[M::mem_pestat] (25, 50, 75) percentile: (47, 307, 448) [M::mem_pestat] low and high boundaries for computing mean and std.dev: (1, 1250) [M::mem_pestat] mean and std.dev: (284.54, 203.62) [M::mem_pestat] low and high boundaries for proper pairs: (1, 1651) [M::mem_pestat] skip orientation RF as there are not enough pairs [M::mem_pestat] skip orientation RR as there are not enough pairs [M::mem_process_seqs] Processed 320216 reads in 378.248 CPU sec, 58.330 real sec [M::mem_pestat] # candidate unique pairs for (FF, FR, RF, RR): (1, 40, 0, 1) [M::mem_pestat] skip orientation FF as there are not enough pairs [M::mem_pestat] analyzing insert size distribution for orientation FR...##Introduction BWA is a software package for mapping DNA sequences against a large reference genome, such as the human genome.Released packages can be downloaded at Source Forge.
It is recommended to run the post-processing script.My theory was that your sequences were repetitive enough that they had so many possible alignments that the aligner gave up, but that when they were aligned as pairs that the space became restricted enough that things then worked. Anyway, perhaps looking at the PE alignments in IGV would be helpful. I checked out the PE alignments in IGV, as you suggested, and noticed that there are small little clusters (~20 bp in length) of alignments with depth of 20000 reads for some of these clusters.Both read1 and read2 are overlapping in those clusters.A read may be mapped to the junction of two adjacent reference sequences.In this case, BWA-backtrack will flag the read as unmapped (0x4), but you will see position, CIGAR and all the tags. Does BWA work with ALT contigs in the GRCh38 release?
Bwa single end
It consists of three algorithms: BWA-backtrack, BWA-SW and BWA-MEM.The first algorithm is designed for Illumina sequence reads up to 100bp, while the rest two for longer sequences ranged from 70bp to a few megabases.If you have questions about BWA, you may sign up the mailing list and then send the questions to [email protected] BWA works with a variety types of DNA sequence data, though the optimal algorithm and setting may vary.You may also ask questions in forums such as Bio Star and SEQanswers. The following list gives the recommended settings: BWA-MEM is recommended for query sequences longer than ~70bp for a variety of error rates (or sequence divergence).If I take a look at the small area where some of these reads align and blast those against our viral genome I get 100% alignment.
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I am still confused as to why in SE mode I get virtually no alignment but in PE I get these clusters of alignments.
A similar issue may occur to BWA-SW alignment as well. Yes, since 0.7.11, BWA-MEM officially supports mapping to GRCh38 ALT.
BWA-backtrack and BWA-SW don't properly support ALT mapping as of now. Briefly, it is recommended to use bwakit, the binary release of BWA, for generating the reference genome and for mapping. Can I just run BWA-MEM against GRCh38 ALT without post-processing?
I used BWA mem to align some Miseq (2X300bp) reads to a human reference expecting very low mapping since human reads would be considered contaminants.
If I map read1 only I get the following output from samtools flagstat: 238834 0 in total (QC-passed reads QC-failed reads) 0 0 duplicates 147 0 mapped (0.06%:-nan%) 0 0 paired in sequencing 0 0 read1 0 0 read2 0 0 properly paired (-nan%:-nan%) 0 0 with itself and mate mapped 0 0 singletons (-nan%:-nan%) 0 0 with mate mapped to a different chr 0 0 with mate mapped to a different chr (map Q477668 0 in total (QC-passed reads QC-failed reads) 0 0 duplicates 307795 0 mapped (64.44%:-nan%) 477668 0 paired in sequencing 238834 0 read1 238834 0 read2 307704 0 properly paired (64.42%:-nan%) 307742 0 with itself and mate mapped 53 0 singletons (0.01%:-nan%) 25 0 with mate mapped to a different chr 11 0 with mate mapped to a different chr (map Q238834 0 in total (QC-passed reads QC-failed reads) 0 0 duplicates 153 0 mapped (0.06%:-nan%) 0 0 paired in sequencing 0 0 read1 0 0 read2 0 0 properly paired (-nan%:-nan%) 0 0 with itself and mate mapped 0 0 singletons (-nan%:-nan%) 0 0 with mate mapped to a different chr 0 0 with mate mapped to a different chr (map Q Hmm, that's pretty repetitive, but not enough to fully explain these results.