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exceRpta computational exRNA-seq
analysis pipelineRob Kitchen
Yale 2015 - 04 - 23
1
Extracellular RNA Communication
NIH Common Fund
> data management> reference profiles> exRNA biogenesis > exRNA biomarker > exRNA therapy
currently 30 funded projects
exRNA.org2
exRNA-seq analysis software
3
small RNA-seqanalysis toolkit
exceRpt
quantification (RPM) ofmiRNA, tRNA, piRNA, snoRNA, circularRNA,
& long transcript fragments
long RNA-seqanalysis toolkit
RSEQTools
quantification (RPKM) of [multi-exon] transcripts
agenda1. exceRpt smallRNA-seq analysis suite
- filtering, QC, and alignment- quantification & normalisation - visualisations- differential expression (soon)
2. use-case involving 345 samples
3. downstream analysis - miRNA-mRNA targets from miRTarBase- network analysis - enrichment analysis- pathway analysis
exRNA-seq analysis software
5
small RNA-seqanalysis toolkit
exceRpt
quantification (RPM) ofmiRNA, tRNA, piRNA, snoRNA, circularRNA,
& long transcript fragments
long RNA-seqanalysis toolkit
RSEQTools
quantification (RPKM) of [multi-exon] transcripts
for a typical cellular sample…
99% pass adapter removal
1% map to calibrator oligos
1% fail adapter removal
3% rRNA contamination
88% map to host genome
75% map to known miRNAs
7% taken on toexogenous
smRNA mapping12%
novel smRNAs? contaminants?
all smRNA-seq reads
1. remove 3’ adapters
2. map to calibrator oligos
3. map to 45S & 5S rRNA
4. map to host genome
smRNA-seqanalysis workflow
1%tRNA, snoRNApiRNA, Rfam
• exRNA samples typically much noisier
• cascade of read-alignment steps mitigates contamination6
.fq.gz.fq .sra
sequenced read (50nt)
smallRNA (~20-30nt) adapter (~20-30nt)AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC
optional: map to spike-in library
map to UniVec contaminants
read length analysisfastQC
map to tRNAs, piRNAs, & gencode
map to host genome (hg19 hg38 mm10)
sRN
AB
ench
map to endogenous miRNAs
map to 45S, 5S, & mitochondrial rRNAs
unmapped reads
unmapped reads
unmapped reads
preprocessing filtering QC
input
endogenousalignment
unmapped reads
map to exogenous miRNAs
exogenousalignment
map to all genomes in ensembl & NCBI
• automatic pre-processing and QC of sequence reads
• absolute quantitation by quantification of exogenous spike-in sequences
• explicit rRNA filtering & QC
• quantify many different smallRNA types
• choice of 3 end-points
exceRpt
unmapped reads
unmapped reads
standard formats
remove adapters + primers
for reads >15nt
map using bowtie2
hierarchical mapping
using bowtie
choreographed by sRNABench
map using STAR
read-quality filter
1
2
31 2 3
effect of filtering
• what happens to alignments when we individually remove upstream libraries?
• gencode appears to be a subset of the repetitive elements
• quality filter, UniVec, and repetitive elements have the largest impact
100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
0.0% 10.3% 10.3% 10.3% 10.3% 10.3% 10.3% 10.3% 10.3%
0.0% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1%
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
7.0% 0.0% 6.4% 6.4% 6.4% 6.4% 6.4% 6.4% 6.4%
4.2% 3.8% 0.0% 3.8% 3.8% 3.8% 3.8% 3.8% 3.8%
88.8% 85.8% 83.3% 79.5% 79.5% 79.5% 79.5% 79.5% 79.5%
65.2% 62.3% 62.5% 58.8% 58.8% 58.8% 58.8% 58.8% 58.8%
52.3% 47.9% 47.9% 48.5% 48.5% 48.5% 48.5% 48.5% 48.5%
0.9% 0.9% 0.9% 0.9% 0.9% 0.9% 0.9% 0.9% 0.9%
0.4% 0.4% 0.4% 0.0% 0.4% 0.4% 0.4% 0.4% 0.4%
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
0.1% 0.2% 0.2% 0.1% 0.0% 0.1% 0.1% 0.1% 0.1%
0.1% 0.1% 0.1% 0.1% 0.0% 0.1% 0.1% 0.1% 0.1%
4.6% 4.8% 4.5% 3.9% 3.8% 0.0% 3.7% 3.7% 3.7%
3.9% 5.8% 4.6% 3.5% 3.5% 0.0% 3.4% 3.4% 3.4%
1.5% 1.8% 2.3% 1.3% 1.2% 4.7% 0.0% 1.2% 1.2%
1.2% 1.2% 1.3% 1.0% 1.0% 4.2% 0.0% 1.0% 1.0%
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
20.7% 19.8% 18.4% 18.4% 18.4% 18.7% 19.4% 18.4% 18.4%
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
20.7% 19.8% 18.4% 18.4% 18.4% 18.6% 19.4% 18.4% 18.4%
1.4% 2.0% 1.3% 1.3% 1.3% 1.4% 1.7% 1.3% 1.3%exogenous_genomes
input_to_exogenous_genomes
miRNA_exogenous_sense
input_to_miRNA_exogenous
circularRNA_antisense
circularRNA_sense
repetitiveElement_antisense
repetitiveElement_sense
gencode_antisense
gencode_sense
piRNA_antisense
piRNA_sense
tRNA_antisense
tRNA_sense
miRNA_antisense
miRNA_sense
genome
reads_used_for_alignment
rRNA
UniVec_contaminants
calibrator
failed_homopolymer_filter
failed_quality_filter
successfully_clipped
input
SRR822433_1_noQualFilter
SRR822433_2_noUniVec
SRR822433_3_noRiboRNA
SRR822433_4_notRNA
SRR822433_5_nopiRNA
SRR822433_6_noGencode
SRR822433_7_noRE
SRR822433_8_noCirc
SRR822433_FullPipeline
Sample
Stage
0.00
0.25
0.50
0.75
1.00ReadFraction
bone marrow kidney liver lung ovary pancreas placenta skin temporal neocortex
exogenous_genomesinput_to_exogenous_genomes
miRNA_exogenous_senseinput_to_miRNA_exogenous
circularRNA_antisensecircularRNA_sense
repetitiveElement_antisenserepetitiveElement_sense
gencode_antisensegencode_sense
piRNA_antisensepiRNA_sense
tRNA_antisensetRNA_sense
miRNA_antisensemiRNA_sense
genomereads_used_for_alignment
rRNAUniVec_contaminants
calibratorfailed_homopolymer_filter
failed_quality_filtersuccessfully_clipped
input
SRR
5786
11SR
R57
8612
SRR
5786
13SR
R57
8614
SRR
5786
16SR
R57
8617
SRR
5786
18SR
R57
8619
SRR
5786
21SR
R57
8622
SRR
5786
23SR
R57
8624
SRR
5786
25SR
R57
8626
SRR
0702
30SR
R07
0232
SRR
0702
34SR
R07
0236
SRR
0702
38SR
R07
0240
SRR
0702
42SR
R07
0244
SRR
0702
46SR
R07
0248
SRR
0396
11
SRR
0396
12
SRR
0396
13
SRR
0396
24
SRR
0396
25
SRR
3726
12SR
R37
2614
SRR
3726
16SR
R37
2618
SRR
3726
20SR
R37
2622
SRR
3726
24SR
R37
2626
SRR
3726
28SR
R37
2630
SRR
3726
32SR
R37
2634
SRR
3726
36SR
R37
2638
SRR
3726
40SR
R37
2642
SRR
3726
44SR
R37
2646
SRR
3726
48SR
R37
2652
SRR
3726
54SR
R37
2656
SRR
3726
57SR
R37
2660
SRR
3726
62SR
R37
2664
SRR
3726
66SR
R37
2668
SRR
3726
70SR
R37
2672
SRR
8361
66SR
R83
6167
SRR
8361
68SR
R83
6169
SRR
8361
70SR
R83
6171
SRR
8361
72SR
R83
6173
SRR
8361
74SR
R83
6175
SRR
8361
76SR
R83
6177
SRR
8716
09
SRR
8716
52
SRR
8716
71
SRR
8733
81
SRR
8734
01
SRR
8734
10
SRR
8224
52SR
R82
2453
SRR
8224
54SR
R82
2455
SRR
8224
56SR
R82
2457
SRR
8224
58SR
R82
2459
SRR
3308
81SR
R33
0882
SRR
3308
83SR
R33
0884
SRR
3308
85SR
R33
0886
SRR
3308
87SR
R33
0888
SRR
3308
89SR
R33
0890
SRR
3308
91SR
R33
0892
SRR
3308
93SR
R33
0894
SRR
3308
95SR
R33
0896
SRR
3308
97SR
R33
0898
SRR
3308
99SR
R33
0900
SRR
3309
01SR
R33
0902
SRR
3309
03SR
R33
0904
SRR
3309
05SR
R33
0906
SRR
3309
07SR
R33
0908
SRR
3309
09SR
R33
0910
SRR
3309
11SR
R33
0912
SRR
3309
13SR
R33
0914
SRR
3309
15SR
R33
0916
SRR
3309
17SR
R33
0918
SRR
3309
19SR
R33
0920
SRR
3309
21SR
R33
0922
SRR
3309
23SR
R82
8708
SRR
8287
09SR
R82
8710
SRR
8287
11SR
R82
8712
SRR
8287
13SR
R82
8714
SRR
8287
15SR
R82
8716
SRR
8287
17SR
R82
8718
SRR
8287
19SR
R82
8720
SRR
8287
21SR
R82
8722
SRR
8287
23SR
R82
8724
SRR
8287
26
ID
Stag
e
0.00
0.25
0.50
0.75
1.00ReadFraction
effect of filtering
• what happens to alignments when we individually remove upstream libraries?
• gencode appears to be a subset of the repetitive elements
• quality filter, UniVec, and repetitive elements have the largest impact
100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
0.0% 10.3% 10.3% 10.3% 10.3% 10.3% 10.3% 10.3% 10.3%
0.0% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1%
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
7.0% 0.0% 6.4% 6.4% 6.4% 6.4% 6.4% 6.4% 6.4%
4.2% 3.8% 0.0% 3.8% 3.8% 3.8% 3.8% 3.8% 3.8%
88.8% 85.8% 83.3% 79.5% 79.5% 79.5% 79.5% 79.5% 79.5%
65.2% 62.3% 62.5% 58.8% 58.8% 58.8% 58.8% 58.8% 58.8%
52.3% 47.9% 47.9% 48.5% 48.5% 48.5% 48.5% 48.5% 48.5%
0.9% 0.9% 0.9% 0.9% 0.9% 0.9% 0.9% 0.9% 0.9%
0.4% 0.4% 0.4% 0.0% 0.4% 0.4% 0.4% 0.4% 0.4%
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
0.1% 0.2% 0.2% 0.1% 0.0% 0.1% 0.1% 0.1% 0.1%
0.1% 0.1% 0.1% 0.1% 0.0% 0.1% 0.1% 0.1% 0.1%
4.6% 4.8% 4.5% 3.9% 3.8% 0.0% 3.7% 3.7% 3.7%
3.9% 5.8% 4.6% 3.5% 3.5% 0.0% 3.4% 3.4% 3.4%
1.5% 1.8% 2.3% 1.3% 1.2% 4.7% 0.0% 1.2% 1.2%
1.2% 1.2% 1.3% 1.0% 1.0% 4.2% 0.0% 1.0% 1.0%
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
20.7% 19.8% 18.4% 18.4% 18.4% 18.7% 19.4% 18.4% 18.4%
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
20.7% 19.8% 18.4% 18.4% 18.4% 18.6% 19.4% 18.4% 18.4%
1.4% 2.0% 1.3% 1.3% 1.3% 1.4% 1.7% 1.3% 1.3%exogenous_genomes
input_to_exogenous_genomes
miRNA_exogenous_sense
input_to_miRNA_exogenous
circularRNA_antisense
circularRNA_sense
repetitiveElement_antisense
repetitiveElement_sense
gencode_antisense
gencode_sense
piRNA_antisense
piRNA_sense
tRNA_antisense
tRNA_sense
miRNA_antisense
miRNA_sense
genome
reads_used_for_alignment
rRNA
UniVec_contaminants
calibrator
failed_homopolymer_filter
failed_quality_filter
successfully_clipped
input
SRR822433_1_noQualFilter
SRR822433_2_noUniVec
SRR822433_3_noRiboRNA
SRR822433_4_notRNA
SRR822433_5_nopiRNA
SRR822433_6_noGencode
SRR822433_7_noRE
SRR822433_8_noCirc
SRR822433_FullPipeline
Sample
Stage
0.00
0.25
0.50
0.75
1.00ReadFraction
bone marrow kidney liver lung ovary pancreas placenta skin temporal neocortex
exogenous_genomesinput_to_exogenous_genomes
miRNA_exogenous_senseinput_to_miRNA_exogenous
