---
# System prepended metadata

title: Andrew Kittentails Genome
tags: [Genomes, ' Andrew']

---

---
title: Andrew Kittentails Genome Assembly
break: false
tags: Genomes, Andrew
---

# Genome Assembly Notes for *Synthyris bullii*

This document contains notes for genome assembly for Synthyris bullii (Kittentails) with an estimated genome size of 0.6GB (based on Veronica (Synthyris) missurica; Albach and GreilHuber 2004). The genome is being assembled from individual ND9672 grown from maternal plant ND8241 (Nachusa Doug population at Nachusa Grasslands, Illinois). The genome was sequenced by PacBio at Mt. Sinai using a SMRTcell on Revio (ADD MORE METADATA DETAILS) ...

Data is currently on the server Funk @ CBG

**CBG Servers:** Curie = "ID"@10.2.0.53; Funk = @10.2.0.51; Rosalind = @10.2.0.52
**NU Server:** Quest = "ID"@quest.northwestern.edu

**Reminders/tips for running jobs in terminal with screen:**
* Add prefix 'screen -L' to 'command' to go into screen session 
* Add -LogFile to name screen log file
* Add -aS to name each screen
* To view all screens: screen -list
* To reenter session: screen -r <ID>
* CTRL+a+d detaches from screen
* CTRL+a+K kills screen 
* Make sure to log off server when screens are running
* background vs screen
    * With screen, each job has a process ID, and you can see the ID's

## Assembly Outline

1. Run QC with 'SequelTools' or 'LongQC'(expected 20X+ coverage)
2. Run HifiASM - primary and alternate assembly
3. Run BUSCO - uses known genomes to test assembly quality and completeness
4. Create table that contains: total assembly length (bp), N50 (Kbp; 1Mb is a good #), # scaffolds/contigs, BUSCO score (S:D:F:M%)
5. Error Correction - Use pbmm2 and/or GCpp to map raw reads back to assembly, decided to use NextPolish2. 
6. Check BUSCO again!!
7. PROFIT
______________________________________________________

## 1. Run QC with 'SequelTools' or 'LongQC'
 https://github.com/ISUgenomics/SequelTools
 https://github.com/yfukasawa/LongQC

### Long QC
##### Code to run requires:

    input Either fasta, fastq or PacBio BAM formatted file is required. Input file is expected to be ready for analysis or have at least 5x coverage.
    -o or --output specify a path for output
    -x or --preset specify a platform/kit to be evaluated. adapter and some ovlp parameters are automatically applied. (pb-rs2, pb-sequel, ont-ligation, ont-rapid, ont-1dsq)
    
##### Web summary looks good
* file:///C:/Users/adavi/Downloads/web_summary.html
* yield = 26,464,887,540 base pairs
* expected genome size = 600,000,000 base pairs
* yield/expected genome size = 44.1X (average genome coverage)
* N50 = 13,665 (50% of reads are over 13,665 base pairs long)


______________________________________________________
## 2. HifiASM (v0.19.8-r603)

https://github.com/chhylp123/hifiasm

    hifiasm -t 32 synthryis_bullii_bc2049.reads.fastq

**There are multiple hifiasm assembly outputs, they are:**

hifiasm.asm.bp.**p_ctg**.fa; 

* **p_ctg** (Primary Contigs): These are the primary contigs from the assembly, reflecting the overall structure of the assembled genome. They include all the contigs that are considered, regardless of haplotypes. Less accurate but more contiguous. 

* **hap1** and **hap2**: These represent the two haplotypes in a heterozygous assembly. If your organism is diploid, these contigs reflect the two different genetic variants present. **Combining these two assemblies is the preferred approach for generating a usable genome assembly**. 

