Parameter Value
hashtag #ABACBS2018
start_day 2018-11-26
end_day 2018-11-28
timezone Australia/Sydney
theme theme_light
accent #dd0c15
accent2 #EE858A
kcore 2
topics_k 6
bigram_filter 3
fixed TRUE
seed 1

Introduction

An analysis of tweets from the #ABACBS2018 hashtag for the Australian Bioinformatics and Computational Biology Society conference, 26-28 November 2018 at The University of Melbourne, Melbourne Australia

A total of 1596 tweets from 248 users were collected using the rtweet R package.

1 Timeline

1.1 Tweets by day

1.2 Tweets by day and time

Filtered for dates 2018-11-26 - 2018-11-28 in the Australia/Sydney timezone.

2 Users

2.1 Top tweeters

Overall

Original

Retweets

2.2 Retweet proportion

2.3 Top tweeters timeline

2.4 Top tweeters by day

Overall

Day 1

Day 2

Day 3

Original

Day 1

Day 2

Day 3

Retweets

Day 1

Day 2

Day 3

3 Sources

Users

Tweets

4 Networks

4.1 Replies

The “replies network”, composed from users who reply directly to one another, coloured by PageRank.

4.2 Mentions

The “mentions network”, where users mention other users in their tweets. Filtered for a k-core of 2. Node colour and size adjusted according to PageRank score.

5 Tweet types

5.1 Retweets

Proportion

Count

Top 10

screen_name text retweet_count
AliciaOshlack

If you are interested in joining my lab for a post-doc in research bioinformatics have a chat to me or message me at #abacbs2018 #COMBINE18

https://t.co/404MibRFnZ 		41
davisjmcc We’ll soon be advertising three new roles, so if you’re a postdoc with a computational PhD (or will be soon), or a bioinformatics or statistics Honours graduate, please get in touch! Tell your postdocs, students, friends! More info: https://t.co/sRoEMCI5Lv #ABACBS2018/#ABACBS18 20
davisjmcc Nancy Zhang has given by far the most persuasive argument for an expression recovery (“imputation”) tool for scRNA-seq data I’ve seen. SAVER superiority confirmed by indep’t analysis from @talandrews and @m_hemberg in recent F1000 paper #abacbs2018 17
davisjmcc

#ABACBS2018/#ABACBS18 has been a delightful re-entry for me into the Aus bioinf/comp bio community after 7 years in UK.

I’m back to lead a new research group at @SVIResearch and @unimelb, working on all things #singlecell, with a big interest in genetics and methods development. 		16
mritchieau Charity Law is unwell, so won’t be presenting at #abacbs2018, but you can read about her work on exploring intron signal at https://t.co/ip7TMoN34f. On the upside, the morning session is now back on time :) Get well soon Charity! https://t.co/lBrXREjZ4e 15
lazappi #ABACBS2018 Award Winners - Early-career researcher @BelindaPhipson - Open science @torstenseemann - Professional bioinformatics Alex Garnham - Mid-career researcher David Lynn - Senior research fellow Mark Ragan 14
JovMaksimovic Great to see the Illumina developing open source software #ABACBS2018 #byebyeblackbox https://t.co/GuD4iLys9i 13
PeteHaitch Yingxin Lin showing, yet again, that students give amongst the best talks. Here, presenting scMerge for integrating scRNA-seq datasets #abacbs2018 📝: https://t.co/7Y8fQGqL0T 💻: https://t.co/6lStKA8RWq 13
lazappi Thanks @BelindaPhipson for mentioning @scRNAtools. Check it out here if you are interested https://t.co/EClP64fOU7. Submissions and updates welcome! #abacbs2018 12
AliciaOshlack Congratulations @torstenseemann for your open science award at #abacbs2018. Well deserved! 11

Most retweeted

5.2 Likes

Proportion

Count

Top 10

screen_name text favorite_count
davisjmcc

#ABACBS2018/#ABACBS18 has been a delightful re-entry for me into the Aus bioinf/comp bio community after 7 years in UK.