circularRNA_antisensecircularRNA_sense
repetitiveElement_antisenserepetitiveElement_sense
gencode_antisensegencode_sense
piRNA_antisensepiRNA_sense
tRNA_antisensetRNA_sense
miRNA_antisensemiRNA_sense
genomereads_used_for_alignment
rRNAUniVec_contaminants
calibratorfailed_homopolymer_filter
failed_quality_filtersuccessfully_clipped
input
SRR
5786
11SR
R57
8612
SRR
5786
13SR
R57
8614
SRR
5786
16SR
R57
8617
SRR
5786
18SR
R57
8619
SRR
5786
21SR
R57
8622
SRR
5786
23SR
R57
8624
SRR
5786
25SR
R57
8626
SRR
0702
30SR
R07
0232
SRR
0702
34SR
R07
0236
SRR
0702
38SR
R07
0240
SRR
0702
42SR
R07
0244
SRR
0702
46SR
R07
0248
SRR
0396
11
SRR
0396
12
SRR
0396
13
SRR
0396
24
SRR
0396
25
SRR
3726
12SR
R37
2614
SRR
3726
16SR
R37
2618
SRR
3726
20SR
R37
2622
SRR
3726
24SR
R37
2626
SRR
3726
28SR
R37
2630
SRR
3726
32SR
R37
2634
SRR
3726
36SR
R37
2638
SRR
3726
40SR
R37
2642
SRR
3726
44SR
R37
2646
SRR
3726
48SR
R37
2652
SRR
3726
54SR
R37
2656
SRR
3726
57SR
R37
2660
SRR
3726
62SR
R37
2664
SRR
3726
66SR
R37
2668
SRR
3726
70SR
R37
2672
SRR
8361
66SR
R83
6167
SRR
8361
68SR
R83
6169
SRR
8361
70SR
R83
6171
SRR
8361
72SR
R83
6173
SRR
8361
74SR
R83
6175
SRR
8361
76SR
R83
6177
SRR
8716
09
SRR
8716
52
SRR
8716
71
SRR
8733
81
SRR
8734
01
SRR
8734
10
SRR
8224
52SR
R82
2453
SRR
8224
54SR
R82
2455
SRR
8224
56SR
R82
2457
SRR
8224
58SR
R82
2459
SRR
3308
81SR
R33
0882
SRR
3308
83SR
R33
0884
SRR
3308
85SR
R33
0886
SRR
3308
87SR
R33
0888
SRR
3308
89SR
R33
0890
SRR
3308
91SR
R33
0892
SRR
3308
93SR
R33
0894
SRR
3308
95SR
R33
0896
SRR
3308
97SR
R33
0898
SRR
3308
99SR
R33
0900
SRR
3309
01SR
R33
0902
SRR
3309
03SR
R33
0904
SRR
3309
05SR
R33
0906
SRR
3309
07SR
R33
0908
SRR
3309
09SR
R33
0910
SRR
3309
11SR
R33
0912
SRR
3309
13SR
R33
0914
SRR
3309
15SR
R33
0916
SRR
3309
17SR
R33
0918
SRR
3309
19SR
R33
0920
SRR
3309
21SR
R33
0922
SRR
3309
23SR
R82
8708
SRR
8287
09SR
R82
8710
SRR
8287
11SR
R82
8712
SRR
8287
13SR
R82
8714
SRR
8287
15SR
R82
8716
SRR
8287
17SR
R82
8718
SRR
8287
19SR
R82
8720
SRR
8287
21SR
R82
8722
SRR
8287
23SR
R82
8724
SRR
8287
26
ID
Stag
e
0.00
0.25
0.50
0.75
1.00ReadFraction
• what happens if we run the smallRNA libraries through the pipeline as if they were reads?
