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README.md

PolyASite Workflow

Pipeline to infer poly(A) site clusters through processing of 3' end sequencing libraries prepared according to various protocols. The pipeline was used for the generation of the PolyASite atlas.

Pipeline schematic

Further information on the implemented processing can be found below and on PolyASite. Pipeline DAG

Requirements

The pipeline was tested on an HPC environment managed by Slurm.

Conda environment

We recommend that to use a Conda environment that contains the necessary software.

The environment was created with:

conda env create \
      --name polyA_atlas_pipeline \
      --file snakemake_run_env_requirements.yaml

Activate the environment with:

source activate polyA_atlas_pipeline

Deactivate the environment with:

source deactivate

Prerequisites

The pipeline has three central elements: the Snakefile, a config file, and a sample table:

  • The Snakefile does not need to be changed, modified or updated unless bugs, intended updates etc., require changes.
  • The config file (called config.yaml) needs to be adjusted according to your needs. It requires a set of samples, an organism, a genome version and an annotation version. Organism and genome/annotation versions are edited directly in the config file. Samples are provided indirectly by indicating the path to the sample table. An example for a config file can be found here: tests/EXAMPLE_config.yaml.
    Please see below in the Run section part how you can also run Snakemake without modifying the config file, instead specifying the required information as arguments to command line parameters.
  • The sample table lists sample-specific information required for the successful run of the pipeline. Follow the format in tests/EXAMPLE_samples.tsv and include one line for each sample to be processed.

Run the pipeline

Local

Local execution is not recommended and should only be used for testing purposes.

snakemake \
    -p \
    --use-singularity \
    --singularity-args "--bind ${PWD}" \
    --configfile config.yaml \
    &>> run_update.Organism_genomeVersion_annotationVersion.log

Slurm

snakemake \
    -p \
    --use-singularity \
    --singularity-args "--bind ${PWD}" \
    --configfile config.yaml \
    --cluster-config cluster_config.json \
    --jobscript jobscript.sh \
    --cores 500 \
    --local-cores 10 \
    --cluster "sbatch --cpus-per-task {cluster.threads} \
              --mem {cluster.mem} --qos {cluster.queue} \
              --time {cluster.time} -o {params.cluster_log} \
              -p [NODE_ID] --export=JOB_NAME={rule} \
              --open-mode=append" \
    &>> run_update.Organism_genomeVersion_annotationVersion.log

General notes on running the pipeline

Instant config changes

If you do not want to change the base config file, you can also specify the appropriate values in the Snakemake command itself, e.g.:

snakemake \
    -p \
    --use-singularity \
    --singularity-args "--bind ${PWD}" \
    --configfile config.yaml \
    --config organism=HomoSapiens genome=GRCh38.90 atlas.release_name:r2.0 -- \
    &>> run_update.Organism_genomeVersion_annotationVersion.log

Running only parts of the pipeline

With the Snakemake option --until you can specify a target rule for running the pipeline. This is useful if you only want to run a subset of rules. For example, the pipeline includes the creation of bigWig- and track-info files for display of data in the UCSC genome browser. If you don't need these files, run with --until complete_clustering. For examples see here.

Generate graph for preprocessing of individual sample of specific protocol

When a target file is provided in the Snakemake command, Snakemake will run the pipeline only until the point at which the desired file is created. This can be used to generate overview graphs on the processing of samples from specific protocols to check their processing steps. For example:

snakemake \
    -p \
    --configfile config.yaml \
    --dag \
    samples/counts/SRX517313_GRCh38.90.ip3pSites.out \
    | dot \
        -T png \
    > graph.SAPAS.png

Protocol-specific notes

3' READS

Pre-processing involves:

  1. Filtering of reads based on the 5' configuration
  2. 3' adapter trimming
  3. Reverse complementing
  4. 3' trimming of potentially remaining As from the poly(A) tail

Only reads that start with a specified number of random nucleotides and two Ts are considered, with the number of random nucleotides having to be extracted from the corresponding GEO/SRA entries or publication. See here for more information.

