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# Sphinx build info version 1 | ||
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. | ||
config: e0eb6db499003519cf5a02c49f3f533e | ||
tags: 645f666f9bcd5a90fca523b33c5a78b7 |
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.doctrees/_autosummary/precellar.utils.strip_barcode_from_fastq.doctree
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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"# Processing barcoded Fastq files\n", | ||
"\n", | ||
"You would likely encounter barcoded fastq files when working with single cell ATAC-seq data.\n", | ||
"As on early days of single cell ATAC-seq, cell barcodes are usually added to the read name of the fastq files.\n", | ||
"This notebook demonstrates how to process these barcoded fastq files." | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 1, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"import precellar" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"## Extracting cell barcodes from read names" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 2, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"name": "stdout", | ||
"output_type": "stream", | ||
"text": [ | ||
"@CCAGCACAAGCCATCCTATCGT:A00953:155:HVCHLDRXX:1:1101:1036:1031 1:N:0:1\n", | ||
"ANCTTGGATCATCAGGTTTGTCTGTAGCTGATTTATTTCTTTAAGTTTCCC\n", | ||
"+\n", | ||
"F#FFFFFFFF:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF\n", | ||
"@TAACCACTACGAATGACTGACA:A00953:155:HVCHLDRXX:1:1101:1127:1031 1:N:0:1\n", | ||
"TNCCAGGACCAGTGACCGTCACCCGCAGTAAGGATCGGGGCGGCTCCGCCA\n", | ||
"+\n", | ||
"F#:FFFFFFFFF:FFFFF:FF,F,FFFFFFFF,FFF:FFFF:FFFFFF,FF\n", | ||
"@CGATATGTAGGGGACTAATTCC:A00953:155:HVCHLDRXX:1:1101:1145:1031 1:N:0:1\n", | ||
"GNCGGATCACAAGGTCAGGAGTTCGAGACCTGGCTGGCCAACACGGTGAAA\n", | ||
"\n", | ||
"gzip: stdout: Broken pipe\n" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"!zcat R1.fq.gz | head" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 3, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"precellar.utils.strip_barcode_from_fastq(\n", | ||
" 'R1.fq.gz',\n", | ||
" 'R1_processed.fq.zst',\n", | ||
" out_barcode='I1.fq.zst',\n", | ||
" regex=\"^([ACTG]+):\",\n", | ||
" right_add=1,\n", | ||
")\n", | ||
"\n", | ||
"precellar.utils.strip_barcode_from_fastq(\n", | ||
" 'R2.fq.gz',\n", | ||
" 'R2_processed.fq.zst',\n", | ||
" regex=\"^([ACTG]+):\",\n", | ||
" right_add=1,\n", | ||
")" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 4, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"name": "stderr", | ||
"output_type": "stream", | ||
"text": [ | ||
"\u001b[90m[\u001b[0m2024-10-01T15:18:02Z \u001b[32mINFO \u001b[0m cached_path::cache\u001b[90m]\u001b[0m Starting download of https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/generic_atac.yaml\n", | ||
"\u001b[90m[\u001b[0m2024-10-01T15:18:02Z \u001b[32mINFO \u001b[0m cached_path::cache\u001b[90m]\u001b[0m Downloaded 2643 bytes\n", | ||
"\u001b[90m[\u001b[0m2024-10-01T15:18:02Z \u001b[32mINFO \u001b[0m cached_path::cache\u001b[90m]\u001b[0m New version of https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/generic_atac.yaml cached\n" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"assay = precellar.SeqSpec(\"https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/generic_atac.yaml\")" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 5, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"data": { | ||
"text/plain": [ | ||
"\n", | ||
"└── atac(153-1150)\n", | ||
" ├── atac-illumina_p5(29)\n", | ||
" ├── atac-read1(34) [↓R1(1-98)]\n", | ||
" ├── gDNA(1-1000)\n", | ||
" ├── atac-read2(34) [↑R2(1-98), ↓I1(22)]\n", | ||
" ├── atac-cell_barcode(22)\n", | ||
" └── atac-illumina_p7(24)" | ||
] | ||
}, | ||
"execution_count": 5, | ||
"metadata": {}, | ||
"output_type": "execute_result" | ||
} | ||
], | ||
"source": [ | ||
"assay" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 6, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"assay.update_read(\"R1\", fastq=\"R1_processed.fq.zst\")\n", | ||