• miRNAs include all species, but most are highly conserved
• 1/20 piRNAs are rRNA
mappability 100.0% 100.0% 100.0% 100.0% 100.0%100.0% 100.0% 100.0% 100.0% 100.0%0.0% 0.0% 0.0% 0.0% 0.0%0.3% 0.3% 0.3% 0.0% 0.0%NA% NA% NA% NA% NA%0.0% 0.0% 0.0% 0.0% 0.0%0.1% 0.2% 0.1% 5.0% 0.0%99.6% 99.5% 99.6% 95.0% 100.0%75.5% 75.5% 73.9% 94.9% 84.2%32.5% 32.4% 27.7% 0.0% 0.0%0.6% 0.6% 0.3% 0.0% 0.0%0.0% 0.0% 0.0% 0.2% 84.2%0.0% 0.0% 0.0% 0.0% 0.0%0.0% 0.0% 0.0% 94.6% 0.0%0.0% 0.0% 0.0% 0.1% 0.0%7.8% 7.7% 8.3% 0.0% 12.3%4.9% 4.9% 5.8% 0.0% 3.2%8.1% 7.9% 7.5% 0.0% 0.5%8.9% 9.1% 7.4% 0.0% 25.8%0.0% 0.0% 0.0% 0.0% 0.0%0.0% 0.0% 0.0% 0.0% 0.0%18.7% 18.7% 20.8% 0.0% 0.0%13.6% 13.6% 14.9% 0.0% 0.0%1.4% 1.4% 1.4% 0.0% 0.0%1.2% 1.2% 1.4% 0.0% 0.0%exogenous_genomes
input_to_exogenous_genomesmiRNA_exogenous_sense
input_to_miRNA_exogenouscircularRNA_antisense
circularRNA_senserepetitiveElement_antisense
repetitiveElement_sensegencode_antisense
gencode_sensepiRNA_antisense
piRNA_sensetRNA_antisense
tRNA_sensemiRNA_antisense
miRNA_sensegenome
reads_used_for_alignmentrRNA
UniVec_contaminantscalibrator
failed_homopolymer_filterfailed_quality_filter
clippedinput
miRBase21_hg19_FullPipeline
miRBase21_hg38_FullPipeline
miRBase21_mm10_FullPipeline
piRNAs_hg38_FullPipeline
tRNAs_hg38_FullPipeline
Sample
Stage
0.00
0.25
0.50
0.75
1.00ReadFraction
100.0% 100.0% 100.0% 100.0% 100.0%100.0% 100.0% 100.0% 100.0% 100.0%0.0% 0.0% 0.0% 0.0% 0.0%0.3% 0.3% 0.3% 0.0% 0.0%NA% NA% NA% NA% NA%0.0% 0.0% 0.0% 0.0% 0.0%0.1% 0.2% 0.1% 5.0% 0.0%99.6% 99.5% 99.6% 95.0% 100.0%75.5% 75.5% 73.9% 94.9% 84.2%32.5% 32.4% 27.7% 0.0% 0.0%0.6% 0.6% 0.3% 0.0% 0.0%0.0% 0.0% 0.0% 0.2% 84.2%0.0% 0.0% 0.0% 0.0% 0.0%0.0% 0.0% 0.0% 94.6% 0.0%0.0% 0.0% 0.0% 0.1% 0.0%7.8% 7.7% 8.3% 0.0% 12.3%4.9% 4.9% 5.8% 0.0% 3.2%8.1% 7.9% 7.5% 0.0% 0.5%8.9% 9.1% 7.4% 0.0% 25.8%0.0% 0.0% 0.0% 0.0% 0.0%0.0% 0.0% 0.0% 0.0% 0.0%18.7% 18.7% 20.8% 0.0% 0.0%13.6% 13.6% 14.9% 0.0% 0.0%1.4% 1.4% 1.4% 0.0% 0.0%1.2% 1.2% 1.4% 0.0% 0.0%exogenous_genomes
input_to_exogenous_genomesmiRNA_exogenous_sense
input_to_miRNA_exogenouscircularRNA_antisense
circularRNA_senserepetitiveElement_antisense
repetitiveElement_sensegencode_antisense
gencode_sensepiRNA_antisense
piRNA_sensetRNA_antisense
tRNA_sensemiRNA_antisense
miRNA_sensegenome
reads_used_for_alignmentrRNA
UniVec_contaminantscalibrator
failed_homopolymer_filterfailed_quality_filter
clippedinput
miRBase21_hg19_FullPipeline
miRBase21_hg38_FullPipeline
miRBase21_mm10_FullPipeline
piRNAs_hg38_FullPipeline
tRNAs_hg38_FullPipeline
Sample
Stage
0.00
0.25
0.50
0.75
1.00ReadFraction
mappability
• what happens if we run the smallRNA libraries through the pipeline as if they were reads?