According to this paper, sequencing can be done in sense and antisense direction. The samples that are currently processed here were sequenced in antisense direction. Future samples should be checked carefully in order to decide whether current settings are appropriate.

SAPAS

Pre-processing involves:

  1. Combined 5' and 3' adapter trimming
  2. Trimming of remaining Cs at the 3' end (they are a result of template switching reverse transcription)
  3. Reverse complementing

Sequencing libraries are prepared such that sequencing can be done either in antisense direction (Illumina) or in sense direction (454). So far, only samples from Illumina sequencing have been processed. If "sense direction samples" need to be processed, the pipeline must be adapted accordingly.

In the supplementary material of the APASdb paper, the authors state that they only consider reads that have the expected 5' linker sequence 5'-TTTTCTTTTTTCTTTTTT-3'. However, manual comparison of the first reads from an old sample (SRX026584) with one from the mentioned publication revealed that the abundance of this linker is very low in the samples from the APASdb publication. Therefore, we have decided not to be too strict with the 5' linker. Very often, only poly(T)s are found: therefore, for the newer samples only a stretch of Ts is given as 5' adapter and trimmed together with the 3' adapter.

A-seq2

Processing is done according to this protocol, but without using the first nucleotide as barcode information.

A-seq

Pre-processing involves:

  1. 3' adapter trimming
  2. Valid reads filtering with additional consideration of a maximum read length (see below).

3'-seq (Mayr)

Pre-processing involves:

  1. 3' adapter trimming
  2. Additional trimming of As and Ns at the 3' end
  3. Valid reads filtering with additional consideration of a maximum read length (see below).

PAS-Seq

Pre-processing involves:

  1. Trimming of poly(T) at the 5' end
  2. 3' adapter trimming
  3. Trimming of additional Cs at the 3' end
  4. Reverse complementing

DRS

Current pre-processing involves:

  1. Reverse complementing
  2. Correction by 1 nt to obtain the true 3' end position (note that this is directly encoded in the Snakefile, not the config file.)

The protocol facilitates direct sequencing of the RNA 3' end. Due to an initial T-fill step that involves the incorporation of a blocking nucleotide (anything except for a T), sequencing begins actually one nucleotide upstream of the RNA 3'-most nucleotide. Therefore, a correction of 1 in the downstream direction of the read's reverse complement is necessary to obtain the 3' end (See "Extended Experimental Procedures" in Ozsolak et al for more info.

PolyA-seq

Pre-processing involves:

  1. 3' adapter trimming
  2. Reverse complementing

3P-Seq

Pre-processing involves:

  1. Reverse complementing if necessary
  2. Filtering reads: only proceed with reads with at least 2 As at the 3' end
  3. Remove additional As at the 3' end that might remain from the poly(A) tail

Note that processing for samples of this protocol is sample-specific. In particular, only a subset of samples requires reverse complementing, and hence, each sample has to be checked manually to infer whether reverse complementing is required or not. Once, this information is provided in the design file, the pipeline will process samples accordingly.

An easy way to check whether a file needs to be revese complemented is to count the occurence of the poly(A) signal in the first reads and their revese complements:

zcat samples/GSM1268942/GSM1268942.fa.gz \
    | head -n10000 \
    | tail -n1000 \
    | grep TTTATT | wc -l
zcat samples/GSM1268942/GSM1268942.fa.gz \
    | head -n10000 \
    | tail -n1000 \
    | grep AATAAA | wc -l

Comparing these numbers should give a clear prefernce for one of the two signals.

2P-Seq

Pre-processing involves:

  1. 3' adapter trimming
  2. Reverse complementing

Maximum read length

Samples prepared with protocols 3'-seq (Mayr) and A-seq have a restriction on the maximum read length for processed reads to count as valid. As these protocols require sequencing in the sense direction, the length restriction ensures that the 3' end of the transcript is reached.

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