I will provide example from my own dataset using latest version of HISAT2
HISAT2 summary stats:
Total pairs: 11587225
Aligned concordantly or discordantly 0 time: 4464083 (38.53%)
Aligned concordantly 1 time: 2195620 (18.95%)
Aligned concordantly >1 times: 4877336 (42.09%)
Aligned discordantly 1 time: 50186 (0.43%)
Total unpaired reads: 8928166
Aligned 0 time: 8019048 (89.82%)
Aligned 1 time: 304653 (3.41%)
Aligned >1 times: 604465 (6.77%)
Overall alignment rate: 65.40%
Description
1. Total pairs: 11587225
Total reads = 11587225 * 2 = 23174450 (matches total number of reads in the sample)
2. Aligned concordantly or discordantly 0 time: 4464083 (38.53%)
These are unmapped reads : 4464083 * 2 (paired end) = 8928166
( 8928166 / 23174450 (Total reads) ) * 100 ~ 38.53%
3. Aligned concordantly 1 time: 2195620 (18.95%)
These are uniquely mapped reads : 2195620 * 2 (paired end) = 4391240
( 4391240 / 23174450 (Total reads) ) * 100 ~ 18.95%
4. Aligned concordantly >1 times: 4877336 (42.09%)
These are multi mapped reads : 4877336 * 2 = 9754672
( 9754672 / 23174450 (Total reads) ) * 100 ~ 42.09%
5.Aligned discordantly 1 time: 50186 (0.43%)
Discordant aligned : 50186 * 2 = 100372
( 100372 / 23174450 (Total reads) ) * 100 ~ 0.43%
6. Total unpaired reads: 8928166
These are not paired reads
Aligned 0 time: 8019048 (89.82%)
(8019048 / 8928166 ) * 100 = 89.82% i.e. 89% of the unpaired reads did not align at all
Aligned 1 time: 304653 (3.41%)
(304653 / 8928166 ) * 100 = 3.41% i.e. 3.41% of the unpaired reads aligned once
Aligned >1 times: 604465 (6.77%)
(604465 / 8928166 ) * 100 = 6.77% i.e. 6.77% of the unpaired reads are multi mapped
7. Overall alignment rate: 65.40%
Calculation as explained below
PAIRED READS
Aligned concordantly 1 time: (2195620 * 2 = 4391240)
Aligned concordantly >1 times: (4877336 *2 = 9754672)
Aligned discordantly 1 time: (50186 * 2 = 100372)
UNPAIRED READS
Aligned 1 time: 304653
Aligned >1 times: 604465
Total = 4391240 + 9754672 + 100372 + 304653 + 604465 = 15155402
Overall Alignment Rate = (15155402 / 23174450) * 100 = 65.40%
This means the total mapping (alignment) ratio of RNA reads to the genome that you used. This is not bad result, but it can improve. You can use the latest genome. The alignment ratio depends on several things;
I guess you can use samtools to figure out genomic coordination of RNA reads, or you ca use one of visualization tools to see where these RNA reads mapped in the genome.
Thanks.based on your comment H have some questions: 1- I use GSE58708 dataset. I have to say that before alignment, I use FastQC software for quality control. how can I understand quality of read? 2-My data is Single-End.how can I find type for RNA sequencing strand? 3-how can I find that i have rRNA in my reads?
Based on FastQC report, for instance, you can remove short reads.For this you can use trimmomatic. Please check options of trimmomatic to see what you can do. you can also remove adaptor sequences if you have used illumina. For sequencing strand, you should check strand type if you have downloaded this data from a database or to someone who performed sequencing. For rRNA check, you can do blast remotely, meaning searching your RNA reads to NCBI human RNA database using -remote option. Please have a look blast manual to search remotely and to search against to only human RNA database by specifying organism in your blast command.
finally, you should check number of reads in your fastq file and compare hisat2 results below: