Directional RNA-seq data -which parameters to choose?

REF:

https://chipster.csc.fi/manual/library-type-summary.html

Directional RNA-seq methods are gaining popularity. Several protocols and products are available for the library preparation step, and different tools and softwares have different options to take these into account. Since this has caused a lot of confusion due to incoherent parameter naming, we try to clarify this issue a bit here.

To be able to select the right parameters for your data, first you need to know which library prep method was used when generating your data. In general, there are three types of library preps:

un-stranded
"second-strand" = directional, where the first read of the read pair (or in case of single end reads, the only read) is from the transcript strand
"first-strand" = directional, where the first read (or the only read in case of SE) is from the opposite strand.

Directional RNA-seq data -which parameters to choose?
Summary of library type protocols
(borrowed from: http://onetipperday.sterding.com/2012/07/how-to-tell-which-library-type-to-use.html)
The reads on the left are from the same strand as the transcript, and their pairs on the right are from the opposing strand. The number above the read states which read it is, the first (/1) or the second (/2). Thus, perhaps a bit unintuitively, the first case, "fr-firststrand" is such that the first read (/1) is actually from the opposing strand as the transcript, and second read (/2) is from the transcript strand.

Why is this so important? If you use wrong directionality parameter, in the read counting step the reads are considered to be from the wrong strand. This means that in the cases where there are no genes on that other strand, you won't get any hits, and if there are genes in the same location on the other strand, your reads are counted for that wrong gene.

How can I check I chose correctly? It's a good idea to check that!
Using the tool RNA-seq strandedness inference and inner distance estimation using RseQC: We added this tool under the Quality control category to help you. The tool aligns subsets of the input FASTQ files against the reference genome, and this alignment is then compared to the reference annotation to deduce the strandedness. Make sure you select the correct reference when running the tool. Check out the help page of this tool for more information!
In aligners like HISAT2 and Tophat you can also do a comparison and check the mapping rate. Take a small subset of your reads and run HISAT2/TopHat with the different parameters and compare the results, and check the log file.
In HTSeq you can also run the tool with different options and check the number of reads that are not counted for any gene (=the "no-feature reads"). (In Chipster, open file htseq-count-info.txt).

Be extra careful to assign the paired files correctly! Using these parameters assumes you are giving the files in specific order: read1, read2. In Chipster always check from the parameters window that your files are assigned correctly.

Below we list some common library preparation kits and their corresponding parameters in different tools. Is your kit missing from the list? If you have the data generated with that kit and figure out the library type, please let us know too, so we can add that kit to the list below.

Unstranded:
Information regarding the strand is not conserved (it is lost during the amplification of the mRNA fragments).
Kits:
TruSeq RNA Sample Prep kit
Parameters:
HISAT2 / TopHat / Cufflinks / Cuffdiff: library-type fr-unstranded
HTSeq: stranded -- no

Directional, first strand:
The second read (read 2) is from the original RNA strand/template, first read (read 1) is from the opposite strand. The information of the strand is preserved as the original RNA strand is degradated due to the dUTPs incorporated in the second synthesis step.
Kits:
All dUTP methods, NSR, NNSR
TruSeq Stranded Total RNA Sample Prep Kit
TruSeq Stranded mRNA Sample Prep Kit
NEB Ultra Directional RNA Library Prep Kit
Agilent SureSelect Strand-Specific
Parameters:
HISAT2 / TopHat / Cufflinks / Cuffdiff: library-type fr-firststrand
HTSeq: stranded -- reverse

Directional, second strand:
The first read (read 1) is from the original RNA strand/template, second read (read 2) is from the opposite strand. The directionality is preserved, as different adapters are ligated to different ends of the fragment.
Kits:
Directional Illumina (Ligation), Standard SOLiD
ScriptSeq v2 RNA-Seq Library Preparation Kit
SMARTer Stranded Total RNA
Encore Complete RNA-Seq Library Systems
NuGEN SoLo
Parameters:
HISAT2 / TopHat / Cufflinks / Cuffdiff: library-type fr-secondstrand
HTSeq: stranded -- yes

