@@ -12,9 +12,13 @@ This document describes the individual rules of the pipeline for information pur
***extract_transcripts_as_bed12**
***index_genomic_alignment_samtools**
***star_rpm**
***rename_star_rpm_for_alfa**
***calculate_TIN_scores**
***salmon_quantmerge_genes**
***salmon_quantmerge_transcripts**
***generate_alfa_index**
***alfa_qc**
***alfa_qc_all_samples**
### Sequencing mode specific
***(pe_)fastqc**
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@@ -123,6 +127,9 @@ Needed for TIN score calculation and bedgraph coverage calculation.
Create stranded bedgraph coverage with STAR's RPM normalisation.
Described [here](https://ycl6.gitbooks.io/rna-seq-data-analysis/visualization.html)
STAR RPM uses SAM flags to correctly tell where the read and its mate mapped to. That is, if read1 is mapped to the plus strand, then read2 is mapped to the minus strand and STAR will count read1 and read2 to the plus strand.
This is in contrast to `bedtools genomecov -bg -split`, where the reads are assigned to the respective strand irrespective of their mates.
**Input:** .bam, .bam.bai index
**Output:** coverage bedGraphs
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@@ -131,6 +138,14 @@ Described [here](https://ycl6.gitbooks.io/rna-seq-data-analysis/visualization.ht
--outWigNorm "RPM"
#### rename_star_rpm_for_alfa
Local rule to rename and copy the stranded bedgraph coverage tracks such that they comply with [ALFA](https://github.com/biocompibens/ALFA).
The renaming to `plus.bg` and `minus.bg` depends on the library orientation, which is provided by the user in `kallisto_directionality`.
**Input:** .bg coverage tracks
**Output:** renamed and copied bedgraph files
#### 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:
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@@ -158,6 +173,33 @@ Merge the salmon quantification *transcript* results for all samples of same seq
**Output:** Two tsv files for transcript quantifications, one for tpm and one for number of reads.
#### generate_alfa_index
Create ALFA index files used for running [ALFA](https://github.com/biocompibens/ALFA) for a given organism.
**Output:** two ALFA index files, one stranded and one unstranded
#### alfa_qc
Run [ALFA](https://github.com/biocompibens/ALFA) from stranded bedgraph tracks.
The library orientation is needed as *fr-firststrand* and *fr-secondstrand*. Currently, the values from `kallisto_directionality` are re-used.
ALFA counts features in the bedgraph coverage tracks, by using the library orientation and the ALFA index files. The counts are stored in `ALFA_feature_counts.tsv`.
The main output of ALFA are two plots, `ALFA_Biotypes.pdf` and `ALFA_Categories.pdf`. They display the nucleotide distributions among the different features and their enrichment. For details see [ALFA documentation](https://github.com/biocompibens/ALFA).
**Input:** the renamed .bg files (suffixed with `out.plus.bg` and `out.minus.bg`), library orientation, the stranded ALFA index file
**Output:** ALFA_Biotypes.pdf and ALFA_Categories.pdf; ALFA_feature_counts.tsv containing table for the plots
#### alfa_qc_all_samples
Combine the output of all samples into one plot generated by [ALFA](https://github.com/biocompibens/ALFA).
**Input:** ALFA_feature_counts.tsv from each sample in `samples.tsv`
**Output:** ALFA_Biotypes.pdf and ALFA_Categories.pdf for all samples together
### 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.