• miRNAs include all species, but most are highly conserved
• 1/20 piRNAs are rRNA
total reads by biotype
12
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IG_D_geneIG_J_gene
IG_J_pseudogeneTR_J_pseudogene
circularRNAtranscribed_unitary_pseudogene
translated_unprocessed_pseudogeneTR_J_gene
IG_C_pseudogeneTR_C_gene
translated_processed_pseudogeneTR_V_pseudogene
IG_C_geneIG_V_pseudogene
pseudogeneIG_V_gene
3prime_overlapping_ncrnanon_coding
non_stop_decaypolymorphic_pseudogene
Mt_rRNATR_V_gene
rRNAtranscribed_processed_pseudogene
unitary_pseudogeneknown_ncrna
tRNAtranscribed_unprocessed_pseudogene
exogenous_miRNAsense_overlapping
unprocessed_pseudogeneTEC
sense_intronicMt_tRNA
processed_pseudogenemisc_RNA
snRNAsnoRNA
nonsense_mediated_decayexogenous_genomes
antisenseprocessed_transcript
piRNAretained_intron
lincRNARE
protein_codingmiRNA
1e−02 1e−01 1e+00 1e+01 1e+02 1e+03 1e+04 1e+05 1e+06 1e+07readCount
biotype
13
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IG_D_geneIG_J_gene
IG_J_pseudogeneTR_J_pseudogene
circularRNAtranscribed_unitary_pseudogene
translated_unprocessed_pseudogeneTR_J_gene
IG_C_pseudogeneTR_C_gene
translated_processed_pseudogeneTR_V_pseudogene
IG_C_geneIG_V_pseudogene
pseudogeneIG_V_gene
3prime_overlapping_ncrnanon_coding
non_stop_decaypolymorphic_pseudogene
Mt_rRNATR_V_gene
rRNAtranscribed_processed_pseudogene
unitary_pseudogeneknown_ncrna
tRNAtranscribed_unprocessed_pseudogene
exogenous_miRNAsense_overlapping
unprocessed_pseudogeneTEC
sense_intronicMt_tRNA
processed_pseudogenemisc_RNA
snRNAsnoRNA
nonsense_mediated_decayexogenous_genomes
antisenseprocessed_transcript
piRNAretained_intron
lincRNARE
protein_codingmiRNA
1e−02 1e−01 1e+00 1e+01 1e+02 1e+03 1e+04 1e+05 1e+06 1e+07readCount
biotype
●
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●
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●
●
●
IG_D_geneIG_J_gene
IG_J_pseudogeneTR_J_pseudogene
circularRNAtranscribed_unitary_pseudogene
translated_unprocessed_pseudogeneTR_J_gene
IG_C_pseudogeneTR_C_gene
translated_processed_pseudogeneTR_V_pseudogene
IG_C_geneIG_V_pseudogene
pseudogeneIG_V_gene
3prime_overlapping_ncrnanon_coding
non_stop_decaypolymorphic_pseudogene
Mt_rRNATR_V_gene
rRNAtranscribed_processed_pseudogene
unitary_pseudogeneknown_ncrna
tRNAtranscribed_unprocessed_pseudogene
exogenous_miRNAsense_overlapping
unprocessed_pseudogeneTEC
sense_intronicMt_tRNA
processed_pseudogenemisc_RNA
snRNAsnoRNA
nonsense_mediated_decayexogenous_genomes
antisenseprocessed_transcript
piRNAretained_intron
lincRNARE
protein_codingmiRNA
1e−02 1e−01 1e+00 1e+01 1e+02 1e+03 1e+04 1e+05 1e+06 1e+07readCount
biotype
●
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IG_D_geneIG_J_gene
IG_J_pseudogeneTR_J_pseudogene
circularRNAtranscribed_unitary_pseudogene
translated_unprocessed_pseudogeneTR_J_gene
IG_C_pseudogeneTR_C_gene
translated_processed_pseudogeneTR_V_pseudogene
IG_C_geneIG_V_pseudogene
pseudogeneIG_V_gene
3prime_overlapping_ncrnanon_coding
non_stop_decaypolymorphic_pseudogene
Mt_rRNATR_V_gene
rRNAtranscribed_processed_pseudogene
unitary_pseudogeneknown_ncrna
tRNAtranscribed_unprocessed_pseudogene
exogenous_miRNAsense_overlapping
unprocessed_pseudogeneTEC
sense_intronicMt_tRNA
processed_pseudogenemisc_RNA
snRNAsnoRNA
nonsense_mediated_decayexogenous_genomes
antisenseprocessed_transcript
piRNAretained_intron
lincRNARE
