Faq

How to choose restriction enzymes and library preparation strategies¶

To achieve the best scaffolding and phasing performance, we recommend the following strategies for different sequencing data types:

• For long-read based technologies (e.g., Pore-C or CiFi): We recommend using 4-cutter restriction enzymes (such as DpnII, MboI， or NlaIII) rather than 6-cutter enzymes (such as HindIII). 4-cutter enzymes have a much higher density of restriction sites, which can generate a larger number of shorter DNA fragments on a single long read. This allows for the capture of richer and higher-order physical contacts.

• For short-read based technologies (e.g., traditional Hi-C): The recommended priority is: Omni-C > Multi-restriction sites Hi-C (e.g., Arima) > Traditional single-restriction site Hi-C.
  • Omni-C uses DNase I for sequence-independent digestion, providing extremely uniform sequence coverage and eliminating the sequence bias and blind spots associated with specific restriction enzyme motifs.
  • Arima multi-enzyme protocols provide significantly higher site density than single-enzyme protocols, facilitating the accurate resolution of challenging regions in polyploid and complex genomes.

The results of the first round partition are unsatisfactory.¶

In our two-round partition algorithm, the first round partition depends on the h-trans errors between homologous chromosomes; if you input a contig assembly with low level switch errors or input a high accuracy pore-c data, the h-trans will be not enough to cluster all contigs to correct homologous groups, resulting in unsatisfactory results. You can set the -q1 0 for hyperpartition to increase the rate of h-trans errors. However, this parameter may raise error of out of memory when you input huge pore-c data in porec table or hic contacts in pairs file.

The total size of the chromosomes significantly smaller than the estimate genome size¶

If the following two conditions exist, you can adjust the mode of the cphasing pipeline to either (--preset sensitive) or (--preset very-sensitive). 1. The amount of entered data is low. 2. The input genome is relatively complex, with many homozygous or nearly homozygous regions. It should be noted that the above two modes will cause some very small contig to cluster or sort incorrectly. In the second case, greedy clustering may occurs, in which two highly homologous sets of chromosomes are grouped into one group.

How to set the -n parameter when assembling an aneuploid genome.¶

The aneuploid genome, such as modern cultivated sugarcane, contains unequal homologous chromosomes. The -n parameter can be set to zero (-n 10:0) to automatically partition contigs into different chromosomes within a homologous group.
However, we also allow the user to input a file with two columns: the first column is the index(1-base) of the first round partition, and the second column is the chromosome number of each homologous. And then specified the -n 10:second.number.tsv in cphasing pipeline or cphasing hyperpartition. - second.number.tsv

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