* **p_utg** (Primary Uniparental Transcripts): These are contigs that represent a single parent in a diploid genome, typically used to simplify analysis by focusing on one haplotype.
______________________________________________________
## 3. BUSCO (v5.5.0)

BUSCO Manual:
https://busco.ezlab.org/busco_userguide.html#command-line-options
BUSCO publication walkthrough (much more helpful):
https://currentprotocols.onlinelibrary.wiley.com/doi/full/10.1002/cpz1.323



##### Convert .gfa to .fa file type
    awk '/^S/{print ">"$2;print $3}' hifiasm.asm.bp.p_ctg.gfa > hifiasm.asm.bp.p_ctg.fa*
##### run on primary contigs and then on combined primary and alternate

* need to check how many cores to use? how many are on Funk? Steve used 30 for hybphaser recently

        screen -L busco -i hifiasm.asm.bp.hap2.p_ctg.fa -m genome -c 30 -o BUSCO_sbull_hap2

Error: No module named 'pandas'
There was a problem installing BUSCO or importing one of its dependencies. See the user guide and the GitLab issue board (https://gitlab.com/ezlab/busco/issues) if you need further assistance.

^^ Looks as though we need to install more dependencies before we can run BUSCO

 **Scores using default evaluation database:**   
*  hap1hap2.p_ctg - combined assembly (USABLE GENOME)
    * ****
*  bp.p_ctg - primary contig
    * **C:100.0%[S:49.0%,D:51.0%],F:0.0%,M:0.0%,n:255**
*  bp.hap1.p_ctg - haplotype 1; primary contig that has been phased
    * **C:98.5%[S:51.0%,D:47.5%],F:0.0%,M:1.5%,n:255**
*  bp.hap2.p_ctg - haplotype 2; primary contig that has been phased
    *  **C:98.9%[S:52.2%,D:46.7%],F:0.4%,M:0.7%,n:255**
*  bp.p_utg - primary unitig; mostly repeat regions
    * **C:100.0%[S:6.3%,D:93.7%],F:0.0%,M:0.0%,n:255**
    
Checking for space on Server:
    cat /proc/cpuinfo
    free -m (free memory)
    df -lh

tail -f busco.log : output give the following error 
    File "/usr/local/lib/python3.10/dist-packages/busco/BuscoRunner.py", line 195, in run
    raise BatchFatalError(str(exc_value))
busco.Exceptions.BatchFatalError: [Errno 5] Input/output error
    
BUSCO COMPLETED!!??
Checking BUSCO output:
    
*    Move and rename accordingly the output 'short_summaries.txt' into a BUSCO_summaries folder so that all summaries can be visualized together 
*  Run:  *python3 scripts/generate_plot.py –wd BUSCO_summaries*
    * cannot get this to run, keeps looking for scripts/generate_plot.py in my directories??   

### Re-running BUSCO with a set lineage
    
* Previous run was with auto-lineage (default) but few scaffolds were returned 
* New run with EUDICOT lineage (eudicots_odb10)
* And run with EMBRYOPHYTA lineage (embryophyta_odb10)

 New command (added lineage with -l eudicots_odb10 and name for screen with -aS hap1):
    
    screen -L -Logfile s_log.busco.eud.p_ctg -aS hap1 busco -i hifiasm.asm.bp.hap1.p_ctg.fa -m genome -l eudicots_odb10 -c 20 -o BUSCO_sbull_eudicot_hap1
    
    screen -L -Logfile s_log.busco.emb.p_ctg -aS emb.p_ctg busco -i hifiasm.asm.bp.hap1.p_ctg.fa -m genome -l embryophyta_odb10 -c 20 -o BUSCO_sbull_embryophyta_hap1

### Eudicota BUSCOs
*  hap1hap2.p_ctg - combined assembly (USABLE GENOME)
    *   **C:96.7%[S:2.7%,D:94.0%],F:0.3%,M:3.0%,n:2326**
    *   2249    Complete BUSCOs (C)
        63      Complete and single-copy BUSCOs (S)
        2186    Complete and duplicated BUSCOs (D)
        8       Fragmented BUSCOs (F)
        69      Missing BUSCOs (M)
        2326    Total BUSCO groups searched

    *    Assembly Statistics:
        2556    Number of scaffolds
        2556    Number of contigs
        2,460,379,596      Total length **This is double the size of the genome right??**
        0.000%  Percent gaps
        2 MB    Scaffold N50
        2 MB    Contigs N50
    
*  bp.p_ctg - primary contig
    * **C:96.4%[S:71.3%,D:25.1%],F:0.4%,M:3.2%,n:2326**
    * 2242    Complete BUSCOs ( C )
        1659    Complete and single-copy BUSCOs (S)
        583     Complete and duplicated BUSCOs (D)
        10      Fragmented BUSCOs (F)
        74      Missing BUSCOs (M)
        2326    Total BUSCO groups searched
    * Assembly Statistics:
        1065    Number of scaffolds
        1065    Number of contigs
        1,337,434,359      Total length (1.3Gb - about twice the size expected)
        0.000%  Percent gaps
        9 MB    Scaffold N50
        9 MB    Contigs N50
    
*  bp.hap1.p_ctg - haplotype 1; primary contig that has been phased
    * **C:94.6%[S:74.5%,D:20.1%],F:0.6%,M:4.8%,n:2326**
    * 2201    Complete BUSCOs (C)
        1734    Complete and single-copy BUSCOs (S)
        467     Complete and duplicated BUSCOs (D)
        14      Fragmented BUSCOs (F)
        111     Missing BUSCOs (M)
        2326    Total BUSCO groups searched
    * Assembly Statistics:
        1668    Number of scaffolds
        1668    Number of contigs
        1,249,595,024      Total length
        0.000%  Percent gaps
        2 MB    Scaffold N50
        2 MB    Contigs N50
    
*  bp.hap2.p_ctg - haplotype 2; primary contig that has been phased
    * **C:94.9%[S:75.0%,D:19.9%],F:0.5%,M:4.6%,n:2326**
    * 2209    Complete BUSCOs (C)
        1745    Complete and single-copy BUSCOs (S)
        464     Complete and duplicated BUSCOs (D)
        11      Fragmented BUSCOs (F)
        106     Missing BUSCOs (M)
        2326    Total BUSCO groups searched
    * Assembly Statistics:
        888     Number of scaffolds
        888     Number of contigs
        1210784572      Total length
        0.000%  Percent gaps
        3 MB    Scaffold N50
        3 MB    Contigs N50
*  bp.p_utg - primary unitig; mostly repeat regions
    *   **C:96.8%[S:7.0%,D:89.8%],F:0.3%,M:2.9%,n:2326**
        2250    Complete BUSCOs (C)
        162     Complete and single-copy BUSCOs (S)
        2088    Complete and duplicated BUSCOs (D)
        8       Fragmented BUSCOs (F)
        68      Missing BUSCOs (M)
        2326    Total BUSCO groups searched
    *  Assembly Statistics:
        24217   Number of scaffolds
        24217   Number of contigs
        2605941398      Total length
        0.000%  Percent gaps
        634 KB  Scaffold N50
        634 KB  Contigs N50
    
### Embryophyta BUSCOs
    
    C:98.6%[S:2.6%,D:96.0%],F:0.3%,M:1.1%,n:1614
        1592    Complete BUSCOs (C)
        42      Complete and single-copy BUSCOs (S)
        1550    Complete and duplicated BUSCOs (D)
        5       Fragmented BUSCOs (F)
        17      Missing BUSCOs (M)
        1614    Total BUSCO groups searched
    
    Assembly Statistics:
        2556    Number of scaffolds
        2556    Number of contigs
        2460379596      Total length
        0.000%  Percent gaps
        2 MB    Scaffold N50
        2 MB    Contigs N50
    
______________________________________________________    
## 4. Create Busco Tables to visualize assembly quality
    
* Total assembly length (bp) = 1,337,434,359 
* N50 (kbp) = 
* Number of scaffolds/contigs = 1065
* BUSCO C(S:D):F:M)% = 49.0 : 51.0 : 0 0 : 0.0
    * C = 100%
    * n = 255
    
* **Complete:100.0%[Single-copy:49.0%, Duplicate:51.0%], Fragmented:0.0%, Missing:0.0%, n:255**

![image](https://hackmd.io/_uploads/BJJGwXSoA.png)
    
    
________________________________________________________
    
## 5. Error Correction with meryl, winnowmap, samtools and Polishing Genome with NextPolish2 ##
    
* Need to install nextpolish2, if you get the _libgcc-ng >=12 error_, run:
            
        conda config --append channels conda-forge
    to  tell conda to also look on the conda-forge channel when you search for packages
    
* Combine all hifiasm assembly outputs (hap1, hap2, p_ctg, p_utg) into one assembly file:
    
        cat hifiasm.asm.bp.hap1.p_ctg.fa hifiasm.asm.bp.hap2.p_ctg.fa hifiasm.asm.bp.p_ctg.fa hifiasm.asm.bp.p_utg.fa > s_bullii.combined_assembly.fa
    
    
    
    ^^ this didn't work with winnowmap, I got a -split-prefix error so i have rerun winnow on each assembly separately - when do I combine the genome assemblies??
    
     
    
https://github.com/Nextomics/NextPolish2?tab=readme-ov-file#install
    
    
**1. Prepare HiFi mapping file with winnowmap (can also used minimap2)** (what and why courtesy of ChatGPT4.0)
    
        screen -L -Logfile meryl_assembly -aS meryl.asm # prefix to code for screen 
        meryl count k=15 output merylDB s_bullii.combined_assembly.fa

**What 'meryl count' does**: This command uses a tool called meryl to count k-mers (short sequences of DNA) of length 15 from the input file asm.fa.gz (a compressed file of **your genome assembly**).

**Why**: It creates a database (merylDB) that stores information about these 15-mers
        
    meryl print greater-than distinct=0.9998 merylDB > repetitive_k15.txt
        
**What 'meryl print' does:** This command generates a list of k-mers from the merylDB that are highly unique (greater than 99.98% distinct).

**Why:** It helps identify and filter out repetitive sequences, saving them to repetitive_k15.txt.    
    
    winnowmap -t 5 -W repetitive_k15.txt -ax map-pb synthryis_bullii_bc2049.reads.fastq s_bullii.combined_assembly.fa|samtools sort -o hifi.map.sort.bam -
    

**What 'winnowmap' does:** This command uses winnowmap to align the HiFi reads (hifi.fasta.gz) to the assembly (asm.fa.gz), using the unique k-mers for better accuracy. The results are sorted and saved as a BAM file (hifi.map.sort.bam).

**Why:** This alignment helps in mapping the reads to the assembly, which is essential for polishing the genome.


    
** having trouble with this file ^^ 
    
9/10/24: running a few different ways:   

    winnow > rerun witout | to samtools = no output to be found, see winnow_combo
    winnow_2 > rerun with p_ctg assembly only, no | = typo in input file
    winnow_3 > rerun with p_ctg assembly only, no | and > hifi_map.sam = typo in input/re run
    
        winnowmap -t 60 -W repetitive_k15.txt -ax map-pb --split-prefix combined_map s_bullii.combined_assembly.fa synthryis_bullii_bc2049.reads.fastq

    ^^^ There is no output file still??? I can't find any errors in the screenlog
    
Trying this with hap1 (smallest assembly file to expedite troubleshooting):
    
        screen -L -Logfile winnow_hap1 -aS winnow.hap1 winnowmap -t 30 -W repetitive_k15.txt -ax map-pb hifiasm.asm.bp.hap1.p_ctg.fa synthryis_bullii_bc2049.reads.fastq > hifi.map.hap1.sam
    
^^^ OUTPUT FILE IS CREATED BUT EMPTY AGHH
    
trying again with the samtools sort option
    
    screen -L -Logfile s_log.winnow_hap1_samtools -aS winnow.hap1 winnowmap -t 100 -W repetitive_k15.txt -ax map-pb -o hifi.map.hap1.sam hifiasm.asm.bp.hap1.p_ctg.fa synthryis_bullii_bc2049.reads.fastq | samtools sort -o hifi.map.sort.bam -
    
No .bam file but I have a .sam file!! IT WORKKKEEEDD!! Finally an output, kind of unsure what wotked though :(
    
Repeat with hap2, p_ctg, and u_ctg...
    
