Parameter Value
hashtag #gi2019
start_day 2019-11-06
end_day 2019-11-09
timezone America/New_York
theme theme_light
accent #005190
accent2 #7FA8C7
kcore 5
topics_k 9
bigram_filter 5
fixed TRUE
seed 1

Introduction

An analysis of tweets from the #gi2019 hashtag for the [Genome Informatics conference][GI2019], 6-9 November 2019, at Cold Spring Harbor Laboratories, New York, USA.

A total of 3820 tweets from 1053 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 2019-11-06 - 2019-11-09 in the America/New_York 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

Day 4

Original

Day 1

Day 2

Day 3

Day 4

Retweets

Day 1

Day 2

Day 3

Day 4

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 5. Node colour and size adjusted according to PageRank score.

5 Tweet types

5.1 Retweets

Proportion

Count

Top 10

screen_name text retweet_count
lpachter I highly recommend “How to read (single-cell RNA-seq) PCA plots” (by @vallens): https://t.co/Co3A47SZTR #gi2019 He notes that “A particular danger [in interpreting T-shapes] is that it is tempting to interpret this as a bifurcation in the data.” (it almost never is). #gi2019 256
lh3lh3 I am looking for one or two postdocs working on bioinformatics and computational biology in general. Find me at #gi2019 if you are around. https://t.co/cZpnhzMAtr 204
aphillippy Heng is amazing. Go work for him. If he turns you down, come talk to me. I am also looking for students and postdocs at #gi2019 😆 https://t.co/uuuMq6gXLJ 74
ACSCevents Save the date - Genome Informatics 2020 - 14-17 Sept at the genome campus #GI2020 #gi2019 https://t.co/EfCc74qrCR 62
lpachter A reminder: “cluster sizes in a t-SNE plot mean nothing” https://t.co/GUe2BTFLEO #gi2019 46
hdashnow I’m presenting STRling, our new method to detect novel (and reference) STR expansions from short-read data. https://t.co/hPyL7WBhkI #gi2019 Big thanks to @brent_p who has done a huge amount of work on this algorithm and is an all around fantastic guy to work with. 42
BenLangmead

Slides from my #gi2019 talk this morning, about work primarily by @dnb_hopkins: https://t.co/lZYnBK8dhm

Software: https://t.co/JALMMmfSca

Library: https://t.co/8Yifw0NUsz 		28
deannachurch Also- I’m looking for someone to lead my Informatics/analysis group- and single cell experience is a must! Help build the next generation of genomics tools using genome engineering! https://t.co/v8vzvssQUM #gi2019 27
infoecho Real bioinformatics “file parsing”!!#gi2019 https://t.co/4vll3qI61u 23
lpachter We’ve posted the kallisto | bustools poster presented by @sinabooeshaghi at #gi2019 on @F1000Research https://t.co/EVxAXZvGAC https://t.co/inzS4JAeUZ 22

Most retweeted

5.2 Likes

Proportion

Count

Top 10

screen_name text favorite_count
lpachter I highly recommend “How to read (single-cell RNA-seq) PCA plots” (by @vallens): https://t.co/Co3A47SZTR #gi2019 He notes that “A particular danger [in interpreting T-shapes] is that it is tempting to interpret this as a bifurcation in the data.” (it almost never is). #gi2019 757
lh3lh3 I am looking for one or two postdocs working on bioinformatics and computational biology in general. Find me at #gi2019 if you are around. https://t.co/cZpnhzMAtr 230
samstudio8 Made it to #gi2019 at @CSHL. My metagenomic assembly graph artwork is the book cover! https://t.co/T2X6EPqweC 187
lpachter A reminder: “cluster sizes in a t-SNE plot mean nothing” https://t.co/GUe2BTFLEO #gi2019 166
aphillippy Heng is amazing. Go work for him. If he turns you down, come talk to me. I am also looking for students and postdocs at #gi2019 😆 https://t.co/uuuMq6gXLJ 165
ACSCevents Save the date - Genome Informatics 2020 - 14-17 Sept at the genome campus #GI2020 #gi2019 https://t.co/EfCc74qrCR 136
sexchrlab

I can’t begin to tell you how much I love the openness of Genome Informatics. I know science has a long way to go, but the culture of sharing data and code, and emphasizing validation; it warms my heart.

