129 lines
5.3 KiB
Markdown
129 lines
5.3 KiB
Markdown
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# HT-RNAseq - A pipeline for processing high-throughput RNA-seq data
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## Introduction
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__TODO__: Add a description of the pipeline here.
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## Test data
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As test data, we use [a DRUGseq dataset](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE176150) from the [NCBI Sequence Read Archive](https://www.ncbi.nlm.nih.gov/sra).
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The original data has been (partly) subsampled to reduce the test runtime. We used [seqtk](https://github.com/lh3/seqtk) for this with a seed of 1, e.g.:
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```bash
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seqtk sample -s1 orig/SRR14730302/VH02001614_S8_R1_001.fastq.gz 10000 > 10k/SRR14730302/VH02001614_S8_R1_001.fastq.gz
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```
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The data is available at: `gs://viash-hub-test-data/htrnaseq/v1/`:
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```
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❯ gcstree -f viash-hub-test-data/htrnaseq/v1/
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viash-hub-test-data
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└── htrnaseq
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└── v1
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├── [ 48] 2-wells.fasta
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├── [465.3K] GSE176150_metadata.csv
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├── 100k
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│ ├── SRR14730301
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│ │ ├── [8.5M] VH02001612_S9_R1_001.fastq
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│ │ └── [14.9M] VH02001612_S9_R2_001.fastq
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│ └── SRR14730302
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│ ├── [8.5M] VH02001614_S8_R1_001.fastq.gz
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│ └── [14.9M] VH02001614_S8_R2_001.fastq.gz
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├── 10k
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│ ├── SRR14730301
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│ │ ├── [845.4K] VH02001612_S9_R1_001.fastq
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│ │ └── [1.5M] VH02001612_S9_R2_001.fastq
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│ └── SRR14730302
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│ ├── [845.3K] VH02001614_S8_R1_001.fastq.gz
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│ └── [1.5M] VH02001614_S8_R2_001.fastq.gz
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└── orig
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├── [20.4G] SRR14730301
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│ └── [20.4G] SRR14730301
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├── SRR14730301
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│ ├── [9.1G] VH02001612_S9_R1_001.fastq.gz
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│ └── [22.0G] VH02001612_S9_R2_001.fastq.gz
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├── [16.9G] SRR14730302
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│ └── [16.9G] SRR14730302
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├── SRR14730302
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│ ├── [7.6G] VH02001614_S8_R1_001.fastq.gz
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│ └── [18.0G] VH02001614_S8_R2_001.fastq.gz
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├── [18.0G] SRR14730303
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│ └── [18.0G] SRR14730303
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├── SRR14730303
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│ ├── [8.1G] VH02001618_S7_R1_001.fastq.gz
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│ └── [19.2G] VH02001618_S7_R2_001.fastq.gz
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├── [16.5G] SRR14730304
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│ └── [16.5G] SRR14730304
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├── SRR14730304
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│ ├── [7.5G] VH02001700_S6_R1_001.fastq.gz
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│ └── [17.8G] VH02001700_S6_R2_001.fastq.gz
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├── [19.0G] SRR14730305
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│ └── [19.0G] SRR14730305
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├── SRR14730305
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│ ├── [8.4G] VH02001702_S5_R1_001.fastq.gz
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│ └── [20.6G] VH02001702_S5_R2_001.fastq.gz
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├── [14.6G] SRR14730306
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│ └── [14.6G] SRR14730306
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├── SRR14730306
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│ ├── [6.6G] VH02001704_S4_R1_001.fastq.gz
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│ └── [16.0G] VH02001704_S4_R2_001.fastq.gz
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├── [21.5G] SRR14730307
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│ └── [21.5G] SRR14730307
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├── SRR14730307
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│ ├── [9.6G] VH02001708_S3_R1_001.fastq.gz
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│ └── [23.2G] VH02001708_S3_R2_001.fastq.gz
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├── [20.7G] SRR14730308
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│ └── [20.7G] SRR14730308
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├── SRR14730308
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│ ├── [9.3G] VH02001710_S2_R1_001.fastq.gz
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│ └── [22.1G] VH02001710_S2_R2_001.fastq.gz
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├── [15.8G] SRR14730309
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│ └── [15.8G] SRR14730309
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└── SRR14730309
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├── [7.2G] VH02001712_S1_R1_001.fastq.gz
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└── [16.9G] VH02001712_S1_R2_001.fastq.gz
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18 directories, 37 files
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```
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The `orig` directory contains the original fastq files. The fastq files are available for 10k and 100k subsamples in the `10k` and `100k` directories, respectively.
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The `2-wells.fasta` file contains the barcodes for 2 wells.
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## Test run
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The pipeline can be run by creating a `params.yaml` file like this:
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```yaml
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param_list:
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- input_r1: "gs://viash-hub-test-data/htrnaseq/v1/100k/SRR14730301/VH02001612_S9_R1_001.fastq"
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input_r2: "gs://viash-hub-test-data/htrnaseq/v1/100k/SRR14730301/VH02001612_S9_R2_001.fastq"
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genomeDir: "gs://viash-hub-test-data/htrnaseq/v1/genomeDir/gencode.v41.star.sparse"
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barcodesFasta: "gs://viash-hub-test-data/htrnaseq/v1/2-wells.fasta"
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id: sample_one
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- input_r1: "gs://viash-hub-test-data/htrnaseq/v1/100k/SRR14730302/VH02001614_S8_R1_001.fastq"
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input_r2: "gs://viash-hub-test-data/htrnaseq/v1/100k/SRR14730302/VH02001614_S8_R2_001.fastq"
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genomeDir: "gs://viash-hub-test-data/htrnaseq/v1/genomeDir/gencode.v41.star.sparse"
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barcodesFasta: "gs://viash-hub-test-data/htrnaseq/v1/2-wells.fasta"
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id: sample_two
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```
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and then:
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```bash
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viash ns build --setup cb
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nextflow run . -main-script target/nextflow/workflows/htrnaseq/main.nf \
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-profile docker \
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-c target/nextflow/workflows/htrnaseq/nextflow.config \
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-params-file params.yaml \
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-resume \
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--publish_dir output
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```
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Or, by running `src/workflows/htrnaseq/integration_test.sh`.
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# Special Thanks
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Developed in collaboration with Data Intuitive and Open Analytics.
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