 1:9 to 9:1 human:viral, with 3 iterations of each viral read set + human reads at each titre for representative sampling. This study contains the full synthetic titration dataset used to validate the human read removal methodologies, with 351 read sets comprising 13 viral samples, at 9 human titres with 3 iterations of each. Reads arising from the 1000 genomes project samples can be identified in read names by the presence of a relevant ENA run accession number (prefixed ERR), other reads are derived from the viral samples. This dataset was run through multiple human read removal methods and subsequent read composition was interrogated in a read-fate analysis to assess performance of the various methods.