Matt:LabNotes/2015-3-19

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Revision as of 01:07, 24 March 2015 by >Mzcai (→‎Conclusion)
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CA12k_Nov2014_V4 in vitro Capture Sequencing Analysis

  • With in vitro Capture data, DARTFISH gene counts can be normalized and compared to other methods such as RNA-Seq

Mapping MiSeq reads to Oligo Sequences

Convert Probelist to Fasta File

CA12kNov2014_Probelist2Fasta.pl

 bowtie2-build CA12k_Nov2014_V4_H1H2.fa CA12k_Nov2014_V4_H1H2
 bowtie2 --phred33 -x CA12k_Nov2014_V4_H1H2 -q MC-20150121_CA12kNov2014_V4gDNA-1.R1.fastq > CA12kNov2014_V4gDNA_R1_H1H2.sam 2> CA12kNov2014_V4gDNA_stderr.txt &
 2573875 reads; of these:
 2573875 (100.00%) were unpaired; of these:
   115745 (4.50%) aligned 0 times
   2458058 (95.50%) aligned exactly 1 time
   72 (0.00%) aligned >1 times
 95.50% overall alignment rate
 bowtie2 --phred33 -x CA12k_Nov2014_V4_H1H2 -q MC-20150121_CA12kNov2014_V4cDNA-2.R1.fastq > CA12kNov2014_V4cDNA_R1_H1H2.sam 2> CA12kNov2014_V4cDNA_stderr.txt &
 2425688 reads; of these:
 2425688 (100.00%) were unpaired; of these:
   110744 (4.57%) aligned 0 times
   2314903 (95.43%) aligned exactly 1 time
   41 (0.00%) aligned >1 times
 95.43% overall alignment rate
 samtools view -bS CA12kNov2014_V4gDNA_R1_H1H2.sam | samtools sort - CA12kNov2014_V4gDNA_R1_H1H2_sorted
 samtools view -h -F 4 CA12kNov2014_V4gDNA_R1_H1H2_sorted.bam > CA12kNov2014_V4gDNA_R1_H1H2_sorted_filtered.sam
 samtools view -bS CA12kNov2014_V4cDNA_R1_H1H2.sam | samtools sort - CA12kNov2014_V4cDNA_R1_H1H2_sorted
 samtools view -h -F 4 CA12kNov2014_V4cDNA_R1_H1H2_sorted.bam > CA12kNov2014_V4cDNA_R1_H1H2_sorted_filtered.sam

Count # of Reads Aligned to each Probe

CountReadsPer_Gene_Probe.pl

  • Verified with grep -c 'Gene' CA12kNov2014_V4gDNA_R1_H1H2_sorted_filtered.sam and grep -c 'Probe' CA12kNov2014_V4gDNA_R1_H1H2_sorted_filtered.sam
    • Differences in counts are accounted for by strings in header lines

Compare with Blue's BA8 bulk RNA-seq Gene Counts

RNA-Seq Data on Genome-miner

  • mapped_genes.fpkm_tracking.txt
    • /media/LTS_33T/RL_LTS33T/201404_201405_7Samples_BulkNucleiBatch1-20140623_Expt146/STAR/RL-BA8-sec9-n-N702-15May14_S2_mapped
      • neuronal nuclei
    • /media/LTS_33T/RL_LTS33T/201404_201405_7Samples_BulkNucleiBatch1-20140623_Expt146/STAR/RL-BA8-sec9-t-N701-15May14_S1_mapped
      • bulk tissue

Analysis in R

Results

  • Since 40 (1%) probes have target regions that are highly repetitive (softmasked in reference genome; lowercase), they can have very high false in vitro capture counts and are removed from analysis
DARTFISH vs Sorted Neuronal Nuclei

File:BA8 logDARTFISH vs logRNASeqBulkN masked regression.jpeg

  • Including probes targeting masked regions

File:BA8 logDARTFISH vs logRNASeqBulkN regression.jpeg

DARTFISH vs Bulk Tissue

File:BA8 logDARTFISH vs logRNASeqBulkT masked regression.jpeg

  • Including probes targeting masked regions

File:BA8 logDARTFISH vs logRNASeqBulkT regression.jpeg

Conclusion

  • in situ DARTFISH gene counts correlates better with bulk tissue RNA-Seq
  • While removing probes that target masked regions is most certainly correct, it barely improves correlation with RNA-Seq
  • Need to design 40 suppressor oligos to completely suppress
    • Maybe only 10-20 to suppress the probes that have astronomical in situ counts