* hap2:
    
        screen -L -Logfile s_log.winnow_hap2 -aS winnow.hap2 winnowmap -t 40 -W repetitive_k15.txt -ax map-pb -o hifi.map.hap2.sam hifiasm.asm.bp.hap2.p_ctg.fa synthryis_bullii_bc2049.reads.fastq 

* p_ctg
    
        screen -L -Logfile s_log.winnow_p_ctg -aS winnow.p_ctg winnowmap -t 40 -W repetitive_k15.txt -ax map-pb -o hifi.map.p_ctg.sam hifiasm.asm.bp.p_ctg.fa synthryis_bullii_bc2049.reads.fastq 
    
* p_utg

        screen -L -Logfile s_log.winnow_p_utg -aS winnow.p_utg winnowmap -t 40 -W repetitive_k15.txt -ax map-pb -o hifi.map.p_utg.sam hifiasm.asm.bp.p_utg.fa synthryis_bullii_bc2049.reads.fastq
    
   **b. sorting** (haven't been able to get this to work on the end of the winnowmap command, so sorting after map is created)
    
        samtools sort -o hifi.map.hap1.sort.bam hifi.map.hap1.sam 
    
    
   **c. indexing**
    
        samtools index hifi.map.sort.bam
    
**What 'samtools index' does:**  generates a .bai file (index file) for the specified BAM file. This index file contains information about the positions of the reads in the BAM file.
    
**Why:** The index allows for quick random access to specific regions of the BAM file. This is especially useful when working with large genomic datasets, as it enables tools and applications (like genome browsers) to quickly retrieve and display data from specific regions without needing to read the entire BAM file. When you use a .bam file with other bioinformatics tools, the tools typically access the associated .bai file automatically if it is present in the same directory and follows the naming convention (i.e., the same name as the .bam file, but with the .bai extension)


**2. Creating k-mer files with yak (21 and 31 k-mers, explore why we would use others)**
    
        yak count -o k21.yak -k 21 -b 37 -i synthryis_bullii_bc2049.reads.fastq
    
        yak count -o k31.yak -k 31 -b 37 -i synthryis_bullii_bc2049.reads.fastq
    

**What 'yak' does:** This command counts 21/31-mers from the provided FASTQ files (which contain raw sequencing data) and outputs the results to k21.yak. The -b 37 option is used to exclude singletons (k-mers that appear only once).

**Why:** Producing k-mer datasets helps in understanding the composition of the sequences.


    
**3. Run NextPolish2**
    
        screen -L -Logfile s_log.nextpolish4 -aS nextPolish_hap1 nextPolish2 -t 60 hifi.map.hap1.sort.bam hifiasm.asm.bp.hap1.p_ctg.fa k21.yak k31.yak -o asm.np2.hap1.fa
    
**What 'nextPolish2' does:** This command runs NextPolish2, which refines the genome assembly using the aligned HiFi reads and k-mer datasets.

