Low-memory digital normalization.
收藏Figshare2015-12-02 更新2026-04-29 收录
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The results of digitally normalizing a 5 m read E. coli data set (1.4 GB) to C = 20 with k = 20 under several memory usage/false positive rates. The false positive rate (column 1) is empirically determined. We measured reads remaining, number of “true” k-mers missing from the data at each step, and the number of total k-mers remaining. Note: at high false positive rates, reads are erroneously removed due to inflation of k-mer counts.
创建时间：
2015-12-02
