Documentation

A brief documentation of the pipeline rules is given in 'pipeline_documentation.md'.

ATTENTION: Descriptions of tools are copy-pasted from their respective homepages, so this documentation cannot be used in a publication.

Everyone has to check the sections on the rules they have added, as I merely tried to understand what has been done, without feedback from the rule authors. This applies especially to @katsanto, also check the input samples table description (!!!), and to @devagy74 I guess. Work by @burri0000 and @bakma had not been included at the time of writing, so the respective sections have to be added to the documentation by these guys.

I did not add the documentation to the README because I didn't want to step on anyone's toes.

This closes #60 (closed) and #57 (closed) .

pipeline_steps.md

 # RNAseq pipeline documentation
 
 ## Overview
-### General pipeline
+### General
 * read samples table
 * create log directories
 * **create_index_star**
@@ -12,7 +12,7 @@
 * **salmon_quantmerge_genes**
 * **salmon_quantmerge_transcripts**
 
-### Paired end
+### sequencing mode specific
 * **pe_fastqc**
 * **pe_remove_adapters_cutadapt**
 * **pe_remove_polya_cutadapt**
@@ -21,14 +21,7 @@
 * **pe_quantification_salmon**
 * **pe_genome_quantification_kallisto**
 
-### Single end
-* **fastqc**
-* **remove_adapters_cutadapt**
-* **remove_polya_cutadapt**
-* **map_genome_star**
-* **index_genomic_alignment_samtools**
-* **quantification_salmon**
-* **genome_quantification_kallisto**
+
 
 ## Detailed description of steps
 The pipeline consists of three snakefiles: The main Snakefile contains some general rules for the creation of indices and rules that deal with summary steps and combining of results across samples of the run. For single-end and paired-end sequencing samples there are two separate sub-snakefiles, as parameters to individual tools differ between the sequencing modes.    
@@ -36,7 +29,7 @@ Individual rules of the pipeline will be described shortly, and links to the res
 Description of paired- and single-end rules are combined, only differences will be highlighted.
 
 
-### General pipeline
+### General
 #### read samples table
 The input samples table will be read.    
 Requirements: 
@@ -65,7 +58,7 @@ sd | Estimated standard deviation of fragment length; for single-end kallisto qu
 mean | Estimated average fragment length; for single-end kallisto quantification (type=STRING or type=INT)
 multimappers | max number of multiple alignments allowed for a read: if exceeded, the read is considered unmapped; for star mapping (type=STRING or type=INT)
 soft_clip | "Local": standard local alignment with soft-clipping allowed. "EndToEnd": force end-to-end read alignment, do not soft-clip; for star mapping (type=STRING)
-pass_mode | "None": 1-pass mapping; "Basic": basic 2-pass mapping, with all 1st pass junctions inserted into thegenome indices on the fly; for star mapping (type=STRING)
+pass_mode | "None": 1-pass mapping; "Basic": basic 2-pass mapping, with all 1st pass junctions inserted into the genome indices on the fly; for star mapping (type=STRING)
 libtype | "A": automatically infer. For more info see [salmon manual](https://salmon.readthedocs.io/en/latest/salmon.html) (type=STRING)
 kallisto_directionality | "--fr-stranded":Strand specific reads, first read forward. "--rf-stranded": Strand specific reads, first read reverse; for kallisto (type=STRING)
 fq1_polya | stretch of As or Ts, depending on read orientation; for cutadapt (type=STRING)
@@ -77,100 +70,180 @@ Currently not implemented as Snakemake rule, but general statement.
 
 
 #### create_index_star
-Create index for STAR alignments. Supply the reference genome sequences (FASTA files) and annotations (GTF file), from which STAR generates genome indexes that are utilized in the 2nd (mapping) step. The genome indexes are saved to disk and need only be generated once for each genome/annotation/index size combination. [STAR manual](http://labshare.cshl.edu/shares/gingeraslab/www-data/dobin/STAR/Releases/FromGitHub/STAR-2.6.0c/doc/STARmanual.pdf)    
+Create index for STAR alignments. Supply the reference genome sequences (FASTA files) and annotations (GTF file), from which STAR generates genome indexes that are utilized in the 2nd (mapping) step. The genome indexes are saved to disk and need only be generated once for each genome/annotation/index size combination. [STAR manual](https://github.com/alexdobin/STAR/blob/master/doc/STARmanual.pdf)    
 