I’m back to lead a new research group at @SVIResearch and @unimelb, working on all things #singlecell, with a big interest in genetics and methods development. 		62
AliciaOshlack Managed to get an Oshlack lab photo of the whole group at #abacbs2018 #loveit https://t.co/dmun9v1Ha7 58
BelindaPhipson Just wanted to thank @WEHI_research and @unimelb for subsidising childcare at #abacbs2018. Fantastic to have this support at conferences. 57
AliciaOshlack Congratulations to @BelindaPhipson for winning the #abacbs2018 early career researcher award. There couldn’t be a more deserving winner #soproud 55
BelindaPhipson Feel honoured to receive the ECR award at #abacbs2018. Thank you to my amazing mentors @AliciaOshlack and Gordon Smyth for nominating me. 54
davisjmcc Nancy Zhang has given by far the most persuasive argument for an expression recovery (“imputation”) tool for scRNA-seq data I’ve seen. SAVER superiority confirmed by indep’t analysis from @talandrews and @m_hemberg in recent F1000 paper #abacbs2018 48
hdashnow

@theosysbio: “Data resuscitation”

That’s an apt description of what Bioinformaticians do when they they are not engaged in the experimental design, but rather are asked to save the experiment. #abacbs2018 		39
cabbagesofdoom Much deserved #abacbs2018 open source award to @torstenseemann - I’ve annotated multiple organisms with Prokka, and I’m a fan! 39
AliciaOshlack

If you are interested in joining my lab for a post-doc in research bioinformatics have a chat to me or message me at #abacbs2018 #COMBINE18

https://t.co/404MibRFnZ 		34
JovMaksimovic Great to see the Illumina developing open source software #ABACBS2018 #byebyeblackbox https://t.co/GuD4iLys9i 33

Most likes

5.3 Quotes

Proportion

Count

Top 10

screen_name text quote_count
shazanfar

my current TweetDeck tab is “#combine18 OR #combine2018 OR #abacbs18 OR #abacbs2018”

maybe I should include the SNPs associated too 😂🤦‍♀️ https://t.co/iBtt6sLApf 		2
AliciaOshlack Apparently the conference program has the hashtag at #abacbs2018 … Best to go with that and not #ABACBS18 I think https://t.co/Wq3VdV2jSn 2
AliciaOshlack You can vote for @JovMaksimovic for post-doc rep at the #ABACBS2018 AGM soon https://t.co/6pEzWwJP3k 2
hdashnow I’ve been burned by the short-deadline/part-time issue myself. Something we should all be aware of when promoting #WomenInScience #ABACBS18 #abacbs2018 #COMBINE18 https://t.co/Xt82J3Jp9X 2
mritchieau singscore #bioconductor software available from https://t.co/vK9vsLOAnH #abacbs2018 https://t.co/W2KJePOvrv 2
Alimahmoudi29 #abacbs2018 @S_Foroutan Singscore https://t.co/wx6GMYKt3r 2
shazanfar Those at #abacbs2018 take note :D https://t.co/fGFHMlZQ57 2
mritchieau Want more #singlecells in Melbourne next July? #abacbs2018 https://t.co/fMo1nJ5DvL 2
_StuartLee

For those that can’t make it to the workshop at #BiocAsia - you can still play along at home and learn about Granges. I’ve just posted solutions to the exercises. #abacbs2018

https://t.co/goTgwtl0n8 https://t.co/W7eMSFamZ4 		1
AliciaOshlack

Maybe @abacbs can make a final call on this

…remembering last year was #abacbs17 and this year we have #COMBINE18

#ABACBS18 vs #abacbs2018 https://t.co/qYHTa8edUf 		1

Most quoted

6 Media

Proportion

Top 10

screen_name text favorite_count
AliciaOshlack Managed to get an Oshlack lab photo of the whole group at #abacbs2018 #loveit https://t.co/dmun9v1Ha7 58
JovMaksimovic Great to see the Illumina developing open source software #ABACBS2018 #byebyeblackbox https://t.co/GuD4iLys9i 33
lazappi #abacbs2018 international keynote @DunhamLab “Drivers of aneuploidy and adaptation in yeast” https://t.co/46wfHZhqMC 30
mritchieau Charity Law is unwell, so won’t be presenting at #abacbs2018, but you can read about her work on exploring intron signal at https://t.co/ip7TMoN34f. On the upside, the morning session is now back on time :) Get well soon Charity! https://t.co/lBrXREjZ4e 29
RoxaneLegaie As the Professional Bioinformaticians Representative at @abacbs and a co-organiser of the @RLadiesMelb, I couldn’t be any prouder of our Prof Bioinfo Award winner 2018… Alex Garnham !! 🤗🎉💃🏼💪👏 Congrats lady! 😎👌 #abacbs2018 https://t.co/ABt02OY59r 27
AliciaOshlack missMethyl #woohoo #abacbs2018 @JovMaksimovic @BelindaPhipson https://t.co/I9g1pV6Gjg 26
RoxaneLegaie Congratulations @_hollywhitfield for winning the @combine_au Best Talk prize and for sharing it with us at #abacbs2018. A great talk indeed! 👌 And good luck with the upcoming PhD! @WEHI_research https://t.co/KeIkV4JTi4 26
lazappi #abacbs2018 Day 2 international keynote from @ctsa11 https://t.co/NGe43lPpKQ 24
kizza_a this is me. come and say hi. or just read it here https://t.co/IaZLC18VDk about my nee iffyRna tool #abacbs2018 thanks https://t.co/Ky7SvPV2yJ 18
mritchieau ⁦@DoktrNick⁩ shows us a beautiful visualisation of kidney development as a tree, reconstructed from imaging data. Informed development of a generative growth model for this process #abacbs2018 https://t.co/ZjKFVPAziw 18