"assay.update_read(\"I1\", fastq=\"I1.fq.zst\")\n", | ||
"assay.update_read(\"R2\", fastq=\"R2_processed.fq.zst\")" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 7, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"data": { | ||
"text/plain": [ | ||
"\n", | ||
"└── atac(153-1150)\n", | ||
" ├── atac-illumina_p5(29)\n", | ||
" ├── atac-read1(34) [↓R1(51)]\n", | ||
" ├── gDNA(1-1000)\n", | ||
" ├── atac-read2(34) [↑R2(51), ↓I1(22)]\n", | ||
" ├── atac-cell_barcode(22)\n", | ||
" └── atac-illumina_p7(24)" | ||
] | ||
}, | ||
"execution_count": 7, | ||
"metadata": {}, | ||
"output_type": "execute_result" | ||
} | ||
], | ||
"source": [ | ||
"assay" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 8, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"name": "stderr", | ||
"output_type": "stream", | ||
"text": [ | ||
"\u001b[90m[\u001b[0m2024-10-01T15:18:10Z \u001b[32mINFO \u001b[0m precellar::align\u001b[90m]\u001b[0m Counting barcodes...\n", | ||
"\u001b[90m[\u001b[0m2024-10-01T15:18:10Z \u001b[33mWARN \u001b[0m seqspec\u001b[90m]\u001b[0m Reads (R1) may contain additional bases downstream of the variable-length region, e.g., adapter sequences.\n", | ||
"\u001b[90m[\u001b[0m2024-10-01T15:18:10Z \u001b[33mWARN \u001b[0m seqspec\u001b[90m]\u001b[0m Reads (R2) may contain additional bases downstream of the variable-length region, e.g., adapter sequences.\n", | ||
"\u001b[90m[\u001b[0m2024-10-01T15:18:10Z \u001b[32mINFO \u001b[0m precellar::align\u001b[90m]\u001b[0m Found 2500 barcodes. 100.00% of them have an exact match in whitelist\n", | ||
"\u001b[90m[\u001b[0m2024-10-01T15:18:10Z \u001b[32mINFO \u001b[0m precellar::align\u001b[90m]\u001b[0m Aligning reads...\n", | ||
"\u001b[90m[\u001b[0m2024-10-01T15:18:10Z \u001b[33mWARN \u001b[0m seqspec\u001b[90m]\u001b[0m Reads (R1) may contain additional bases downstream of the variable-length region, e.g., adapter sequences.\n", | ||
"\u001b[90m[\u001b[0m2024-10-01T15:18:10Z \u001b[33mWARN \u001b[0m seqspec\u001b[90m]\u001b[0m Reads (R2) may contain additional bases downstream of the variable-length region, e.g., adapter sequences.\n", | ||
"100%|██████████| 2500/2500 [00:00<00:00, 15545.42it/s]" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"qc = precellar.align(\n", | ||
" assay, \"/data/kzhang/GRCh38/hg38.fa.gz\",\n", | ||
" modality=\"atac\",\n", | ||
" output_fragment=\"atac_fragments.tsv.zst\",\n", | ||
" num_threads=32,\n", | ||
")" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 9, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"data": { | ||
"text/plain": [ | ||
"{'frac_q30_bases_read1': 0.8179764705882353,\n", | ||
" 'frac_valid_barcode': 1.0,\n", | ||
" 'sequenced_read_pairs': 2500.0,\n", | ||
" 'frac_q30_bases_barcode': 1.0,\n", | ||
" 'frac_unmapped': 0.07640000000000002,\n", | ||
" 'sequenced_reads': 5000.0,\n", | ||
" 'frac_fragment_flanking_single_nucleosome': 0.0029791459781529296,\n", | ||
" 'frac_confidently_mapped': 0.8524,\n", | ||
" 'frac_fragment_in_nucleosome_free_region': 0.010427010923535254,\n", | ||
" 'frac_q30_bases_read2': 0.9442745098039216,\n", | ||
" 'frac_nonnuclear': 0.0128,\n", | ||
" 'frac_duplicates': 0.004940711462450593}" | ||
] | ||
}, | ||
"execution_count": 9, | ||
"metadata": {}, | ||
"output_type": "execute_result" | ||
} | ||
], | ||
"source": [ | ||
"qc" | ||
] | ||
} | ||
], | ||
"metadata": { | ||
"kernelspec": { | ||
"display_name": "Python 3", | ||
"language": "python", | ||
"name": "python3" | ||
}, | ||
"language_info": { | ||
"codemirror_mode": { | ||
"name": "ipython", | ||
"version": 3 | ||
}, | ||
"file_extension": ".py", | ||
"mimetype": "text/x-python", | ||
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"nbconvert_exporter": "python", | ||
"pygments_lexer": "ipython3", | ||
"version": "3.10.13" | ||
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"nbformat": 4, | ||
"nbformat_minor": 2 | ||
} |
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