#GI2019 		131
infoecho A Manhattan plot for #GI2019 https://t.co/Jpamfgex8e 108
hdashnow I’m presenting STRling, our new method to detect novel (and reference) STR expansions from short-read data. https://t.co/hPyL7WBhkI #gi2019 Big thanks to @brent_p who has done a huge amount of work on this algorithm and is an all around fantastic guy to work with. 103
chrisamiller

SN: Not every bioinformatician gets to go to the algorithm ball. Some of them have to stay home and write pipelines

Preach, brother 😆 #gi2019 		98

Most likes

5.3 Quotes

Proportion

Count

Top 10

screen_name text quote_count
AliciaOshlack We already have two new posters on our @F1000Research Channel for this year’s conference #Gi2019. Check them out at your leisure https://t.co/Qi3BJYQCs5 4
AliciaOshlack We already have 5 posters up on the website for you to look at before the poster session #GI2019 https://t.co/xrktvzLo6G https://t.co/qSNoUoImSe 4
dsurujon What a great idea! Here are my slides for my #gi2019 talk on Friday on how transcriptomic chaos can predict bacterial fitness https://t.co/zXVnqfAcfx https://t.co/4DBC2pID7I 4
ascendox RT mike_schatz "RT AliciaOshlack: We already have two new posters on our F1000Research Channel for this year’s conference #Gi2019. Check them out at your leisure https://t.co/pz1UEPRaQ3"; 4
AdamJOrr Guest tweeter in @lh3lh3 ’s #gi2019 talk https://t.co/oLWLyS6ucx 2
nephantes Heng Li @lh3lh3: nextflow pipeline used for liftover hg38 -> hg19 ☑️ sucessfully. :) @nextflowio #gi2019 https://t.co/zdDOrcO8zo 2
AliciaOshlack Sad that @sexchrlab wasn’t able to be here to do the opening of #gi2019 with us because of stupid flight cancellations https://t.co/DbTTm0vPsr 2
AliciaOshlack I actually really like this photo. Who would have thought that @pathogenomenick and I only met for the first time 10 mintues before that #gi2019 https://t.co/DbTTm0vPsr 2
aphillippy Heng is amazing. Go work for him. If he turns you down, come talk to me. I am also looking for students and postdocs at #gi2019 😆 https://t.co/uuuMq6gXLJ 2
michelebusby #gi2019 PhDs: Please don’t take yourself out the running for this because you’ve been using Heng’s tools for the last 5 years and are intimidated! I always learn a lot when I talk to Heng (as does the whole community) and this is a great opportunity. Take your shot. https://t.co/5grj3gBP1j 2

