❗❗❗ [READ ME FIRST] Issue Submission Guidelines ❗❗❗

[zengxiaofei]

I maintain this project in my spare time. To make support efficient and save time for everyone, I need to be able to quickly understand your question and identify the problem.

Please read the following guidelines carefully before submitting an issue. Issues that do not follow these guidelines may be closed without a response.

Step 1: Before You Submit an Issue

Before submitting a new issue, please make sure you have already tried the following:

• Read the documentation: [English] | [简体中文]
• Check the help messages for the relevant commands (e.g., haphic -h, haphic pipeline -h, haphic cluster -h, haphic plot -h) to understand all available parameters and their descriptions.
• Search existing issues to see if your question has already been answered: https://github.com/zengxiaofei/HapHiC/issues
• Consult the AI-powered HapHiC Knowledge Base: DeepSeek-Powered HapHiC Knowledge Base #106

Step 2: Submitting Your Issue

If you've gone through the steps above and still need help, please create a new issue following these principles:

(1) One Issue, One Topic

• Summarize your core question or problem. Each issue should focus on a single topic.
• If you have multiple unrelated questions, please create separate issues for each. This helps other users find relevant discussions more easily.
• Choose a descriptive title that accurately reflects the content of the issue.

(2) Describe Your Problem Systematically

• Use bullet points or a structured format to describe your situation, the information you have, and the specific sub-questions you have about the central topic.
• Avoid a "stream of consciousness" narrative. Do not simply paste your raw, unstructured thought process. Organize your thoughts first.

(3) Provide Sufficient Context

Please provide as much relevant information as possible:

Biological Background

• Karyotype and ploidy level: e.g., 2n=4x=32.
• Polyploidy type: Is it an autopolyploid or an allopolyploid? If known, specify the genome formula (e.g., AAAA, AABB).
• Expected genome size: Specify whether this size corresponds to 2n (2C), 1n (1C), or 1x, and how it was estimated (e.g., flow cytometry, GenomeScope, k-mer depth, closely related species).
• Microchromosomes: Does your species have them? Does the provided karyotype / chromosome number include them?
• General taxonomic group: e.g., Mammal, Monocot, Fish.

Assembly Process

• Data types used for the initial assembly: e.g., PacBio HiFi, ONT long reads, ONT ultra-long reads, Hi-C reads.
• Sample source: Are the Hi-C reads and the long reads from the same individual?
• Origin of the input genome assembly: Which assembler was used? Was it haplotype-phased? Which assemblywas used (e.g., p_ctg, hap*.p_ctg, p_utg)? Was it processed with any other processes (e.g., purge dups, polishing, scaffolding)?
• Hi-C data processing: How was the Hi-C data mapped and filtered? Please provide the exact commands used. (It is strongly recommended to use the mapping and filtering pipeline described in our documentation).
• The complete log file (or stderr output) from your HapHiC run. This contains critical information like the software version, the exact command executed, and any error messages.
• Basic assembly statistics: e.g., total size, contig N10-N90 and L10-L90; you can calculate them using this tool:

  $ gunzip fa_detail.gz
  $ chmod 755 fa_detail
  $ fa_detail asm.fa

Result-related Issues

• A picture is worth a thousand words. Visualizing your Hi-C contact map in Juicebox is almost always the most efficient and intuitive way to show your results. Please provide screenshots instead of long text descriptions.
• Juicebox also clearly displays contig and scaffold boundaries, which is crucial information that haphic plot currently cannot provide.
• If the pipeline terminated due to a clustering issue, please visualize the results from the quick view mode and provide the Hi-C contact map.
• For clustering-specific problems, please also provide the following files:
  • 01.cluster/inflation_3.0/mcl*.txt
  • 02.reassign/reassigned_groups/reassigned_clusters.txt
  • 02.reassign/final_groups/final_clusters.txt