6.1 Most liked image

7 Tweet text

7.1 Word cloud

The top 100 words used 3 or more times.

7.2 Hashtags

Other hashtags used 5 or more times.

7.3 Emojis

7.4 Bigram graph

Words that were tweeted next to each other at least 3 times.

7.5 Topic modelling

Top 10 words associated with 6 topics identified by LDA.

7.5.1 Representative tweets

Most representative tweets for each topic

Topic 1

screen_name text gamma
carsweshau Maitreya Dunham on rich genomic datasets and thinking about CNV (causative? drivers?) in human disease (aneuploidy, cancer, complex disease). Yeast as a relevant system owing to CNVs affecting many traits in yeast, can perform experimental evolution in a chemostat #abacbs2018 0.9920590
mritchieau Leming Shi tells us about MAQC/SEQC projects: huge collaboration that used RNA mixtures to compare gene expression technologies and analysis methods. A valuable resource for the research community. Extending to biomarker analysis at present - hoping to publish soon #abacbs2018 https://t.co/BN8LAV8I0C 0.9917566
CFlensburg

#abacbs18 (aka #abacbs2018) going down this week, conference starting tomorrow, and I’ll try to live report a bit. Program here: https://t.co/CmbEoA7kJX

Feel free to follow/filter/unfollow/mute/block/report as you feel appropriate.

For other live tweeps: @TweetDeck is awesome. 		0.9910770
mritchieau ⁦@DunhamLab⁩ improved upon results from DNAcopy to segment data along the genome in collaboration with statisticians ⁦@daniela_witten⁩ and Lucy Gao. Applied 1D Fused Lasso to help distinguish between ‘steppy’ or linear models and map driver genes #abacbs2018 https://t.co/UdxjsF4j23 0.9910770
shazanfar

#abacbs2018 For those wanting a head-start (or attending other sessions), all BioC Asia ClassifyR workshop material is on the Github:

Used tomorrow (90mins): https://t.co/P83l9Q8AeB

Prior workshop with more background on classification methods (3hr): https://t.co/EUs9HoOT19 		0.9893152
methylnick Twas a brilliant talk and controls are fundamental to any interpretation of genomic data. It’s a slow adoption but my colleagues are starting to listen. #abacbs2018 #reproducibility #controls #referenceMaterial https://t.co/49SqJRvO0v 0.9874581
ramialison_lab @BelindaPhipson @WEHI_research @unimelb Childcare onsite is the best at a conference… mum and dad could enjoy all sessions… bub even wanted his own #abacbs2018 badge ;) Thanks a million @abacbs @WEHI_research @unimelb and @claresloggett https://t.co/021or95w3K 0.9866867
mritchieau Charity Law is unwell, so won’t be presenting at #abacbs2018, but you can read about her work on exploring intron signal at https://t.co/ip7TMoN34f. On the upside, the morning session is now back on time :) Get well soon Charity! https://t.co/lBrXREjZ4e 0.9848195
aljabadi Nancy Zhang explains how predictable genes can be trusted in their approach to sc gene expression recovery, aka imputation. #SAVER #abacbs2018 0.9848195
lazappi Ann-Marie plots walking us through the challenges of cancer genomics, different types of variants, tumour heterogeneity, challenges related to therapy. #abacbs2018 0.9848195