-Input: genome fasta file, gtf file    
-Parameters: sjdbOverhang (This is the 'index_size' specified in the input file).    
-Output: `chrNameLength.txt` will be used for STAR mapping; `chrName.txt`
+**Input:** genome fasta file, gtf file    
+**Parameters:** sjdbOverhang (This is the `index_size` specified in the samples table).    
+**Output:** chrNameLength.txt will be used for STAR mapping; chrName.txt
 
  
 #### create_index_salmon
-Create index for Salmon quantification. If you want to use Salmon in mapping-based mode, then you first have to build a salmon index for your transcriptome. This will build the mapping-based index, using an auxiliary k-mer hash over k-mers of length 31. While the mapping algorithms will make used of arbitrarily long matches between the query and reference, the k size selected here will act as the minimum acceptable length for a valid match. Thus, a smaller value of k may slightly improve sensitivty. We find that a k of 31 seems to work well for reads of 75bp or longer, but you might consider a smaller k if you plan to deal with shorter reads. [Salmon manual](https://salmon.readthedocs.io/en/latest/salmon.html)   
+Create index for Salmon quantification. If you want to use Salmon in mapping-based mode, then you first have to build a salmon index for your transcriptome. This will build the mapping-based index, using an auxiliary k-mer hash over k-mers of length 31. While the mapping algorithms will make use of arbitrarily long matches between the query and reference, the k size selected here will act as the minimum acceptable length for a valid match. Thus, a smaller value of k may slightly improve sensitivty. We find that a k of 31 seems to work well for reads of 75bp or longer, but you might consider a smaller k if you plan to deal with shorter reads. [Salmon manual](https://salmon.readthedocs.io/en/latest/salmon.html)   
 
-Input: transcriptome fasta file for transcripts to be quantified    
-Parameters: kmer length ('kmer' in the input samples table).    
-Output: salmon index, used for quantification.
+**Input:** transcriptome fasta file for transcripts to be quantified    
+**Parameters:** kmer length (`kmer` in the input samples table).    
+**Output:** salmon index, used for quantification.
 
 
 #### create_index_kallisto
 Create index for Kallisto quantification. Similar to salmon index described above. The default kmer size of 31 is used in this pipeline and thus not adaptable by the user. [Kallisto manual](https://pachterlab.github.io/kallisto/manual).    
-Input: transcriptome fasta file for transcripts to be quantified    
-Output: kallisto index, used for kallisto quantification.    
+
+**Input:** transcriptome fasta file for transcripts to be quantified    
+**Output:** kallisto index, used for kallisto quantification.    
 
 
 #### extract_transcripts_as_bed12
 Convert transcripts from gtf to bed12 format. This is needed for the TIN score calculation and doesn't require any parameters.    
-Input: gtf file    
-Output: "full_transcripts_protein_coding.bed"    
+
+**Input:** gtf file    
+**Output:** "full_transcripts_protein_coding.bed"    
 
 
 #### calculate_TIN_scores
-Given a set of BAM files and a gene annotation BED file, calculates the Transcript Integrity Number (TIN) for each transcript. [GitLab repository](https://git.scicore.unibas.ch/zavolan_group/tools/tin_score_calculation)TIN is conceptually similar to RIN (RNA integrity number) but provides transcript level measurement of RNA quality and is more sensitive to measure low quality RNA samples:
+Given a set of BAM files and a gene annotation BED file, calculates the Transcript Integrity Number (TIN) for each transcript. [GitLab repository](https://git.scicore.unibas.ch/zavolan_group/tools/tin_score_calculation). TIN is conceptually similar to RIN (RNA integrity number) but provides transcript level measurement of RNA quality and is more sensitive to measure low quality RNA samples:
 
 * TIN score of a transcript is used to measure the RNA integrity of the transcript.
 * Median TIN score across all transcripts can be used to measure RNA integrity of that "RNA sample".
 * TIN ranges from 0 (the worst) to 100 (the best). TIN = 60 means: 60% of the transcript has been covered if the reads coverage were uniform.
 * TIN will be assigned to 0 if the transcript has no coverage or covered reads is fewer than cutoff.
 