protein_codingmiRNA
1e−02 1e−01 1e+00 1e+01 1e+02 1e+03 1e+04 1e+05 1e+06 1e+07readCount
biotype
• large contribution from miRNA and mRNA
• also some signal from exogenous sequences
total reads by biotype
exceRpt @ Genboree
• extremely simple to use (1 input, 1 output)
• can process multiple samples in parallel
• very customisable (choice of smRNA libs, calibrators, etc)14
input
output
• exceRpt output from multiple samples can be combined, compared, and tested for differential abundance
• features: - intuitive QC visualisations - filtering & normalisation - differential expression
• processed expression data are excel, R, matlab, & geneSpring compatible
downstream analysis
15
0e+00
1e+07
2e+07
3e+07
4e+07
0 50 100 150read length (nt)
# re
ads
SRR330912SRR330913SRR330914SRR330915SRR330916SRR330917SRR330918SRR330919SRR330920SRR330921SRR330922SRR330923SRR372611SRR372612SRR372613SRR372614SRR372615SRR372616SRR372617SRR372618SRR372619SRR372620SRR372621SRR372622SRR372623SRR372624SRR372625SRR372626SRR372627SRR372628SRR372629SRR372630SRR372631SRR372632SRR372633SRR372634SRR372635SRR372636SRR372637SRR372638SRR372639SRR372640
read−length distributions
read length
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1e−03
1e+00
1e+03
1e+06
sample
Rea
ds p
er m
illion
(RPM
)
miRNA abundance distributions (RPM)
miRN
A RPM
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1e−02
1e+01
1e+04
1e+07
sample
Rea
d co
unt
miRNA abundance distributions (raw counts)
miRN
A count
agenda1. exceRpt smallRNA-seq analysis suite
- filtering, QC, and alignment- quantification & normalisation - visualisations- differential expression (soon)
2. use-case involving 345 samples
3. downstream analysis - miRNA-mRNA targets from miRTarBase- network analysis - enrichment analysis- pathway analysis
17
Downstream Analyses: OverviewPathways
Genb
oree
Focused set of
interactions
All known interactions
PD vs PDD diff exp Burgos K., et al. (2014) PLoS ONE
18
1. Query Interactions: Genboree
19
2. Network Analysis: Cytoscape
Upregulated and downregulated in PD with dementia relative to PD alone. Burgos K., et al. (2014) PLoS ONE
20
2. Network Analysis: Cytoscape
55207
6632
8382
11080
1647
233903162
5294
23266
4148
11215
23396
64781
80204
163081
3976
10019
55809
221035
54726
57038
5305
9945
26258
57608
5048
5324
4170
65059
285672
5743
4839
1993
6938
595 517277431
54332
10160
4211
3720
599596
3308
60436
3491
55591
26523
23670
110044306
7832
80223
56144
2355465987
10159
3725
4001
57532
22908
1843
57142
23224
6097
51167
4038
54877
3821
23219
23345
3598
57502
248
5459
3785
323
23657
1871
5451
2146
4204
64418
146691
6674
116984
1635
8726
4613
8577422
1021
38554609
91347535
4602
6427
1019
6657
7465898
4233
79923
166968
2099
6651
23405
84612
23054
377677
6856
9972
51809
4193
26071
3205
3298
3690
5054
860
3589
26273
253461
632
6659
3381
55432
5868
23212
27125
10966
70481490 7430
4089
472
64864
10672
2896225843
10983 51715
2033
138151
hsa-miR-101-3p
hsa-miR-26b-5p
hsa-miR-30c-5p
hsa-miR-26a-5p
hsa-miR-135a-5phsa-miR-30a-3p
hsa-miR-148b-3p
hsa-miR-195-5p
hsa-miR-503-5p
hsa-miR-34c-5phsa-miR-34b-3p
hsa-miR-34b-5p
hsa-miR-18b-5p
hsa-miR-30b-5p
hsa-miR-374a-5p
hsa-miR-211-5p
hsa-miR-374b-5phsa-miR-18a-5p
hsa-miR-135b-5p
hsa-miR-204-5p
21
2. Network Analysis: Cytoscape
colour or filter miRNA-mRNA connections based on type of experimental support e.g. luciferase, CLIP, etc.