Topic 2

screen_name text gamma
sydneybioinfo Hearing from fantastic @sydneybioinfo (1st yr PhD student) @LinYingxin scMerge: Integration of multiple single-cell transcriptomics datasets leveraging stable expression and pseudo-replication. Motivated by real issues with integrating developmental liver scRNA-Seq #abacbs2018 0.9917566
cabbagesofdoom @koadman wrt your repeat % Q: v. low gaps levels but also smaller assemblies for the other snake genomes analysed. Will need to dig deeper to tell missing data from possible 10x repeat over-assembly artefact. Are we repeating repeats? #ABACBS2018 #QandA 0.9898178
marialenagr Learning about the evolution of single cell RNA-seq in a presentation delivered by international keynote speaker Dr Nancy Zhang. Single cell is currently a hot hot hot topic. #ABACBS2018 @abacbs https://t.co/NeKLs4iNVd 0.9898178
mritchieau ⁦@theosysbio:⁩ mutual information, in particular partial information decomposition works better for network reconstruction. Nice results on neuronal differentiation published in Stumpf PS et al. (2017) https://t.co/0WxhlEoTsP - first author is a long lost cousin :) #abacbs2018 https://t.co/M0qYvOvTr4 0.9893152
hdashnow Yingxin Lin: Unlike bulk RNA-seq, by definition in single cell RNA-seq the cells do not have replications. So we need pseudo-replicates - use cells of the same cell type from different batches #ABACBS2018 0.9887605
minouye271

If anyone at #abacbs2018 is looking for a postdoc in multiomics or polygenic risk scores in Aus or UK, feel free to DM/email me.

The @CamBakerSGI is recruiting at both its @BakerResearchAu & @Cambridge_Uni nodes. Eg https://t.co/oJ3a6ytDBK

More info at https://t.co/R5AQWPf89N 		0.9887605
shazanfar #abacbs2018 hearing from @S_Foroutan on singscore, method to estimate truly single sample gene set/pathway scores. These are useful for building interpretable and stable features for cohort-independent and prospective learning. 0.9881449
aljabadi

Leming Shi explains how lucky we are working in life sciences with a lot of things to discover compared to drug developers who have a rough path ahead until it a real difference is made. #PrecisionMedicine

#abacbs2018 https://t.co/9JAH8eFHXE 		0.9881449
sydneybioinfo Taiyun Kim, PhD student working with @PengyiYang82 and @jeanyang21 at @sydneybioinfo is presenting his work on the impact of similarity metrics on clustering single cell transcriptional data. Paper: https://t.co/WGWXPgZR6p #abacbs2018 0.9866867
sydneybioinfo Continuing with the strong @sydneybioinfo student presentations we have @KevinWang009 presenting work on RUV-Pro: Removing unwanted variation in prospective experiments to enable stable risk prediction #abacbs2018 0.9858143

Topic 3

screen_name text gamma
carsweshau Yi Jin Liew with epigenetic adaptation of corals to ocean acidification. Corals are very important to oceanic ecosystems, so relevant to know effects of rising temperatures etc. on coral. Chances are in humans, a random CpG site will be methylated. Coral, not so! #abacbs2018 0.9906933
paulfharrison

.@dunhamlab looking at driver genes vs larger regions of fitness of genes with 1D fused LASSO at #abacbs2018 (if I’m understanding correctly).

Hearing LASSO these days I wonder if Elastic-Net can be used, here would give intermediates between stepwise and smooth curve fit. 		0.9898178
DunhamLab I’m up first this morning at #abacbs2018! I’ll talk about “Drivers of aneuploidy and adaptation in yeast” focusing on a few datasets we’ve generated that I’d love to set this crowd loose on for more analysis. 0.9881449
mritchieau Yi Jin Liew: coral CpG methylation is very different to patterns seen in mammals. Mostly occurs in gene bodies and much rarer (~ 7%) at CpG islands compared to humans (~ 60-80%) #abacbs2018 https://t.co/PjWS0noQZa 0.9874581
mritchieau ⁦@DunhamLab⁩ uses a pooled approach to gather fitness measures in yeast and associate with changes in copy number using regression. Fun fact: barcoding pioneered by yeast geneticists in the ‘90s - now used by everyone #abacbs2018 https://t.co/idw6ib6mqc 0.9874581
shazanfar #abacbs2018 @steman_research presenting work on ARMET (algorithm for resolving microenvironment transcriptomes). Passes on hierarchical structure of cell types rather than treating independently to deconvolute bulk transcriptomes 0.9866867
shazanfar @davisjmcc @AliciaOshlack @talandrews @m_hemberg I’m intrigued by the correction applied for estimating the gene-gene correlation, am I right to assume it’s not just simply taking Pearson over the ‘recovered’ matrix? #ABACBS2018 0.9858143
shazanfar #abacbs2018 @DunhamLab describes using DNAcopy to sensitively identify ‘fitness breakpoints’ in ingeniously induced tiled aneuploidy in yeast. Learning so much yeast genetics/genomics right now! 0.9858143
paulfharrison .@CFlensburg describing SuperFreq. Parallel plots of copy number and variant allele frequency. Both can be segmented, but it works better to do both simultaneously. A nice simple example of multi-task learning, maybe. #abacbs2018 0.9858143
shazanfar #abacbs2018 Li Jin Liew throws back to yesterday’s #COMBINE18 panel with sharing of workflows with DNA methylation analysis https://t.co/Fl1v7wDnNA 0.9836746