-Input: aligned reads.bam.bai, "full_transcripts_protein_coding.bed"         
-Output: TIN score tsv file
+**Input:** aligned reads.bam.bai, "full_transcripts_protein_coding.bed"         
+**Output:** TIN score tsv file
 
 #### salmon_quantmerge_genes
 Merge the salmon quantification *gene* results for all samples of same sequencing mode into a single file. Do this for tpm and number of reads separately.    
-Input: All salmon quant genes files of same seqmode   
-Output: Two tsv files for gene quantifications, one for tpm and one for number of reads.   
+
+**Input:** All salmon quant genes files of same seqmode   
+**Output:** Two tsv files for gene quantifications, one for tpm and one for number of reads.   
 
 #### salmon_quantmerge_transcripts
-Merge the salmon quantification *transcript* results for all samples of same sequencing mode into a single file. Do this for tpm and number of reads separately.    
-Input: All salmon quant transcript files of same seqmode     
-Output: Two tsv files for transcript quantifications, one for tpm and one for number of reads.   
+Merge the salmon quantification *transcript* results for all samples of same sequencing mode into a single file. Do this for tpm and number of reads separately.   
 
+**Input:** All salmon quant transcript files of same seqmode     
+**Output:** Two tsv files for transcript quantifications, one for tpm and one for number of reads.   
 
-### Sample specific rules
+
+### Sequencing mode specific rules
 #### (pe_)fastqc
 [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) aims to provide a simple way to do some quality control checks on raw sequence data coming from high throughput sequencing pipelines. It provides a modular set of analyses which you can use to give a quick impression of whether your data has any problems of which you should be aware before doing any further analysis.   
-Input: raw fastq files    
-Output: fastqc report (.txt) and several figures (.png)
 
-Same for single- and paired-end.
+**Input:** raw fastq files    
+**Output:** fastqc report (.txt) and several figures (.png)
+
+*Same for single- and paired-end.*
 
 
 #### (pe_)remove_adapters_cutadapt
-[Cutadapt](https://cutadapt.readthedocs.io/en/stable/) finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.  
-Arguments not influencable by user:    
+[Cutadapt](https://cutadapt.readthedocs.io/en/stable/) finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.   
+
+**Input:** fastq reads    
+**Parameters:** Adapters to be removed, specified by user in the columns `fq1_3p`, `fq1_5p`, `fq2_3p`, `fq2_5p` respectively.    
+**Output:** fastq files with adapters removed, reads shorter than 10nt will be discarded.    
+
+
+**Arguments not influencable by user:**        
 -e 0.1  maximum error-rate of 10%    
 -j 8    use 8 threads    
 -m 10   Discard processed reads that are shorter than 10
 -n 3    search for all the given adapter sequences repeatedly, either until no adapter match was found or until 3 rounds have been performed.    
 
-**paired end:**    
+*paired end:*    
 --pair-filter=both      filtering criteria must apply to both reads in order for a read pair to be discarded
 
-**single end:**    
+*single end:*    
 -O 1    minimal overlap of 1
 
-Input: fastq reads    
-Parameters: Adapters to be removed, specified by user in the columns 'fq1_3p', 'fq1_5p', 'fq2_3p', 'fq2_5p' respectively.    
-Output: fastq files with adapters removed, reads shorter than 10nt will be discarded.
+#### (pe_)remove_polya_cutadapt
+Here, cutadapt is used to remove poly(A) tails. 
 
+**Input:** fastq reads    
+**Parameters:** Adapters to be removed, specified by user in the columns 'fq1_polya', 'fq2_polya', respectively.    
+**Output:** fastq files with poly(A) tails removed, reads shorter than 10nt will be discarded. 
 
-#### (pe_)remove_polya_cutadapt
-Here, cutadapt is used to remove poly(A) tails. Arguments like above and additionally:    
---match-read-wildcards  This option is used to allow matching wildcard characters also within reads, because if no tail should be trimmed "XXXXXX" is specified in the samples table, which doesn't match any nucleotides, and thus nothing will be done here.    
+**Arguments like above and additionally:**    
+--match-read-wildcards This option is used to allow matching wildcard characters also within reads, because if no tail should be trimmed "XXXXXX" is specified in the samples table, which doesn't match any nucleotides, and thus nothing will be done here.    
 -n 2    search for all the given adapter sequences repeatedly, either until no adapter match was found or until 2 rounds have been performed.    
 -q 6    trim low-quality 3'ends with a cutoff of 6 nucleotides    
 
 
-**paired end:**
+*paired end:*
 --pair-filter=both      filtering criteria must apply to both reads in order for a read pair to be discarded
 
-**single end:**    
+*single end:*    
 -O 1    minimal overlap of 1
 
 #### (pe_)map_genome_star
+Spliced Transcripts Alignment to a Reference    
+[Publication](https://www.ncbi.nlm.nih.gov/pubmed/23104886).    
+[STAR manual](https://github.com/alexdobin/STAR/blob/master/doc/STARmanual.pdf).    
 
