streammd: fast low-memory duplicate marking using a Bloom filter.

Leonard, Conrad · Bioinformatics · 2023

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Abstract

Identification of duplicate templates is a common preprocessing step in bulk sequence analysis; for large libraries, this can be resource intensive. Here, we present streammd: a fast, memory-efficient, single-pass duplicate marker operating on the principle of a Bloom filter. streammd closely reproduces outputs from Picard MarkDuplicates while being substantially faster, and requires much less memory than SAMBLASTER. streammd is a C++ program available from GitHub https://github.com/delocalizer/streammd under the MIT license.

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