Compatible with C1 (Fluidigm) read data from SRA??

Hi,

I have extensively read the documentation and still have questions:

• Could you confirm alignments of C1 data (Fluidigm) is valid input to Velocyto’s run stage?
• Further, I have no valid cell barcodes available to me from the SRA sample FASTQs (short read archive). I don’t think that will be a problem, even though you warn against this.
• Please confirm the “ValidatedIntrons10X” logic option (default) is still appropriate for handling C1 data, in spite of the fact that it is not a Drop-Seq based technology?

Thanks!

[benslack19]

Hi Velocyto team,

Thanks for making this package and for the responsiveness here on GitHub. I’m seeing some errors that are similar to things that others have posted like here, here and this thread. I’m trying to follow some suggestions but still running into an error. I’m running C1 SMARTer chemistry so there are no UMIs.

Velocyto version: 0.17.13

Command: velocyto run_smartseq2 $BAM /home/singlecell/refs/gtf/Homo_sapiens.GRCh38.94.gtf

Error section of output: 2018-10-02 15:32:09,803 - DEBUG - Read first 0 million reads Traceback (most recent call last): File "/home/singlecell/anaconda3/bin/velocyto", line 11, in <module> sys.exit(cli()) File "/home/singlecell/anaconda3/lib/python3.6/site-packages/click/core.py", line 722, in __call__ return self.main(*args, **kwargs) File "/home/singlecell/anaconda3/lib/python3.6/site-packages/click/core.py", line 697, in main rv = self.invoke(ctx) File "/home/singlecell/anaconda3/lib/python3.6/site-packages/click/core.py", line 1066, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/home/singlecell/anaconda3/lib/python3.6/site-packages/click/core.py", line 895, in invoke return ctx.invoke(self.callback, **ctx.params) File "/home/singlecell/anaconda3/lib/python3.6/site-packages/click/core.py", line 535, in invoke return callback(*args, **kwargs) File "/home/singlecell/anaconda3/lib/python3.6/site-packages/velocyto/commands/run_smartseq2.py", line 71, in run_smartseq2 samtools_memory=1, dump=dump, verbose=verbose, additional_ca=additional_ca) File "/home/singlecell/anaconda3/lib/python3.6/site-packages/velocyto/commands/_run.py", line 229, in _run results = exincounter.count(bamfile_cellsorted, multimap=multimap) # NOTE: we would avoid some millions of if statements evalution if we write two function count and count_with output File "/home/singlecell/anaconda3/lib/python3.6/site-packages/velocyto/counter.py", line 754, in count for r in self.iter_alignments(bamfile, unique=not multimap): File "/home/singlecell/anaconda3/lib/python3.6/site-packages/velocyto/counter.py", line 256, in iter_alignments if unique and read.get_tag("NH") != 1: File "pysam/libcalignedsegment.pyx", line 2392, in pysam.libcalignedsegment.AlignedSegment.get_tag File "pysam/libcalignedsegment.pyx", line 2434, in pysam.libcalignedsegment.AlignedSegment.get_tag KeyError: "tag 'NH' not present"

I’m guessing you would ask about the BAM file so here it is: $SAMTOOLS view $BAMsorted | head

output: M02294:378:000000000-BFB2P:1:1107:27209:11999 99 NM_001087 943 100 72M = 1107 236 GTTCCTTTCAGTACATGGATAGGGCTTCCCTGCTTCAGGTCCCAAATCCTGATGGTCCCATCTTCATAGCCT CCCCCGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG XA:i:1 MD:Z:2C69 NM:i:1 ZW:f:1 M02294:378:000000000-BFB2P:1:1111:22606:4490 99 NM_001087 1006 100 72M = 1051 118 TCTAAGCCTACCACAGCTCTCTTCCCATCAGGGAGGACTCGGCCACAGGTGGCTGGGCAGTTGGGACCCTGG CCCCCGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG XA:i:2 MD:Z:2A0T68 NM:i:2 ZW:f:1 M02294:378:000000000-BFB2P:1:2101:11803:4213 99 NM_001087 1006 100 72M = 1051 118 TCTAAGCCTACCACAGCTCTCTTCCCATCAGGGAGGACTCGGCCACAGGTGGCTGGGCAGTTGGGACCCTGG CCCCCGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG XA:i:2 MD:Z:2A0T68 NM:i:2 ZW:f:1 M02294:378:000000000-BFB2P:1:1111:22606:4490 147 NM_001087 1051 100 73M = 1006 -118 CAGGTGGCTGGGCAGTTGGGACCCTGGAAGGTCTTGCAGTCACCATTCGGGACTTTCCACATCCAGGTGTTGC GGGGGGGGGGFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGCC XA:i:0 MD:Z:73 NM:i:0 ZW:f:1 M02294:378:000000000-BFB2P:1:2101:11803:4213 147 NM_001087 1051 100 73M = 1006 -118 CAGGTGGCTGGGCAGTTGGGACCCTGGAAGGTCTTGCAGTCACCATTCGGGACTTTCCACATCCAGGTGTTGC GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGCC XA:i:0 MD:Z:73 NM:i:0 ZW:f:1 M02294:378:000000000-BFB2P:1:1107:27209:11999 147 NM_001087 1107 100 72M = 943 -236 CCACATCCAGGTGTTGCCGTCAGCTGTGCCCGCCAACAGGACAGGTGCCCGAGGATGCCACTCCATCCACTC GGGGGFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGCC XA:i:0 MD:Z:72 NM:i:0 ZW:f:1 M02294:378:000000000-BFB2P:1:1103:9435:17386 99 NM_001605 408 100 72M = 640 305 TGCCTGTGGCCTGTGCAGACACATCCTTGCCACCACCTTTACCGTCCATCAAGCCTGACACCTGCTGCACCC CCCCCGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG XA:i:0 MD:Z:72 NM:i:0 ZW:f:1 M02294:378:000000000-BFB2P:1:1103:9435:17386 147 NM_001605 640 100 73M = 408 -305 GCCGCTCTCCATCTCCAGGATGACAAGAGGCTGGTTGGGGTTGCTGTCGATGAACTGCTTCGTCTTCTCTAAC GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGCC XA:i:0 MD:Z:73 NM:i:0 ZW:f:1 M02294:378:000000000-BFB2P:1:1108:16377:3308 99 NM_001605 2159 100 72M = 2205 119 TCTCCCAGGGACTGGACGACAACATCCACTAACGTAGCAAAGAAGCCCCTGCTGGCATTGAGCTTTTCATGG CCCCCGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG XA:i:0 MD:Z:72 NM:i:0 ZW:f:1 M02294:378:000000000-BFB2P:1:2114:22144:16145 99 NM_001605 2159 100 72M = 2205 119 TCTCCCAGGGACTGGACGACAACATCCACTAACGTAGCAAAGAAGCCCCTGCTGGCATTGAGCTTTTCATGG CCCCCGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFFGGGGGGGGGGGGGGGGG XA:i:0 MD:Z:72 NM:i:0 ZW:f:1

I appreciate any assistance.

Best, Ben

[cap76]

Having same problem at the moment … did you figure out a solution?