+**Input:** STAR_index, reads as .fastq.gz    
+**Parameters:**    
+* index size, specified by user in column `index_size`
+* multimappers, specified by user in column `multimappers`   
+* soft_clip, specified by user in column `soft_clip`
+* pass_mode, specified by user in column `pass_mode`     
 
-* **pe_index_genomic_alignment_samtools**
-* **pe_quantification_salmon**
-* **pe_genome_quantification_kallisto**
+**Output:** aligned reads as .bam, STAR logfile
+
+**Arguments not influencable by user:**    
+--outSAMunmapped None: do not output unmapped reads in SAM file    
+--outFilterMultimapScoreRange 0: the score range below the maximum score for multimapping alignments    
+--outSAMattributes All: NH HI AS nM NM MD jM jI MC ch    
+--outStd BAM_SortedByCoordinate:  which output will be directed to stdout (standard out)    
+--outSAMtype BAM SortedByCoordinate:   type of SAM/BAM output    
+--outFilterMismatchNoverLmax 0.04: alignment will be output only if its ratio of mismatches to *mapped* length is less than or equal to this value    
+--outFilterScoreMinOverLread 0.3: same as outFilterScoreMin, but normalized to read length (sum of mates’ lengths for paired-end reads)    
+--outFilterMatchNminOverLread 0.3:  Minimal fraction of aligned bases    
+--outFilterType BySJout: reduces the number of ”spurious” junctions     
+--outReadsUnmapped None: do not output unmapped reads.
+
+*Same for single- and paired-end.*
+
+
+#### (pe_)index_genomic_alignment_samtools
+Index the genomic alignment with [samtools index](http://quinlanlab.org/tutorials/samtools/samtools.html#samtools-index). Indexing a genome sorted BAM file allows one to quickly extract alignments overlapping particular genomic regions. Moreover, indexing is required by genome viewers such as IGV so that the viewers can quickly display alignments in each genomic region to which you navigate.    
+Needed for TIN score calculation.    
+
+**Input:** bam file    
+**Output:** bam.bai index file    
+
+*Same for single- and paired-end.*
+
+#### (pe_)quantification_salmon
+[Salmon](https://salmon.readthedocs.io/en/latest/salmon.html) is a tool for wicked-fast transcript quantification from RNA-seq data.
+
+**Input:** 
+* .fastq.gz reads, adapters and poly(A)tails removed. 
+* filtered annotation .gtf
+* salmon index, from **create_index_salmon**    
+
+**Parameters:**  libType, specified by user as `libtype`    
+**Output:** gene and transcript quantifications
+
+**Arguments not influencable by user:**    
+--seqBias: [Correct for sequence specific biases](https://salmon.readthedocs.io/en/latest/salmon.html#seqbias)    
+--validateMappings: Enables selective alignment of the sequencing reads when mapping them to the transcriptome. This can improve both the sensitivity and specificity of mapping and, as a result, can [improve quantification accuracy](https://salmon.readthedocs.io/en/latest/salmon.html#validatemappings).    
+--writeUnmappedNames: write out the names of reads (or mates in paired-end reads) that do not map to the transcriptome.
+
+*additionally for single end:*    
+**Parameters:** 
+* --fldMean: fragment length, user specified as `mean`
+* --fldSD: fragment length SD, user specified as `sd`   
+
+
+
+#### (pe_)genome_quantification_kallisto
+[kallisto](http://pachterlab.github.io/kallisto/manual.html) is a program for quantifying abundances of transcripts from RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads. It is based on the novel idea of pseudoalignment for rapidly determining the compatibility of reads with targets, without the need for alignment.    
+
+**Input:** 
+* .fastq.gz reads, adapters and poly(A)tails removed.
+* kallisto index, from **create_index_kallisto** 
+
+**Parameters:** directionality, `kallisto_directionality` from samples table    
+
+**Output:** Pseudoalignment .sam file
 
+*additionally for single end:*    
+* -l: fragment length, user specified as `mean`
+* -s: fragment length SD, user specified as `sd` 
\ No newline at end of file