MPSS: Process Overview

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MPSS Process Overview
Library to library
Run to run
Bead load to bead load
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MPSS Data Structure
Replicates
Row Means
Row Variance
Merged Signature Counts
Signatures
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Digital Signature to Expression Level
SIGNATURE GATCTGACGTTTTCTAC GATCACAACAGTACCAT GATC
AGGACACGTATCT GATCCGTATGAATCTGG GATCTGACGTTTTCTAC
GATCGCTTTATGTTTTT GATCAGGACACGTATCT GATCCTTTGGAATC
TTG GATCCGTATGTGGTTAA GATCCTGTCTCAACAAC GATCTGACGT
TTTCTAC GATCACAACAGTACCAT GATCCGTATGTGgTTAA GATCAC
AACAGTACCAT GATCCGTATGTGGTTAA GATCTGACGTTTTCTAC ..
.
SIGNATURE OB_COUNT GATCTGACGTTTTCTAC 56 GATCAC
AACAGTACCAT 74 GATCAGGACACGTATCT 11 GATCCGTATGAATC
TGG 1500 GATCGCTTTATGTTTTT 20 GATCCTTTGGAATCTTG 2
GATCCTGTCTCAACAAC 13 GATCAGCTTGGACAATG 24 GATCTTT
GCTGGCAAGC 5 GATCCCCACCCTCCCGC 1 GATCTACCTATACCCAG
67 GATCCGTATGTGgTTAA 1 GATCAGCCCATTTCTGG 4 GATCC
GTaTGTGgTTAA 1 GATCATAACAAGAATGA 31 GATCCCGGTGTGA
GGTA 1 ...
SIGNATURE OB_COUNT GATCTGACGTTTTCTAC 56 GATCAC
AACAGTACCAT 74 GATCAGGACACGTATCT 11 GATCCGTATGAATC
TGG 1500 GATCGCTTTATGTTTTT 20 GATCCTTTGGAATCTTG 2
GATCCTGTCTCAACAAC 13 GATCAGCTTGGACAATG 24 GATCTTT
GCTGGCAAGC 5 GATCCCCACCCTCCCGC 1 GATCTACCTATACCCAG
67 GATCCGTATGTGgTTAA 1 GATCAGCCCATTTCTGG 4 GATCG
CACGTTGTACTT 5 GATCATAACAAGAATGA 31 GATCCCGGTGTGAG
GTA 1 ...
SIGNATURE OB_COUNT GATCTGACGTTTTCTAC 56 GATCAC
AACAGTACCAT 74 GATCAGGACACGTATCT 11 GATCCGTATGAATC
TGG 1500 GATCGCTTTATGTTTTT 20 GATCCTTTGGAATCTTG 2
GATCCTGTCTCAACAAC 13 GATCAGCTTGGACAATG 24 GATCTTTG
CTGGCAAGC 5 GATCCCCACCCTCCCGC 1 GATCTACCTATACCCAG
67 GATCCGTgTGTGTTTAA 1 GATCAGCCCATTTCTGG 4 GATCTG
AATTGGCTGcA 1 GATCATAACAAGAATGA 31 GATCCCGGTGTGAG
GTA 1 ...
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Sample 1 Sample2 SIGNATURE T_Ave T_Stdev
F_Ave F_Stdev T_Ave T_Stdev F_Ave F_Stdev GATCTGAC
GTTTTCTAC 92 1.2 92 4.7 93 2 92 5 GATCACAACAGTACCA
T 122 1.2 123 1.2 121 0 123 2.5 GATCAGGACACGTATCT
19 1.2 17 1.2 16 2.5 18 3 GATCCGTATGTGGTTAA 2489 1
.2 2474 3.5 2600 50 2555 3.6 GATCGCTTTATGTTTTT 17
23.5 0 0 0 0 0 0 GATCCTTTGGAATCTTG 2 0.7 3 2.1 1 1
.2 2 0 GATCCTGTCTCAACAAC 21 1.2 21 2.3 100 10 105
10 GATCAGCTTGGACAATG 40 0 40 1.2 41 0 44 1 GATCTTT
GCTGGCAAGC 10 2.3 14 1.2 12 2.5 15 1.2 GATCTACCTAT
GCCCAG 111 0 109 0 121 0 110 0 GATCAGCCCATTTCTGG 7
1.2 8 4.7 7 1.2 8 4.7 GATCATAACAAGAATGA 51 1.2 50
2.3 60 3.2 51 2.3 GATCCCGGTGTGAGGTA 124 1.2 0 0 1
25 1.2 0 0 GATCTGCCGGTGAGGTA 0 0 163 0 0 0 165 0
...
Sample 1 Sample2 SIGNATURE T_Ave T_Stdev
F_Ave F_Stdev T_Ave T_Stdev F_Ave F_Stdev GATCTGAC
GTTTTCTAC 92 1.2 92 4.7 93 2 92 5 GATCACAACAGTACCA
T 122 1.2 123 1.2 121 0 123 2.5 GATCAGGACACGTATCT
19 1.2 17 1.2 16 2.5 18 3 GATCCGTATGTGGTTAA 2489 1
.2 2474 3.5 2600 50 2555 3.6 GATCGCTTTATGTTTTT 17
23.5 0 0 0 0 0 0 GATCCTTTGGAATCTTG 2 0.7 3 2.1 1 1
.2 2 0 GATCCTGTCTCAACAAC 21 1.2 21 2.3 100 10 105
10 GATCAGCTTGGACAATG 40 0 40 1.2 41 0 44 1 GATCTTT
GCTGGCAAGC 10 2.3 14 1.2 12 2.5 15 1.2 GATCTACCTAT
GCCCAG 111 0 109 0 121 0 110 0 GATCAGCCCATTTCTGG 7
1.2 8 4.7 7 1.2 8 4.7 GATCATAACAAGAATGA 51 1.2 50
2.3 60 3.2 51 2.3 GATCCCGGTGTGAGGTA 124 1.2 0 0 1
25 1.2 0 0 GATCTGCCGGTGAGGTA 0 0 163 0 0 0 165 0
...
Sample 1 Sample2 SIGNATURE Stepper TPM Std
ev TPM Stdev GATCTGACGTTTTCTAC T 92 1.2 93 2 GATCA
CAACAGTACCAT F 123 1.2 123 2.5 GATCAGGACACGTATCT F
19 1.2 18 3 GATCCGTATGTGGTTAA T 2489 1.2 2600 50
GATCGCTTTATGTTTTT 0 0 0 0 GATCCTTTGGAATCTTG 1 1.
2 2 0 GATCCTGTCTCAACAAC F 21 1.2 105 10 GATCAGCTTG
GACAATG F 40 0 44 1 GATCTTTGCTGGCAAGC F 14 1.2 15
1.2 GATCTACCTATGCCCAG T 111 0 121 0 GATCAGCCCATTTC
TGG F 8 4.7 8 4.7 GATCATAACAAGAATGA T 51 1.2 60 3.
2 GATCCCGGTGTGAGGTA T 124 1.2 125 1.2 GATCTGCCGGTG
AGGTA F 163 0 165 0 ...
Sample 1 Sample2 p_value SIGNATURE TPM Std
ev TPM Stdev GATCAAATTCATCTCTA 0 0 15 2 0.0101403
6 GATCAAATTGACCGCTT 8 6 23 9 0.07050718 GATCAAATTG
GTGGGGG 11 18 2 2 0.08729055 GATCAAATTGTACTAGT 2 3
10 7 0.09091700 GATCAAATTGTGCAGTA 15 11 35 4 0.05
020690 GATCCCGGTGTGAGGTA 124 1.2 125 1.2 0.5821848
5 GATCTGCCGGTGAGGTA 163 0 165 0 0.62550128 ...
SIGNATURE Two Two Four Four
GATCTGACGTTTTCTAC 56 55 58 54 GATCACAACAGTACCAT 7
4 73 74 75 GATCAGGACACGTATCT 11 12 11 10 GATCCGTAT
GTGGTTAA 1500 1499 1501 1498 GATCGCTTTATGTTTTT 55
0 0 0 GATCCTTTGGAATCTTG 1 2 4 1 GATCCTGTCTCAACAAC
13 12 12 14 GATCAGCTTGGACAATG 24 24 25 24 GATCTTTG
CTGGCAAGC 5 7 8 9 GATCTACCTATGCCCAG 67 67 66 66 GA
TCAGCCCATTTCTGG 4 5 7 3 GATCATAACAAGAATGA 31 30 31
29 GATCCCGGTGTGAGGTA 75 74 0 0 GATCTGCCGGTGAGGTA
0 0 99 99 ...
Run Group Report
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Calculate Mean, Tpm, and Standard Deviation
Calculate mean and tpm of 2-stepper runs for
signature 1
Weighted Average (20 0 17) / (671873
704108 727162) 1.75927e-5 Average Clone
Counts Normalize Factor (671873 704108
727162) / 3 701047.6 Tpm Normalize Factor 1e6
Mean Weighted Average Ave. Clone Counts
Normalize Factor (1.75927e-5) (701047.6)
12.333 12
Tpm Weighted Average tpm Normalize Factor
(1.75927e-5) (1e6) 17.592 18