**Why:** The goal is to improve the quality of the assembly by correcting errors and filling gaps.
 
Citation to use:
    
Jiang Hu, Zhuo Wang, Fan Liang, Shan-Lin Liu, Kai Ye, De-Peng Wang, NextPolish2: A Repeat-aware Polishing Tool for Genomes Assembled Using HiFi Long Reads, Genomics, Proteomics & Bioinformatics, 2024, qzad009, https://doi.org/10.1093/gpbjnl/qzad009
    
    
______________________________________________________    
## 6. Re-run busco on polished genome (asm.np2.fa)
    
    #eudicots
        screen -L -Logfile busco_hap1_np2 -aS hap1_np2 busco -i asm.np2.hap1.fa -m genome -l eudicots_odb10 -c 80 -o BUSCO_sbull_eudicot_hap1_polished
    
    #embryophyta
        screen -L -Logfile s_log.busco.p_ctg.emb.np2 -aS p_ctg_emb_np2 busco -i asm.np2.p_ctg.fa -m genome -l embryophyta_odb10 -c 34 -o BUSCO_sbull_embryophyta_p_ctg_polished

______________________________________________________    
## 7. FINAL ASSESSMENT OF ASSEMBLY
Should I evaluate assembly with the eudicot or the embryophyta dataset in busco?
    
In (Koshimizu et al. 2023; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10558197/), they used and reported both. They reported "99.4% and 99.6% coverage of the core genes of eudicots and embryophyta, respectively."
    
For S.bullii, the assembly contains 96.5% and 98.5% coverage of the core genes of eudicots and embryophyta, respectively.

**Eudicot BUSCO eval:**
* **p_ctg**:
    * **Before polishing**:
        C:96.4%[S:71.3%,D:25.1%],F:0.4%,M:3.2%,n:2326**
        2242    Complete BUSCOs ( C )
        1659    Complete and single-copy BUSCOs (S)
        583     Complete and duplicated BUSCOs (D)
        10      Fragmented BUSCOs (F)
        74      Missing BUSCOs (M)
        2326    Total BUSCO groups searched
    * **After polishing**: 
        C:96.5%[S:71.4%,D:25.1%],F:0.4%,M:3.1%,n:2326
        2244    Complete BUSCOs (C)
        1661    Complete and single-copy BUSCOs (S)
        583     Complete and duplicated BUSCOs (D)
        10      Fragmented BUSCOs (F)
        72      Missing BUSCOs (M)
        2326    Total BUSCO groups searched
* **hap1**:
    * **Before polishing**:
     C:94.6%[S:74.5%,D:20.1%],F:0.6%,M:4.8%,n:2326
    2201    Complete BUSCOs (C)
        1734    Complete and single-copy BUSCOs (S)
        467     Complete and duplicated BUSCOs (D)
        14      Fragmented BUSCOs (F)
        111     Missing BUSCOs (M)
        2326    Total BUSCO groups searched
    * **After polishing (lol @ marginal gains)**:
        C:94.7%[S:74.6%,D:20.1%],F:0.6%,M:4.7%,n:2326|
        |2202   Complete BUSCOs (C)|
        |1735   Complete and single-copy BUSCOs (S)|
        |467    Complete and duplicated BUSCOs (D)|
        |14     Fragmented BUSCOs (F)|
        |110    Missing BUSCOs (M)|
        |2326   Total BUSCO groups searched| 

* **hap2:**
    * **Before polishing**:
        C:94.9%[S:75.0%,D:19.9%],F:0.5%,M:4.6%,n:2326
        2209    Complete BUSCOs (C)
        1745    Complete and single-copy BUSCOs (S)
        464     Complete and duplicated BUSCOs (D)
        11      Fragmented BUSCOs (F)
        106     Missing BUSCOs (M)
        2326    Total BUSCO groups searched
    * **After polishing**:  
        C:94.9%[S:75.0%,D:19.9%],F:0.5%,M:4.6%,n:2326
        2209    Complete BUSCOs (C)
        1745    Complete and single-copy BUSCOs (S)
        464     Complete and duplicated BUSCOs (D)
        11      Fragmented BUSCOs (F)
        106     Missing BUSCOs (M)
        2326    Total BUSCO groups searched

* **p_utg:**
    * **Before polishing**:
        C:96.8%[S:7.0%,D:89.8%],F:0.3%,M:2.9%,n:2326
        2250    Complete BUSCOs (C)
        162     Complete and single-copy BUSCOs (S)
        2088    Complete and duplicated BUSCOs (D)
        8       Fragmented BUSCOs (F)
        68      Missing BUSCOs (M)
        2326    Total BUSCO groups searched
    * **After polishing**:

        

*  bp.p_ctg - primary contig (THIS IS PRIMARY SEQUENCE)
    * **C:96.4%[S:71.3%,D:25.1%],F:0.4%,M:3.2%,n:2326**
    * 2242    Complete BUSCOs ( C )
        1659    Complete and single-copy BUSCOs (S)
        583     Complete and duplicated BUSCOs (D)
        10      Fragmented BUSCOs (F)
        74      Missing BUSCOs (M)
        2326    Total BUSCO groups searched
    
**Embryophyta BUSCO eval:**
    
* p_ctg:
    * **Before polishing**:
        C:98.4%[S:74.3%,D:24.1%],F:0.4%,M:1.2%,n:1614
        1589    Complete BUSCOs (C)
        1200    Complete and single-copy BUSCOs (S)
        389     Complete and duplicated BUSCOs (D)
        7       Fragmented BUSCOs (F)
        18      Missing BUSCOs (M)
        1614    Total BUSCO groups searched
    * **After polishing**:   
        C:98.5%[S:74.4%,D:24.1%],F:0.4%,M:1.1%,n:1614
        1590    Complete BUSCOs (C)
        1201    Complete and single-copy BUSCOs (S)
        389     Complete and duplicated BUSCOs (D)
        7       Fragmented BUSCOs (F)
        17      Missing BUSCOs (M)
        1614    Total BUSCO groups searched
        1065    Number of scaffolds
        1065    Number of contigs
        1,337,213,455      Total length
        0.000%  Percent gaps
        9 MB    Scaffold N50
        9 MB    Contigs N50
    
* **hap1**:
    * **Before polishing**:
        C:96.7%[S:77.1%,D:19.6%],F:0.5%,M:2.8%,n:1614
        1562    Complete BUSCOs (C)
        1245    Complete and single-copy BUSCOs (S)
        317     Complete and duplicated BUSCOs (D)
        8       Fragmented BUSCOs (F)
        44      Missing BUSCOs (M)
        1614    Total BUSCO groups searched
    * **After polishing**:
        C:96.8%[S:77.2%,D:19.6%],F:0.5%,M:2.7%,n:1614
        1563    Complete BUSCOs (C)
        1246    Complete and single-copy BUSCOs (S)
        317     Complete and duplicated BUSCOs (D)
        8       Fragmented BUSCOs (F)
        43      Missing BUSCOs (M)
        1614    Total BUSCO groups searched

* hap2:
    * **Before polishing**:
        C:97.1%[S:77.8%,D:19.3%],F:0.5%,M:2.4%,n:1614
        1567    Complete BUSCOs (C)
        1256    Complete and single-copy BUSCOs (S)
        311     Complete and duplicated BUSCOs (D)
        8       Fragmented BUSCOs (F)
        39      Missing BUSCOs (M)
        1614    Total BUSCO groups searched
    * **After polishing**:
        C:97.1%[S:77.8%,D:19.3%],F:0.5%,M:2.4%,n:1614
        1567    Complete BUSCOs (C)
        1256    Complete and single-copy BUSCOs (S)
        311     Complete and duplicated BUSCOs (D)
        8       Fragmented BUSCOs (F)
        39      Missing BUSCOs (M)
        1614    Total BUSCO groups searched

* p_utg:
    * **Before polishing**:
    
    * **After polishing**:

    

## 8. Moving data between NU-Quest and CBG with rsync
    
From Funk to Quest: 
    
    rsync -aivP /home/amd9539/Kittentails/2.Genome/ amd9539@quest.northwestern.edu:/projects/p31922/05_genome/
    
From Quest to Funk:
    rsync -aivP /projects/p31922/05_genome/scripts amd9539@10.2.0.51:/home/amd9539/Kittentails/2.Genome/ 
    