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Stable RNA processing product analyzer

Project description

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Stable RNA processing product analyzer

Tool to predict, quantify and characterize stable RNA processing products from RNA-seq data.

Overview

Starpa workflow is divided into multiple consecutive tasks which can be executed separately, as a freely chosen successive subsets or all tasks at once in sequential order. This adds flexibility to the tool to use as an input RNA-seq data in various state of processing. For example Starpa can handle raw data in FastQ format, but also trimmed reads (FastQ format) or aligned reads in SAM format.

Both paired-end (PE) and single-end (SE) sequencing reads are accepted as an input.

In addition, the tool is highly configurable and can handle multiple libraries in parallel manner (multiprocessing).

Tasks are following:

  • trim

Cutadapt is used to trim low quality 3’ end of the reads followed by adapter removal from 3’ end of the reads.

In case of SE, the reads where 3’ adapter was not trimmed are excluded. This ensures that 3’ end of the read is stable RNA processing products is estimated with higher confidence.

  • align

Bowtie2 is used to align reads to the genome. All matches to the genome are recorded.

  • sam_sort

From aligned reads the unmapped and discordantly mapped reads are discarded. In addition, only the reads belonging to best stratum (class of alignment score) are retained while alignments with lower alignments score are excluded.

  • pseudoSE

Alignments with too many mismatches and reads with too many genomic alignments are discarded. All other reads get NH tag (if not present) describing the number of reported alignments. Sequence and quality fields of secondary alignments are filled with sequence and quality data. In the end the PE reads are converted to pseudo SE reads to ease subsequent analysis steps.

  • identify

Flaimapper2 is used to predict stable RNA processing products. To ensure prediction of all processing products which share start or end positions, the reads are fractionated according to their length. Subsequently, Flaimmper2 is run on each fraction of reads separately and the predicted processing products are filtered by the read count (estimation by Flaimapper-2) exceeding threshold set. The filtered predicted processing products are quantified more precisely via bedtools intersect.

  • cluster

Quantified processing products are filtered once again by the read counts (bedtools intersect) exceeding threshold and by relative coverage (average coverage of reads assigned to processing products divided by average coverage of all reads aligned to the positions of processing products). Next, the processing products from all libraries analysed are combined (identifying unique species) and clustered.

Clustering is two step process:

  1. clustering by overlap.

As the prediction of processing products by Flaimapper-2 is probabilistic, the predicted ends of the processing products in different libraries might slightly vary, as also the true ends. Therefore, the predicted processing products which do largely overlap and have some bases (adjustable) not overlapping are clustered and representative processing products for clusters are selected.

  1. clustering by sequence

As a majority of genomes contain repeating regions (repeat regions, rRNA operons, some tRNA genes etc) reads can be mapped to multiple positions resulting multiple processing products consisting from the same or similar set of reads. To reduce the number of identical processing products they are clustered by sequence identity via CDI-HIT-EST. Still the genomic matches of particular reads can be in genomic regions with different surrounding sequence/context (eg. different genes) therefore clustering solely based on sequence identity can result loss of information. To avoid it the predicted processing products which cluster by sequence identity has to be supported by the clustering (again via CDI-HIT-EST) of the contigs they overlap with and representative processing product for the clusters are selected.

In addition, the contigs are identified and wig formatted files (containing coverage data of individual libraries) are created.

  • quantify

Representative processing products will be quantified using bedtools intersect in every library. Additional characteristics will be gathered (relative coverage, coverage at single position level, consensus sequence, quality of consensus sequence, genomic sequence, uniqueness). Quantification data is also converted to read per million of mapped reads (RPM), RPM of biotype and RPM of biotype groups.

Installation

pip install --user starpa

Requirements

Starpa is depending on following tools which have to be installed in your system:

Python3.4+, cutadapt, bowtie2, samtools, Flaimapper-2, bedtools, CDI-HIT-EST.

Python3 requires following packages which will be installed (if missing) during the installation of starpa:

pyfaidx, docopt, schema

Compatibility

OS:

Starpa is compatible with UNIX like operating systems.

Input:

  1. Colorspace reads are not supported.
  2. Both paired-end (PE) and single-end (SE) reads are supported.

Usage

Usage of starpa is as follows:

Usage:
    starpa      [-hv]
    starpa -s <start_task> -e <end_task> -c <parameter_file> -i <input>
    -o <output>

Arguments:

    <start_task>        task to start with
    <end_task>          tast to end with
    <config_file>       configuration file
    <input>             input folder
    <output>            output folder
Options:
    -v, --version
    -h, --help
    -s <start_task>, --start=<start_task>
    -e <end_task>, --end=<end_task>
    -c <config_file>, --config=<config_file>
    -i <input_folder>, --input=<input_folder>
    -o <output_folder>, --output=<output_folder>

Tasks

Starpa work-flow is divided into multiple consecutive tasks which can be executed:

  • separately
  • as a freely chosen successive subsets
  • all at once in sequential order

Tasks in sequential order:

trim, align, sam_sort, pseudoSE, identify, cluster, quantify

Configuration file

Configuration file is used to set various parameters which allow to adjust the performance of the work-flow according to the user needs and input data. The description of each parameter is given in the file itself.

Configuration file states also the location of following files:

adapter files - adapter sequencies in fasta format

genome file - genome sequence in fasta format

annotation file - in GFF or GFF3 format.

“flaimapper parameter file” - described in more deteil here. Given Flaimapper-2 parameters file is adjusted to be suitable to predict processing products with rather defined ends.

“library_file” - describing libraries to be analysed.

“library_file” is a tabular file containing:
  1. the name of the libraries
  2. conditions they are derived from and
  3. identifier of replicate

(note that all three columns are separated by tab)

#Library number        Sample  Replicate
library1       LB OD 0.4       I
library2       LB OD 0.4       II

Configuration file, “flaimapper parameter file” and “library_file” are available in:

src/starpa/data

Input folder

While running a single or multiple tasks, the input folder has to contain specific data required for the first task. For the following task the preceding tasks will prepare proper data.

Each task has different requirements for the input data:

  • trim
Sequencing data in FastQ format.
Can be in PE or SE format which has to be indicated in configuration file .
FastQ files can be compressed as “.gz”, “.bz2” or “.xz”.
  • align
Trimmed and cleaned reads in FastQ format.
Can be in PE or SE format which has to be indicated in configuration file .
FastQ files can be compressed as “.gz” (requires bowtie2.3.1+)
  • sam_sort
Aligned reads in SAM format.
Can be in PE or SE format which has to be indicated in configuration file .
BAM format is not currently supported.
  • pseudoSE
Aligned reads in SAM format.
Can be in PE or SE format which has to be indicated in configuration file .
File can not be sorted by position.
BAM format is not currently supported.
  • identify
Aligned SE or pseudoSE reads in SAM format.
Reads require NH tag to describe the number of reported alignments.
BAM format currently not supported.
  • cluster
Identified and quantified predicted processing products in BED format
(quantification at column #6).
folder bam:
Aligned SE or pseudoSE reads in BAM format.
Reads require NH tag to describe the number of reported alignments.
If task “quantify” will be also executed:
Additional input folder (given by parameter “quantify_sam_file_location”):
Aligned SE or pseudoSE reads in SAM format
(BAM format currently not supported).
Reads require NH tag to describe the number of reported alignments.
  • quantify
Predicted processing products in BED format (preferentially representatives form clustering).
Additional input folder (given by parameter “quantify_sam_file_location”):
Aligned SE or pseudoSE reads in SAM format (BAM format currently not supported).
Reads require NH tag to describe the number of reported alignments.

Output folder

Output folder will contain parameter folder:

parameters/
       eg. config.txt                  -       copy of configuration file
       arguments.txt                   -       command line arguments
       eg. libraries.txt               -       copy of library file
       eg. parameters.dev-2-100-2.txt  -       copy of Flaimapper-2 parameter file

Each task creates a subfolder with its name containing specific output of the task.

XXX - library name
strand - For or Rev
Y - order number of fragmented read group
  • trim
trim_info/
       XXX_triminfo.log        -       log of task
       XXX_triminfo.error      -       collected errors during trimming

PE:
discard/
       XXX_1_short.fq          -       forward reads discared while being too short after
                                       trimming
       XXX_2_short.fq          -       reverse reads discared while being too short after
                                       trimming

XXX_trim_1.fq                  -       trimmed forward reads
XXX_trim_2.fq                  -       trimmed reverse reads

SE:
discard/
       XXX_short.fq            -       reads discarded while being too short after
                                       trimming
       XXX_untrimmed.fq        -       reads discarded while having no adapter trimmed

XXX_trim.fq                    -       trimmed reads
  • align
align_info/
       XXX_aligninfo.log       -       log of task

XXX.sam                        -       aligned reads
  • sam_sort
sort_info/
       XXX_sortinfo.log        -       log of task

XXX_unmapped.sam               -       unmapped reads
XXX_sort.sam                   -       processed reads
  • pseudoSE
pseudoSE_info/
       XXX_pseudoSEinfo.log            -       log of task

mismatched/
       XXX_pseudoSE_mismatch.sam       -       reads discarded while having too many
                                               mismatches

too_many_matches/
       XXX_pseudoSE_multimatch.sam     -       reads discarded while haveing too many
                                               genomic matches

XXX_pseudoSE.sam                       -       processed reads

If oligoA allowed:
oligoA/
       XXX-oligoA-mm_pseudoSE.sam      -       reads with 3' oligoA (non-genome
                                               encoded) which would have otherwise
                                               discarded
       XXX-oligoA-pseudoSE.sam         -       reads with 3' oligoA (non-genome
                                               encoded)
  • identify
flaimapper/
       flaimapper_info/
               XXX/
                       XXX_strand_Y_flaimapper.information     -       log of flaimapper

       flaimapper_temp/
               XXX/
                       XXX_strand_Y_flaimapper.tab             -       flaimapper predicitons

bam/
       XXX_strand.bam                                          -       strand-wise sorted reads
                                                                       from input
       XXX_strand.bam.bai                                      -       index of of bam file
       XXX_strand.sam                                          -       NOT NEEDED

identify_info/
        XXX_strand_identifyinfo.log                            -       log of task

XXX_strand_pp.BED                                              -       NOT NEEDED
XXX_strand_pp_counted.BED                                      -       predicted processing
                                                                       products with
                                                                       quantification
  • cluster
cd_hit_est/
       pp_cd_hit_est.info              -       log of sequence identity based clustering
                                               of combined and overlap clustered predicted
                                               processing products via CD-HIT-EST
       pp_combined.cdhit               -       genomic sequence of combined and overlap
                                               clustered predicted processing products
       pp_combined.cdhit.clstr         -       clusters of combined and overlap clustered
                                               predicted processing products created via
                                               CD-HIT-EST

contigs/
       XXX_contigs.BED                 -       list of contigs identified
       XXX/
               contig_name.fasta       -       sequences of all reads belonging to the
                                               corresponding contigs
               contig_name.sam         -       all reads belonging to the
                                               corresponding contigs

contigs_meta/
       combined_contigs_meta.BED       -       combined contigs to be used to create
                                               metacontigs from all libraries
       XXX_contigs_meta.BED            -       list of contigs to be used to created
                                               metacontigs
       metacontig_cd_hit_est.info      -       log of sequence identity based clustering
                                               of metacontigs via CD-HIT-EST
       metacontigs.cdhit               -       genomic sequence of metacontigs
       metacontigs.cdhit.clstr         -       clusters of metacontigs created via
                                               CD-HIT-EST
       metacontigs.BED                 -       list of metacontigs in bed format
       pp_to_metacontig.BED            -       combined and overlap clustered predicted
                                               processing product match with metacontigs
                                               in BED-like format

mpileup/
       XXX_strand_mpileup.info         -       log of bedtools mpileup

wig/
       XXX_strand.wig                  -       strand specific absolute read coverage
       XXX_strand_RPM.wig              -       strand specific relative read coverage
                                               as read per million mapped reads (RPM)

pp_clusterinfo.log                     -       log of task
pp_unique.library_info                 -       combined predicted processing
                                               products and the origins of libraries
pp_combined.BED                        -       representatives of combined and overlap
                                               clustered predicted processing products
                                               in BED format
pp_combined.cluster                    -       overlap clusters of combined predicted
                                               processing products
pp_combined.library_info               -       representatives of combined and overlap
                                               clustered predicted processing
                                               products and the origins of libraries
pp_metacontig.BED                      -       representatives of predicted processing
                                               products from pp_combined.BED clustered
                                               by sequence identity supported by
                                               metacontig clustering in BED format
pp_metacontig.cluster                  -       sequence identity clusters of predicted
                                               processing products from pp_combined.BED
                                               supported by metacontig clustering
  • quantify
libraries/                                     -       data in library wise
       XXX.biotype_annotation.statistics       -       read alignement statistics
                                                       by annotation biotypes
       XXX.gene_annotation.statistics          -       read alignement statistics
                                                       by genes
       pp_metacontig_XXX_counted.BED           -       absolute quantification of
                                                       predicted processing products
                                                       in BED format

collected.annotation2.statistics               -       combined alignement     statistics
                                                       by annotation biotypes
pp_metacontig_biotype.BED                      -       predicted processing products
                                                       with biotype in BED-like format
pp_metacontig_biotype_match.BED                -       predicted processing products
                                                       match with genes in BED-like
                                                       format
pp_metacontig_counts_total.tsv                 -       absolute quantification of
                                                       predicted processing products
                                                       in BED format
pp_metacontig_counts_RPM.tsv                   -       relative quantification of
                                                       predicted processing products
                                                       as read per million mapped reads
                                                       (RPM) in BED format
pp_metacontig_counts_biotype_RPM.tsv           -       relative quantification of
                                                       predicted processing products
                                                       as RPM of biotype in BED format
pp_metacontig_counts_groupped_biotype_RPM.tsv  -       relative quantification of
                                                       predicted processing products
                                                       as RPM of biotype groups in BED
                                                       format
pp_metacontig_cons_qual.tsv                    -       quality of consensus sequence
                                                       of predicted processing products
                                                       expressed as frequency of the most
                                                       abundant base in a given position
pp_metacontig_cons_seq.tsv                     -       consensus sequence of predicted
                                                       processing products
pp_metacontig_coverage.tsv                     -       coverage of reads assigned to
                                                       predicted processing products
                                                       at single position level
pp_metacontig_genomic_seq.tsv                  -       genomic sequence of predicted
                                                       processing products
pp_metacontig_rel_cov.tsv                      -       relative coverage of predicted
                                                       processing products
pp_metacontig_uniqness.tsv                     -       mean number of genomic genomic
                                                       matches of reads assigned
                                                       to the predicted processing
                                                       products

To do

Authors

starpa was written by Hannes Luidalepp

Project details


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