55207
6632
8382
11080
1647
233903162
5294
23266
4148
11215
23396
64781
80204
163081
3976
10019
55809
221035
54726
57038
5305
9945
26258
57608
5048
5324
4170
65059
285672
5743
4839
1993
6938
595 517277431
54332
10160
4211
3720
599596
3308
60436
3491
55591
26523
23670
110044306
7832
80223
56144
2355465987
10159
3725
4001
57532
22908
1843
57142
23224
6097
51167
4038
54877
3821
23219
23345
3598
57502
248
5459
3785
323
23657
1871
5451
2146
4204
64418
146691
6674
116984
1635
8726
4613
8577422
1021
38554609
91347535
4602
6427
1019
6657
7465898
4233
79923
166968
2099
6651
23405
84612
23054
377677
6856
9972
51809
4193
26071
3205
3298
3690
5054
860
3589
26273
253461
632
6659
3381
55432
5868
23212
27125
10966
70481490 7430
4089
472
64864
10672
2896225843
10983 51715
2033
138151
hsa-miR-101-3p
hsa-miR-26b-5p
hsa-miR-30c-5p
hsa-miR-26a-5p
hsa-miR-135a-5phsa-miR-30a-3p
hsa-miR-148b-3p
hsa-miR-195-5p
hsa-miR-503-5p
hsa-miR-34c-5phsa-miR-34b-3p
hsa-miR-34b-5p
hsa-miR-18b-5p
hsa-miR-30b-5p
hsa-miR-374a-5p
hsa-miR-211-5p
hsa-miR-374b-5phsa-miR-18a-5p
hsa-miR-135b-5p
hsa-miR-204-5p
22
3. Enrichment Analysis: BiNGO
23
4. Pathway Analysis: WikiPathways
wikipathways.org
55207
6632
8382
11080
1647
233903162
5294
23266
4148
11215
23396
64781
80204
163081
3976
10019
55809
221035
54726
57038
5305
9945
26258
57608
5048
5324
4170
65059
285672
5743
4839
1993
6938
595 517277431
54332
10160
4211
3720
599596
3308
60436
3491
55591
26523
23670
110044306
7832
80223
56144
2355465987
10159
3725
4001
57532
22908
1843
57142
23224
6097
51167
4038
54877
3821
23219
23345
3598
57502
248
5459
3785
323
23657
1871
5451
2146
4204
64418
146691
6674
116984
1635
8726
4613
8577422
1021
38554609
91347535
4602
6427
1019
6657
7465898
4233
79923
166968
2099
6651
23405
84612
23054
377677
6856
9972
51809
4193
26071
3205
3298
3690
5054
860
3589
26273
253461
632
6659
3381
55432
5868
23212
27125
10966
70481490 7430
4089
472
64864
10672
2896225843
10983 51715
2033
138151
hsa-miR-101-3p
hsa-miR-26b-5p
hsa-miR-30c-5p
hsa-miR-26a-5p
hsa-miR-135a-5phsa-miR-30a-3p
hsa-miR-148b-3p
hsa-miR-195-5p
hsa-miR-503-5p
hsa-miR-34c-5phsa-miR-34b-3p
hsa-miR-34b-5p
hsa-miR-18b-5p
hsa-miR-30b-5p
hsa-miR-374a-5p
hsa-miR-211-5p
hsa-miR-374b-5phsa-miR-18a-5p
hsa-miR-135b-5p
hsa-miR-204-5p
24
Downstream Analyses: SummaryPathways
Genb
oree
Focused set of
interactions
All known interactions
PD vs PDD diff exp Burgos K., et al. (2014) PLoS ONE
summary• trivial to use exceRpt thanks to:
- automated, linear workflow - GUI, processing, & data/result storage on Genboree
• average runtime for high quality RNA-seq sample:- 1hr for endogenous-only analysis- 2hr 30mins for endogenous+exogenous alignments
• downstream network analysis tools directly integrated in genboree and automatically accept exceRpt results
25
exRNA.orggenboree.org
Acknowledgements
Data Integration and Analysis Component (DIAC) members of the Data Management Resource and Repository (DMRR)
Mark Gerstein Aleks Milosavljevic Joel Rozowsky
Matt Roth Sai LakshmiSubramanian
WilliamThistlethwaite
Alex PicoFabioNavarro
