DeepGenotype

Calculates the frequencies of protein-level mutations from deep-sequencing reads of CRISPR-edited cells

Features

• Calculates genotypes with respect to protein/payload expressiblity and correctness
• Automatically processes a list of samples
• Supports CRISPR editing types: tagging/insertion and SNP/base-editing
• Works with both Illumina and PacBio reads
• Automatically finds coding regions
• Invokes CRISPResso2 to perform read processing and alignment

Inputs

There are two required input files:

• Fastq files (can be gzipped or not)
• A csv file (examples provided in example_csv), see below.

csv file columns

The input csv should contain the following columns with the exact names

• Sample_ID (e.g. mNGplate19_sorted_A2_DDX6-C)
  Important note: For paired-end sequencing, only one Sample_ID is needed. We automatically find both R1 and R2 fastq files.
  Check fastq file suffix parameters --fastq_R1_suffix and --fastq_R1_suffix in the Usage section.
  Also check if you need Fastq_extra_suffix (below)

• gene_name (e.g. DDX6)

• ENST_id (e.g. ENST00000620157)

• WT_amplicon_sequence

• HDR_amplicon_sequence

• gRNA_sequence

• edit_type (e.g. INS or SNP, note that deletions, DEL is not supported at this point)
      INS = insertion, SNP = single nucleotide polymorphism, DEL = deletion

• SNP_payload_cluster (e.g. 1 or 2 ...)     Only needed when edit_type = SNP
      This defines which cluster of SNPs is the payload (TODO: clarify how the non-payload SNPs will affect the perfect HDR, and wt-protein rates)
      Clusters are ordered from left to right in respect to the amplicon sequence.
      For examplp: there are 2 clusters of SNPs, the first cluster is a recut SNP and the second cluster of SNPs is of interest (payload), SNP_cluster should be set to 2, and the first cluster of SNP will only be anlayzed for mutations if its in the coding region.

• Fastq_extra_suffix (Optional)

     Extra suffix needed for mapping Sample_ID to corresponding fastq file names.

     Please note that the common (as opposed to extra) suffixes are the following values by default:
     "_R1_001.fastq.gz"
     "_R2_001.fastq.gz"

     For example if your fastq file names are:
                                                "mNGplate19_sorted_A2_DDX6-C_S90_R1_001.fastq.gz"
                                                "mNGplate19_sorted_A2_DDX6-C_S90_R2_001.fastq.gz"
      and your sample name is "mNGplate19_sorted_A2_DDX6-C", and "S90" is another variable part of the name
     Then you should add "S90" to the "Fastq_extra_suffix" column

 

Outputs:

• Protein-level genotype frequencies table in a csv file
• CRISPResso2 output that includes
  • Read aligning rate
  • Sequence-level genotype frequencies table
  • read-to-genotype assignments information

 

Installation

create a conda environment and activate it

conda create -n DeepGenotype python=3.9
conda activate DeepGenotype

install CRISPResso2

conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge
conda install CRISPResso2==2.2.14

verify CRISPResso2 installation

CRISPResso -h

clone DeepGenotype repo and install dependencies

git clone https://github.com/czbiohub-sf/DeepGenotype
cd DeepGenotype
pip install . # or pip install biopython==1.78 pandas requests openpyxl==3.1.2

verify DeepGenotype installation

cd DeepGenotype # must be in the DeepGenotype/DeepGenotype directory
python DeepGenotype.py

 

Usage:

python DeepGenotype.py --path2csv example_csv/test.csv --path2workDir test_dir/ --path2fastqDir test_dir/fastq_dir/

All paths are relative to DeepGenotype.py
Please make sure the following two python scripts are in the same directory as DeepGenotype.py:
    process_alleles_freq_table_INS.py
    process_alleles_freq_table_SNP.py

Optional arguments

--fastq_R1_suffix    (default "_R1_001.fastq.gz")
--fastq_R2_suffix    (default "_R2_001.fastq.gz")
--single_fastq_suffix    (use this option for single-ended reads as well as pacbio reads, need to specific the suffix, e.g.: fastq.gz)
--quantification_window_size    (default 50, which overrides CRISPResso2's default of 1)

 

To run pacbio test dataset (insertion mode)

load conda, and activate the DeepGenotype conda environment

module load anaconda
conda activate DeepGenotype

run DeepGenotype

# in DeepGenotype/DeepGenotype directory
python DeepGenotype.py \
--path2csv example_csv/test_pacbio.csv \
--path2workDir test_PacBio \
--path2fastqDir test_PacBio/fastq \
--single_fastq_suffix .fastq

NOTE: to run DeepGenotype in the background (and thus safe to close the terminal), preprend nohup and append & to the command:

nohup python DeepGenotype.py \
--path2csv example_csv/test_pacbio.csv \
--path2workDir test_PacBio \
--path2fastqDir test_PacBio/fastq \
--single_fastq_suffix .fastq &