Topic 4

screen_name text gamma
lazappi #ABACBS2018 Award Winners - Early-career researcher @BelindaPhipson - Open science @torstenseemann - Professional bioinformatics Alex Garnham - Mid-career researcher David Lynn - Senior research fellow Mark Ragan 0.9887605
frostickle

Bioinformatics career panel time at #COMBINE18 with: @IBMResearch @bwgoudey @PeterMacCC @RoxaneLegaie @illumina @ctsa11 @QIMRBerghofer @IamAMP

Good to see a balance in industry vs public hospital vs academic & also gender!

#ABACBS2018 https://t.co/pzB2UfR6zw 		0.9881449
sydneybioinfo Several @sydneybioinfo members are in attendance at #abacbs2018 with talks + posters. Give these people a follow & come say Hi! @KevinWang009 Taiyun Kim (talk today), Hani Kim, @LinYingxin @rylmb1 @shazanfar @TheEllisPatrick Nick Canete, Heeva Baharlou, Kitty Lo, Dario Strbenac 0.9881449
aljabadi An end-of-the-day shout out to Dr Leming Shi for - IMO - one if the most passionate talks which still gets me thinking about how imperative it is to be focussed on standardisation of the methods we use in order to facilitate their applications. #abacbs2018 https://t.co/RYXTwNJlqQ 0.9866867
RoxaneLegaie ** Shaming Tweet Warning ** With over 50 people identifying as Professional Bioinformaticians in Australia, and most of them being from Melbourne… How come it was only 5 of us at the Prof Bioinfo get together tonight?? 🤔 Never mind, more food & drinks for us! 😜 #abacbs2018 https://t.co/2W6euJ4JNz 0.9866867
LonsBio Woah! DeepVariant turns variant calling into an image deep learning problem! Mind blown! Wonder what other kinds of bioinformatics problems could use visualisation images as input? #abacbs2018 https://t.co/HoTm8aHcB4 https://t.co/E4ivuw8RLa 0.9866867
lazappi Bit late but analysis of Twitter activity from #abacbs2018 Day 1 (and a bit) https://t.co/W4dPBrQ4Tb. Keep tweeting links to add software to the list (not sure I can get to all the posters today) 0.9848195
JoeCursons The #ABACBS2018 professional bioinformatics award given to Alex Garnham - well deserved as the powerhouse of the @WEHI_research bioinformatics service unit and the saviour of many @WEHI_Postdocs with data to analyse! 0.9848195
lnly0311 Chris Saunders giving a talk about Improving sequence analysis to increase the clinical value of whole genome sequencing. #abacbs2018 - “Not using JAVA” - people clapping 0.9848195
methylnick Another take on the Moore’s Law plot. Chris Saunders from @illumina #abacbs2018 Compute and runtime important considerations for tools to get to result. https://t.co/HwWo0Bzkux 0.9823430

Topic 5

screen_name text gamma
carsweshau Stephen J. Bent has a story of four moths and working on ancient DNA samples (characteristic damage would be lots of cytosine deamination, base oxidation of purines, shorter fragments). One of these moth samples is almost 100 years old! C>T & G>A at ends is the hint! #abacbs2018 0.9902752
shazanfar #abacbs2018 Kim-Anh Do now speaking about PRECISE, Personalised cancer-specific integrated estimation. Two main aims in personalised medicine: build more accurate understanding of individual patients, and introduce adaptive treatments to individuals 0.9902752
_hollywhitfield

To account for individual variability, and administer the correct interventions Kim-An Do is producing integrated networks:

Interaction databases + data -> patient-specific networks

#abacbs2018 #ABACBS18 		0.9881449
_VickiJackson #abacbs2018 finished for another year. Great speaking to @egiannoulatou lab members about challenges in sequencing studies. Unrelated to current work, but also enjoyed talk by @DoktrNick on imaging of developing kidney (reminded me of my previous work in the world of lungs!) 0.9881449
annaquagli Clare Sloggert presenting Reduce to visualise high dimensional data interactively! Written with Plotly Dash: code in #python 🐍and create great web-apps based on #JavaScript #abacbs2018 0.9874581
aljabadi

Richard Edwards on promise of 10x Chromium’s Diploid Phasing to perform comparable to long-read technologies at the cost of short read ones by #demultiplexing using #SNPs.