Most quoted

6 Media

Proportion

Top 10

screen_name text favorite_count
samstudio8 Made it to #gi2019 at @CSHL. My metagenomic assembly graph artwork is the book cover! https://t.co/T2X6EPqweC 187
ACSCevents Save the date - Genome Informatics 2020 - 14-17 Sept at the genome campus #GI2020 #gi2019 https://t.co/EfCc74qrCR 136
infoecho A Manhattan plot for #GI2019 https://t.co/Jpamfgex8e 108
lpachter We’ve posted the kallisto | bustools poster presented by @sinabooeshaghi at #gi2019 on @F1000Research https://t.co/EVxAXZvGAC https://t.co/inzS4JAeUZ 89
infoecho Real bioinformatics “file parsing”!!#gi2019 https://t.co/4vll3qI61u 74
cshlmeetings As #gi2019 wraps up, we’d like to thank meeting sponsor @genome_gov; co-orgs @pathogenomenick, @AliciaOshlack and @sexchrlab; and those who live-tweeted during the entire meeting (especially during the lightning talk session)! See everyone at #gi2021! https://t.co/awkC8GZHTW https://t.co/RAEBm3zce3 70
aphillippy @AliciaOshlack and @pathogenomenick kicking off #gi2019. So many legendary bioinformagicians in attendance. Love this meeting! https://t.co/BIMjUNC1E2 65
yoson Guess which session this was (poll below) #gi2019 https://t.co/UBQJZdFLyn 57
AliciaOshlack Chalkboard update for Genome Informatics meeting 2020 and 2021. Put it in your diaries. #gi2019 https://t.co/3fwbfGaVsx 47
iddux @samstudio8 at #gi2019 on the difference between CPU and GPU tasks. “CPU is like two postdocs, they can do complex work but are easily distracted and need to do other things too. GPU is like an army of babies that can do just one simple thing, but can do it quickly and forever” https://t.co/rjQMzm7Tv3 45

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 5 times.

7.5 Topic modelling

Top 10 words associated with 9 topics identified by LDA.

7.5.1 Representative tweets

Most representative tweets for each topic

Topic 1

screen_name text gamma
Refasho The fitting shoes #PixarSoul #gi2019 #WIZONELOVEIZONE #ThankfulThursday #BWFWarren #Obsession #ODMUnleashesGoons #JusticeForAsim #1026大切なユタの日 #10yearsofdanandphil #10월에_태어난_병아리_윈윈 #nyc #ny #344 #bloomfieldav #uppermontclair #montclair #newark #kearny #edison #byc https://t.co/efM3QsnsQH 0.9905997
Magdoll Bzikadze: centroFlye for centromere assembly - identify centromeric reads, classify as prefix/internal/suffix, find rare/unique k-mers –> represent reads as k-mer clouds –> build contigs –> polish. Rub: need to deal w errors #gi2019 0.9899113
pmelsted STR: several methods for reference STR (all using puns including the letters STR). Canvas (ataxia) disease, reference genome has alu element and AAAAG_n motif, disease elements have AAGGG_n motif, reference based methods fail to detect these #gi2019 0.9895278
pmelsted SK: can get 4x enrichment of a fungal genome within a bacterial community. Human gene enrichment, 28 genes from breast cancer panel. Mapping to a 3.5M reference, eject reads after 3sec. 2.8x enrichment. Showing fresh results obtained on Monday #gi2019 0.9895278
pmelsted SK: ONT real time, read-until can monitor the sequence, up to 512 channels at 450bp/sec. UNCALLED maps 10kbp/sec per thread, 75% of reads classified within 1 sec, [aside: ONT can eject reads from pores, saving on sequencing]. #gi2019 0.9886662
lizworthey KR: multiple global genomic measures being considered; telomere length, genome complexity, coding mutational burden, mutational signatures describing factors that have impacted genome e.g. smoking/age #gi2019 0.9876502
pathogenomenick Andrey Bzikadze talking about centromere assembly with centroFlye: bigging up @khmiga and @aphillippy’s burgeoning T2T Consortium data which has huge haul of ultra-long reads and complementary technologies for human haploid genome: https://t.co/bNU6QpvEfI #gi2019 0.9876502
ascendox RT mike_schatz “RT Magdoll: Aganezov: how to retrace cancer rearrangement history? formulate as minimal eulerian decomposition problem. to deal with non-unique solutions, form as consistent contig covering problem (<–this is new to me). #gi2019 prep… https://t.co/tKWOjW7ITd” 0.9870707
pmelsted AB: length of centromere of X is ~2.8Mbp, consists of repeats of 171bp repeats, in 12 units that are DXZ1. Centromeres are 3% of reference, play a critical role in chrom segregation, variations are linked to cancer and infertility #gi2019 0.9870707
bnlasse