Note also that the --fr/--rf/--ff or "Order of mates to align" parameter in Bowtie has similar sounding parameter options: [--fr: "Forward/reverse", --rf: "Reverse/Forward", --ff: "Forward/forward"]. However, these parameters are a bit different story, as they explain how the paired end reads are oriented towards each other (-> <-, -> -> or <- ->). The default (--fr, -> <-) is appropriate for Illumina's paired-end reads: it means that read 1 appears upstream of the reverse complement of read 2, or vice versa. When running TopHat, the library-type parameter is delivered to Bowtie, so the user doesn't have to worry about that too much.

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I think the issue here is that the R and F options yield the same results. We just encountered this same issue with PE sequencing (RF give the same results as FR).

ref:

https://github.com/infphilo/hisat2/issues/61

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--fr/--rf/--ff should rarely be set, since they refer to the relative orientation of reads and basically everything these days is --fr. Mate-pairs were --rf, but you don't see those much any more.

--rna-strandedness is a very different option, since it sets how reads are expected to align against genes. Most stranded protocols in use these days follow the dUTP-method, where read #2 in a pair has the same orientation as the transcript from which it arose. So either R or RF would typically be appropriate, unless the library is unstranded. In practice, I expect this is more useful if you plan to run stringTie downstream, since then the XS auxiliary tag is set appropriately.

ref:

https://bioinformatics.stackexchange.com/questions/4074/hisat2-which-option-should-mention-for-strand-specific-library-read

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Thanks a lot for your always useful comments. I thought it was so, but then I ran into a different problem. I first aligned with the option forward --fr, and got "70% reads aligned concordantly exactly 1 time". It seemed OK. Then, noticing my mistake with the library type, ran the same fastqsanger input files with option forward --rf and got about 98% "aligned concordantly 0 times". I still cannot explain what happened. Any idea? Both times I did input first read1 then read2 on the tool form.

ref:

https://biostar.usegalaxy.org/p/27320/

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I have a pair end strand-specific library type: fr-secondstrand so could you suggest for Hisat2 it should be --fr?

There are two option in hisat2 : --rna-strandness and --fr/--rf/--ff . please suggest which option should I mention from these two.
--rna-strandness fr
-- fr

ref:

https://github.com/infphilo/hisat2/issues/109

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I'm working with RNA-seq data. For the analysis I will be using HISAT2 to align sequencing reads to the human genome GRCh38. Samples are subjected to strand-specific RNA sequencing using poly-A selection protocol and sequenced on the Illumina HiSeq 2000 system. They are paired-end reads.

I would like to know how the Hisat2 command need to be given for strand-specific option.

--rna-strandness should be RF or FR

For Hisat2 there is two things to take care of:

If its single ended data and forward stranded you need to set: -rna-strandness F If its paired end data and forward stranded you need to set: -rna-strandness FR

Similar, if its reverse stranded for SE data: -rna-strandness R or (Paired End, reverse stranded) -rna-strandness RF

You may have to check in more detail what the protocol actually does.

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Is there a possibility to know whether it is forward stranded or reverse stranded from fatsq files I have (sample1_1.fastq, sample1_2.fatsq) ?

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If you don't know if for sure, you can try using RSeQC to infer the strandedness:

http://rseqc.sourceforge.net

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Most are fr-firststrand (dUTP based methods). But yes it's good to check with infer_experiment.py from RSeQC. For fr-firststrand you should use RF.


ref:
https://www.biostars.org/p/297399/

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I also applied --rna-strandness F and --rna-strandness R respectively (with --tmo option on). My reads should be F. However, F and R gave me exactly the same output, with only diffice at " XS:A:" - one is +, the other gives - for a same read.

With this option being used, every read alignment will have an XS attribute tag: '+' means a read belongs to a transcript on '+' strand of genome. '-' means a read belongs to a transcript on '-' strand of genome.