#abacbs2018 https://t.co/ZPinB1tqFB 		0.9874581
mritchieau ⁦@DoktrNick⁩ shows us a beautiful visualisation of kidney development as a tree, reconstructed from imaging data. Informed development of a generative growth model for this process #abacbs2018 https://t.co/ZjKFVPAziw 0.9866867
lazappi BP: Batch to batch variability can be explained by relative maturity of organoids. This can be applied to a disease modelling experiment using a patient mutation and corrected line. #abacbs2018 0.9866867
LonsBio Application of @bphipson variability results in patient corrected iPSC cells work from @kidney_tom et al, filtering out highly variable genes for DE analysis https://t.co/DjoBK5l47n #ABACBS2018 0.9866867
kizza_a hey @CFlensburg didnt get to ask at qanda. do you have to be careful with cnv on RNAseq if the samples were pooled? got caught out by pooled mice calling variants on RNAseq #abacbs2018 0.9848195

Topic 6

screen_name text gamma
aljabadi Taiyun Kim explains how #kmeans clustering performed better when using correlation-based similarity measures (Pearson and Spearman) than when distance-based ones were used considering pre-defined labels. #confBingo #abacbs2018 https://t.co/lZLQXG0w31 0.9887605
davisjmcc .@TonyPapenfuss rightly acknowledges outstanding support from sponsors to enable provision of childcare at #ABACBS2018. Really important initiative to make it easier for parents to attend the conference! Let’s push to make this a normal provision for conferences. 0.9881449
AliciaOshlack There are several reasons why rare disease cases remain undiagnosed: 1) variant of unknown significance (lots of work happening here) 2) variants we still don’t have tools (methods, technology)to detect 3) not genetic My lab is interested in 2) #abacbs2018 0.9874581
YiwenWang_Eva Glad that people are interested in how to select methods to adjust for batch effect, even though not for microbiome data. I got many good questions and suggestions today! #abacbs2018 @tpq__ @annaquagli @mritchieau Thanks for the picture from my friends! @youyupei @jiaan_yu https://t.co/WlsNTT6gCx 0.9866867
RoxaneLegaie Professional Bioinformaticians attending #abacbs2018 (#abacbs18) Join us for the social event at the Shaw Davey Slum after the @abacbs opening ceremony tonight! https://t.co/CmWQ4RMjAO 0.9836746
_hollywhitfield A very well explained maths-y talk by Vivian Yeung. I’m impressed that post-5pm Holly can understand all of this, great job! #abacbs2018 #ABACBS18 https://t.co/w8JfBQyKIo 0.9836746
mdziemann Thanks to everyone who visited my #ABACBS2018 poster today to discuss bulk reprocessing of RNA-seq data. ICYMI I’ve posted the PDF online https://t.co/eDhYwskgml 0.9836746
shazanfar #abacbs2018 superFreq RNA-Seq doesn’t require matched normals for estimating CNV, but requires at least some normals as a reference @CFlensburg https://t.co/wk6PNl2mRZ 0.9823430
hdashnow @egiannoulatou: Theme of today - short variant calling is not a solved problem! Most callers assume reads have independent errors, but this isn’t true! #abacbs2018 0.9823430
AliciaOshlack

Conference bingo prizes up for grabs. Get your bingo card here. Good luck #confBingo #abacbs2018 #ABACBS18

