Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Speaker Deck
PRO
Sign in
Sign up for free
mapping2015
Leonardo Collado-Torres
February 23, 2015
Science
1
83
mapping2015
Leonardo Collado-Torres
February 23, 2015
Tweet
Share
More Decks by Leonardo Collado-Torres
See All by Leonardo Collado-Torres
LIBD_DS_TLDR
lcolladotor
0
550
psychgenomics-2022
lcolladotor
0
33
Spatial Biology US 2021
lcolladotor
0
150
CDSB2021
lcolladotor
0
210
nih finding data
lcolladotor
0
54
HBHL keynote
lcolladotor
0
110
BioTuring_spatialLIBD
lcolladotor
0
2.6k
CDC/ATSDR R User Group 2021
lcolladotor
0
870
biocthis_ConectaR2021
lcolladotor
0
240
Other Decks in Science
See All in Science
B.LEAGUE におけるバスケットボールのリアルタイム勝利確率モデルの構築 / Realtime win probability model for B.LEAGUE
konakalab
0
150
Obesity And Cancer: The Reality Behind Cancer And Weight
kentclark
0
110
離散微分形式による大規模流体音響解析
deepflow
0
190
Deconvolving Cell Type Proportions in Human Postmortem Brain Tissue from Bulk RNA-seq Data
lahuuki
0
100
Quaternion Rotation
usamik26
0
390
FreeCADで簡易版バスケットボールのモデル
kamakiri1225
0
320
実験ノートをどう取るべきか
rinabouk
PRO
1
1.8k
Tokyo.R コレスポンデンス分析の正しい使い方
bob3bob3
1
1.2k
深層学習による自然言語処理 輪読会#4 資料
tok41
0
470
統計学実践ワークブック 第16章 重回帰分析 pp.125-127
axjack
0
200
ROS再入門 -Lidarセンサーを触ってみた-
miura55
0
280
深層学習による自然言語処理 輪読会#2 資料
tok41
0
510
Featured
See All Featured
Three Pipe Problems
jasonvnalue
89
8.7k
10 Git Anti Patterns You Should be Aware of
lemiorhan
638
53k
Faster Mobile Websites
deanohume
294
29k
Creatively Recalculating Your Daily Design Routine
revolveconf
207
10k
Design by the Numbers
sachag
271
17k
CSS Pre-Processors: Stylus, Less & Sass
bermonpainter
349
27k
"I'm Feeling Lucky" - Building Great Search Experiences for Today's Users (#IAC19)
danielanewman
212
20k
Building Better People: How to give real-time feedback that sticks.
wjessup
344
17k
Stop Working from a Prison Cell
hatefulcrawdad
262
17k
The Brand Is Dead. Long Live the Brand.
mthomps
46
2.7k
A Modern Web Designer's Workflow
chriscoyier
689
180k
Building Adaptive Systems
keathley
25
1.2k
Transcript
Does mapping simulated RNA-seq reads provide information? Leonardo Collado-Torres tweet:
@fellgernon blog: tinyurl.com/FellBit
Previously • Choose 10 genes with FPKM > 20 •
cufflinks: estimate isoform FPKM from 7 Geuvadis samples • polyester: simulate with uniform & rnaf models • Map with TopHat • View coverage https://github.com/alyssafrazee/polyester_code/blob/master/polyester_manuscript.Rmd
https://github.com/alyssafrazee/polyester_code/blob/master/polyester_manuscript.Rmd
Goals • Reproduce • Similar behavior in other genes/samples? •
Do simulated reads predict observed data? Get a measure by gene • Even more than by chance?
None
Original
Reproduced
None
None
None
None
Measures by gene: using single bp exon • Correlation (R^2)
• RMSD: scaling by max first • ARIMA: forecast models – Auto ARIMA on obs – Fit again using simulated data as predictor – P-value for predictor and estimated coef • Chance: – Neg. binomial size 1 and 6 – Compare replicates of simulated data
• d: default params, 2 reps (2x) • r: using
rnaf bias, 2x • b1: neg. binomial with size = 1, 2x • b6: neg. binom. size = 6, 2x • d1-d2: using d1 as “obs” – Same for r1-r2, b1a-b1b, b6a-b6b
Correlation
Correlation: summarize by sample
Correlation: summarize by gene
R^2
Scaling by max then RMSD
Scaling by max then RMSD
None
None
ARIMA: predictor p-value
ARIMA: predictor p-value
ARIMA: predictor coefficient
None
None
Code • https://github.com/alyssafrazee/polyest er_code/blob/master/polyester_manuscri pt.Rmd • https://github.com/lcolladotor/mapBias (private for now)
None
None