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When merging contigs from different clusters, some contig might be very similar or they can cover the same region of the genome, this can artificially increase these values.
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In the third and final stage of assembly we merge contigs from stage 2 along entire clone contigs using a specially designed assembler that uses the clone ordering and clone overlap information to optimize memory usage as well as reduce the number of potential overlaps examined.
We built a pipeline that merged contigs from each NGS data into hybrid assemblies.
After merging contigs in BCCs, all contigs were used for sequence variant analysis.
Merging contigs that overlapped with each other on the human genome resulted in 92,705 contig clusters.
Prior to merging contigs, all duplicates were removed and contigs were combined into a single FASTA file.
However they provide valuable information to merge contigs (reducing contig count from 146 to 122 and increasing N50 size from 99 Kbp to 150 Kbp) and scaffold them (resulting in 110 scaffolds with an N50 size of 232 Kbp), as well as provide indpendent verification of the assembly (266 reads spanned across Newbler contigs and 246 mates connected the contigs).
As we merge contigs we also take the union of the sets of clones.
It represents overlap information from these alignments in a graph, and then finds maximal paths in the graph to produced merged contigs.
Reads sampled from different genomic locations may be misplaced in the same contig either due to hash collisions (contig construction stage) that enable dissimilar reads to share the same min hash value; or because of the graph partitioning strategy (contig clustering stage) employed to merge contigs via common reads.
Assembly merging was performed using the Zorro pipeline [ 56], relying on minimus2 and mummer to split and merge contigs.
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