• Repeat to get mean and tpm of 4-stepper runs for
  signature 1
• Repeat for all signatures in RunGroup
• Calculate standard deviation as well, normalized
  to 1 million

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Lynx MPSS Statistic Model
The data produced with MPSS are of the
categorical" type from a statistical point of
view. Therefore, a test of significance for
differential expression between samples can be
carried out using a normal approximation test
(also referred to as Z-test). If x1 and x2
represent the abundance of a specific signature
in samples 1 and 2, the proportions
thus follow a binomial distribution. Because n1
and n2 are large in MPSS (typically in the order
defined by equation (1) where the unknown
parameters p and q can be estimated as

and
,respectively.
and
(1)
Thus, the test statistics defined by equation (2)
below follow a standard normal distribution.
Equation (2) is a two-tailed, normal
approximation test for binomial
proportions.   The digital nature of MPSS
allows one to use equation (2) to calculate the
percentage difference in expression that is
statistically significant between multiple
samples. These characteristics are in contrast to
the analyses for gene expression data generated
by hybridization based methods, such as
microarrays, where a significance test is
possible only if the experiment is replicated
many times, and where differential expression can
usually be detected only for genes with
relatively high levels of expression and with a
large difference between samples.
(2)

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Calculate P-values
(where x is observed count, and c is clone count)
p 0.2316419 b1 0.319381530 b2 -
0.356563782 b3 1.781477937 b4 -
1.821255978 b5 1.330274429