https://t.co/TsHcgYWIiU https://t.co/EciRSAmGXA 		0.9807748

Session info

## ─ Session info ───────────────────────────────────────────────────────────────
##  setting  value                       
##  version  R version 4.0.0 (2020-04-24)
##  os       macOS Catalina 10.15.6      
##  system   x86_64, darwin17.0          
##  ui       X11                         
##  language (EN)                        
##  collate  en_US.UTF-8                 
##  ctype    en_US.UTF-8                 
##  tz       Europe/Berlin               
##  date     2020-09-01                  
## 
## ─ Packages ───────────────────────────────────────────────────────────────────
##  package      * version    date       lib source                          
##  askpass        1.1        2019-01-13 [1] CRAN (R 4.0.0)                  
##  assertthat     0.2.1      2019-03-21 [1] CRAN (R 4.0.0)                  
##  backports      1.1.8      2020-06-17 [1] CRAN (R 4.0.0)                  
##  bitops         1.0-6      2013-08-17 [1] CRAN (R 4.0.0)                  
##  callr          3.4.3      2020-03-28 [1] CRAN (R 4.0.0)                  
##  clamour      * 0.1.0      2020-09-01 [1] Github (lazappi/clamour@c8ea1c7)
##  cli            2.0.2      2020-02-28 [1] CRAN (R 4.0.0)                  
##  colorspace     1.4-1      2019-03-18 [1] CRAN (R 4.0.0)                  
##  crayon         1.3.4      2017-09-16 [1] CRAN (R 4.0.0)                  
##  curl           4.3        2019-12-02 [1] CRAN (R 4.0.0)                  
##  digest         0.6.25     2020-02-23 [1] CRAN (R 4.0.0)                  
##  dplyr        * 1.0.1      2020-07-31 [1] CRAN (R 4.0.2)                  
##  ellipsis       0.3.1      2020-05-15 [1] CRAN (R 4.0.0)                  
##  emo          * 0.0.0.9000 2020-08-17 [1] Github (hadley/emo@3f03b11)     
##  evaluate       0.14       2019-05-28 [1] CRAN (R 4.0.0)                  
##  fansi          0.4.1      2020-01-08 [1] CRAN (R 4.0.0)                  
##  farver         2.0.3      2020-01-16 [1] CRAN (R 4.0.0)                  
##  forcats      * 0.5.0      2020-03-01 [1] CRAN (R 4.0.0)                  
##  fs           * 1.5.0      2020-07-31 [1] CRAN (R 4.0.2)                  
##  generics       0.0.2      2018-11-29 [1] CRAN (R 4.0.0)                  
##  ggforce        0.3.2      2020-06-23 [1] CRAN (R 4.0.2)                  
##  ggplot2      * 3.3.2      2020-06-19 [1] CRAN (R 4.0.2)                  
##  ggraph       * 2.0.3      2020-05-20 [1] CRAN (R 4.0.0)                  
##  ggrepel      * 0.8.2      2020-03-08 [1] CRAN (R 4.0.0)                  
##  ggtext       * 0.1.0      2020-06-04 [1] CRAN (R 4.0.2)                  
##  glue           1.4.1      2020-05-13 [1] CRAN (R 4.0.0)                  
##  graphlayouts   0.7.0      2020-04-25 [1] CRAN (R 4.0.0)                  
##  gridExtra      2.3        2017-09-09 [1] CRAN (R 4.0.0)                  
##  gridtext       0.1.1      2020-02-24 [1] CRAN (R 4.0.2)                  
##  gtable         0.3.0      2019-03-25 [1] CRAN (R 4.0.0)                  
##  here         * 0.1        2017-05-28 [1] CRAN (R 4.0.0)                  
##  highr          0.8        2019-03-20 [1] CRAN (R 4.0.0)                  
##  htmltools      0.5.0      2020-06-16 [1] CRAN (R 4.0.0)                  
##  httr           1.4.2      2020-07-20 [1] CRAN (R 4.0.2)                  
##  igraph       * 1.2.5      2020-03-19 [1] CRAN (R 4.0.0)                  
##  janeaustenr    0.1.5      2017-06-10 [1] CRAN (R 4.0.0)                  
##  jsonlite       1.7.0      2020-06-25 [1] CRAN (R 4.0.0)                  
##  kableExtra   * 1.2.1      2020-08-27 [1] CRAN (R 4.0.2)                  
##  knitr        * 1.29       2020-06-23 [1] CRAN (R 4.0.0)                  
##  labeling       0.3        2014-08-23 [1] CRAN (R 4.0.0)                  
##  lattice        0.20-41    2020-04-02 [1] CRAN (R 4.0.0)                  
##  lifecycle      0.2.0      2020-03-06 [1] CRAN (R 4.0.0)                  
##  lubridate    * 1.7.9      2020-06-08 [1] CRAN (R 4.0.0)                  
##  magick       * 2.4.0      2020-06-23 [1] CRAN (R 4.0.0)                  
##  magrittr       1.5        2014-11-22 [1] CRAN (R 