To check the terminal output (while running in the background

cat nohup.out

The completed nohup.out should look like this

[DeepGenotype.py][INFO]  Genome edit type: INS
[DeepGenotype.py][INFO]  Processing sample: HEK-nocap-CLTA-R1_ccs.lbc89--lbc89.lbc89--lbc89
[DeepGenotype.py][INFO]  ...running CRISPResso
[DeepGenotype.py][INFO]  ...parsing allele frequency table and re-calculating allele frequencies
[DeepGenotype.py][INFO]  ...done
[DeepGenotype.py][INFO]  Processing sample: HEK-nocap-CLTA-R2_ccs.lbc90--lbc90.lbc90--lbc90
[DeepGenotype.py][INFO]  ...running CRISPResso
[DeepGenotype.py][INFO]  ...parsing allele frequency table and re-calculating allele frequencies
[DeepGenotype.py][INFO]  ...done
[DeepGenotype.py][INFO]  Processing sample: HEK-nocap-CLTA-R3_ccs.lbc91--lbc91.lbc91--lbc91
[DeepGenotype.py][INFO]  ...running CRISPResso
[DeepGenotype.py][INFO]  ...parsing allele frequency table and re-calculating allele frequencies
[DeepGenotype.py][INFO]  ...done
[DeepGenotype.py][INFO]  Done processing all samples in the csv file

 

Example 1: To run MiSeq test dataset (insertion mode)

load conda, and activate the DeepGenotype conda environment

module load anaconda
conda activate DeepGenotype

run DeepGenotype in the background (and thus safe to close the terminal)

nohup python DeepGenotype.py \
--path2csv example_csv/test_INS.csv \
--path2workDir test_MiSeq_INS \
--path2fastqDir test_MiSeq_INS/fastq &

To check the terminal output (while running in the background

cat nohup.out

The completed nohup.out should look like this (only first 9 lines shown)

[DeepGenotype.py][INFO]  Genome edit type: INS
[DeepGenotype.py][INFO]  Processing sample: mNGplate19_sorted_A2_DDX6-C
[DeepGenotype.py][INFO]  ...running CRISPResso
[DeepGenotype.py][INFO]  ...parsing allele frequency table and re-calculating allele frequencies
[DeepGenotype.py][INFO]  ...done
[DeepGenotype.py][INFO]  Processing sample: mNGplate19_sorted_A3_LSM14A-N
[DeepGenotype.py][INFO]  ...running CRISPResso
[DeepGenotype.py][INFO]  ...parsing allele frequency table and re-calculating allele frequencies
[DeepGenotype.py][INFO]  ...done
...

 

Example 2: to run MiSeq test dataset (SNP mode)

load conda, and activate the DeepGenotype conda environment

module load anaconda
conda activate DeepGenotype

run DeepGenotype in the background (and thus safe to close the terminal)

nohup python DeepGenotype.py \
--path2csv example_csv/test_MiSeq_SNP.csv \
--path2workDir test_MiSeq_SNP \
--path2fastqDir test_MiSeq_SNP/fastq &

To check the terminal output (while running in the background

cat nohup.out

The completed nohup.out should look like this (only first 9 lines shown)

[DeepGenotype.py][INFO]  Genome edit type: INS
[DeepGenotype.py][INFO]  Processing sample: mNGplate19_sorted_A2_DDX6-C
[DeepGenotype.py][INFO]  ...running CRISPResso
[DeepGenotype.py][INFO]  ...parsing allele frequency table and re-calculating allele frequencies
[DeepGenotype.py][INFO]  ...done
[DeepGenotype.py][INFO]  Processing sample: mNGplate19_sorted_A3_LSM14A-N
[DeepGenotype.py][INFO]  ...running CRISPResso
[DeepGenotype.py][INFO]  ...parsing allele frequency table and re-calculating allele frequencies
[DeepGenotype.py][INFO]  ...done
...

 

Helper commands

Paginated view of fastq files

compressed

gzip -c example.fastq.gz | less

uncompressed

less example.fastq

Count the number of lines in a fastq file (divide by 4 you'll get the read count)

compressed

gzip -c example.fastq.gz | wc -l

uncompressed

cat example.fastq | wc -l

Count the number of line with a specific sequence in a fastq file

compressed

gzip -c example.fastq.gz | grep -c 'your-sequence-here'

uncompressed

cat example.fastq | grep -c 'your-sequence-here'

for matching sequences at the beginning of the line, add a ^: '^your-sequence-here'
for matching sequences at the end of the line, add a $: 'your-sequence-here$'

License

This project is licensed under the BSD 3-Clause license - see the LICENSE file for details.