Here is a very interesting article by C. Titus Brown’s group. It uses connectivity analysis of graphs to find artifacts in sequencing libraries.
Sequencing errors and biases in metagenomic datasets affect coverage-based assemblies and are often ignored during analysis. Here, we analyze read connectivity in metagenomes and identify the presence of problematic and likely a-biological connectivity within metagenome assembly graphs. Specifically, we identify highly connected sequences which join a large proportion of reads within each real metagenome. These sequences show position-specific bias in shotgun reads, suggestive of sequencing artifacts, and are only minimally incorporated into contigs by assembly. The removal of these sequences prior to assembly results in similar assembly content for most metagenomes and enables the use of graph partitioning to decrease assembly memory and time requirements.
Sorry for late reporting. The paper had been posted at arxiv site for over a month back. We got somewhat turned off about artifact papers having written one several years back. In our paper, we used sequence statistics to find an artifact in microarray data, and then traced back its chemical origin. We thought it was very cool finding and were very excited about it, but nobody else cared :(