4.0.0)                  
##  markdown       1.1        2019-08-07 [1] CRAN (R 4.0.0)                  
##  MASS           7.3-51.6   2020-04-26 [1] CRAN (R 4.0.0)                  
##  Matrix         1.2-18     2019-11-27 [1] CRAN (R 4.0.0)                  
##  modeltools     0.2-23     2020-03-05 [1] CRAN (R 4.0.0)                  
##  munsell        0.5.0      2018-06-12 [1] CRAN (R 4.0.0)                  
##  NLP            0.2-0      2018-10-18 [1] CRAN (R 4.0.0)                  
##  openssl        1.4.2      2020-06-27 [1] CRAN (R 4.0.0)                  
##  pillar         1.4.6      2020-07-10 [1] CRAN (R 4.0.2)                  
##  pkgconfig      2.0.3      2019-09-22 [1] CRAN (R 4.0.0)                  
##  plyr           1.8.6      2020-03-03 [1] CRAN (R 4.0.0)                  
##  png            0.1-7      2013-12-03 [1] CRAN (R 4.0.0)                  
##  polyclip       1.10-0     2019-03-14 [1] CRAN (R 4.0.0)                  
##  processx       3.4.3      2020-07-05 [1] CRAN (R 4.0.2)                  
##  ps             1.3.3      2020-05-08 [1] CRAN (R 4.0.0)                  
##  purrr        * 0.3.4      2020-04-17 [1] CRAN (R 4.0.0)                  
##  R6             2.4.1      2019-11-12 [1] CRAN (R 4.0.0)                  
##  RColorBrewer * 1.1-2      2014-12-07 [1] CRAN (R 4.0.0)                  
##  Rcpp           1.0.5      2020-07-06 [1] CRAN (R 4.0.0)                  
##  RCurl          1.98-1.2   2020-04-18 [1] CRAN (R 4.0.0)                  
##  reshape2       1.4.4      2020-04-09 [1] CRAN (R 4.0.0)                  
##  rlang          0.4.7      2020-07-09 [1] CRAN (R 4.0.2)                  
##  rmarkdown      2.3        2020-06-18 [1] CRAN (R 4.0.0)                  
##  rprojroot      1.3-2      2018-01-03 [1] CRAN (R 4.0.0)                  
##  rstudioapi     0.11       2020-02-07 [1] CRAN (R 4.0.0)                  
##  rtweet       * 0.7.0      2020-01-08 [1] CRAN (R 4.0.0)                  
##  rvest        * 0.3.6      2020-07-25 [1] CRAN (R 4.0.2)                  
##  scales         1.1.1      2020-05-11 [1] CRAN (R 4.0.0)                  
##  selectr        0.4-2      2019-11-20 [1] CRAN (R 4.0.0)                  
##  sessioninfo    1.1.1      2018-11-05 [1] CRAN (R 4.0.0)                  
##  slam           0.1-47     2019-12-21 [1] CRAN (R 4.0.0)                  
##  SnowballC      0.7.0      2020-04-01 [1] CRAN (R 4.0.0)                  
##  stringi        1.4.6      2020-02-17 [1] CRAN (R 4.0.0)                  
##  stringr      * 1.4.0      2019-02-10 [1] CRAN (R 4.0.0)                  
##  tibble         3.0.3      2020-07-10 [1] CRAN (R 4.0.2)                  
##  tidygraph      1.2.0      2020-05-12 [1] CRAN (R 4.0.0)                  
##  tidyr        * 1.1.1      2020-07-31 [1] CRAN (R 4.0.2)                  
##  tidyselect     1.1.0      2020-05-11 [1] CRAN (R 4.0.0)                  
##  tidytext     * 0.2.5      2020-07-11 [1] CRAN (R 4.0.2)                  
##  tm             0.7-7      2019-12-12 [1] CRAN (R 4.0.0)                  
##  tokenizers     0.2.1      2018-03-29 [1] CRAN (R 4.0.0)                  
##  topicmodels  * 0.2-11     2020-04-19 [1] CRAN (R 4.0.0)                  
##  tweenr         1.0.1      2018-12-14 [1] CRAN (R 4.0.0)                  
##  usethis        1.6.1      2020-04-29 [1] CRAN (R 4.0.0)                  
##  utf8           1.1.4      2018-05-24 [1] CRAN (R 4.0.0)                  
##  vctrs          0.3.2      2020-07-15 [1] CRAN (R 4.0.2)                  
##  viridis      * 0.5.1      2018-03-29 [1] CRAN (R 4.0.0)                  
##  viridisLite  * 0.3.0      2018-02-01 [1] CRAN (R 4.0.0)                  
##  webshot      * 0.5.2      2019-11-22 [1] CRAN (R 4.0.0)                  
##  withr          2.2.0      2020-04-20 [1] CRAN (R 4.0.0)                  
##  wordcloud    * 2.6        2018-08-24 [1] CRAN (R 4.0.0)                  
##  xfun           0.16       2020-07-24 [1] CRAN (R 4.0.2)                  
##  xml2         * 1.3.2      2020-04-23 [1] CRAN (R 4.0.0)                  
##  yaml           2.2.1      2020-02-01 [1] CRAN (R 4.0.0)                  
## 
## [1] /Library/Frameworks/R.framework/Versions/4.0/Resources/library