#gi2019 @AndreyBzikadze: centroFlye-Assembling centromeres w/ long error-prone reads

Telomere-to-tel consortium: https://t.co/HdmPfXmTTk https://t.co/Sg82pHMR3q

centroFlye: ID unique k-mers in centromere, use for centro. assembly https://t.co/X6KKGbvJmv https://t.co/0luMvnOzYm 		0.9864341

Topic 2

screen_name text gamma
pmelsted HL: Incremental graph construction. Invariant property: linear path (original genome) and acyclic. Seq to graph alignment: Find seeds in segments, use linear chaining ignoring topology. Graph chaining, use graph topology to line up chains. Search best path with heuristics #gi2019 0.9905997
bnlasse

#gi2019 Heng Li @lh3lh3 The construct & utility of reference pan-genome graphs

Plan: start w/ GRCh38, incrementally add other genomes to construct graph, blacklist & decoy seqs for linear tools, updates preserve coordinate sys

https://t.co/B6XVbWQX50 https://t.co/NcTsAbyPyg 		0.9899113
pmelsted HL: VCF, hard to represent small variants on long insertions wrt reference. GFA format, two components. S-line segments that are sequences, L-line: links between segments. Most popular assembly format. GFA coordinates are unstable, can split segment and change coordintes #gi2019 0.9899113
bnlasse

#gi2019 Shilpa Garg: Efficient chr-scale haplotype-resolved assembly of human individuals

method leverages long accurate reads+long-range conformation data for individuals to generate chr-scale phased assembly w/in a day

👀👇 https://t.co/4M17NhWId8 https://t.co/XhXlNj9TBl 		0.9895278
bnlasse

#gi2019 M Pertea, Efficient & robust transcriptome reconstruction from long-read RNA-seq alignments

Based on StringTie, short read transcriptome assembler: https://t.co/Kjg3ng0GPt

StringTie2, long read sln, overcome error rate and lower throughput 👀👇 https://t.co/00KzRLeRnH 		0.9891140
pmelsted Heng Li, @lh3lh3: Pangenomes, construction and utility. Styles of pangenome graphs: assembly style graph (large messy), linear graph (string of bubbles). Linearity no 2 bases on a haplotype can be mapped to the same graph position. VCF is linear #gi2019 0.9886662
pmelsted HL: sad stories about Gnomad taking 6 years to move to Grch38 and someone running liftover to hg19 from Gnomad v3. New restricted format rGFA. Can incrementally add genomes to construct a graph. Updates preserve coordinate system #gi2019 0.9886662
kasukawa

Utilization of consensus genome, in which minor alleles are replaced to major ones.

Interestingly, pan-human consensus genome is adequate to reduce error rates. Even if using consensus genomes specific to subpopulations, the error rates were not reduced.

#gi2019 		0.9881800
pmelsted EE: Phased assembly, uses linked reads to phase, hifi reads to construct contigs. 81% of hifi reads can be assigned to a haplotype. Regions that were problematic for canu and peregrine assemblers, about 250, colocalized with segmental duplications. #gi2019 0.9876502
lizworthey MK: discussing cow rumen metagenome 11.4 Gb, N50=11Kb. assembly 268 Mr, N50=230Kb. 44 contigs> 1Mb After assemble using tools found 649 bubbles, 96 superbubbles, 210 shared bubbles #gi2019 0.9876502

Topic 3

screen_name text gamma
pmelsted TG: Filtering FPs using dual strand filter, nanopolish has highest sensitivity at high coverage. Phased variants in TP53 region using WhatsHap. Phasing of normal vs tumor tissue revealed cancer specific snps and a copy number difference between alleles in tumor #gi2019 0.9895278
pmelsted TG: High coverage of targeted regions means you can call SNPs better (except for homopolymer sites). Comp of tools, samtools, clair, medaka and nanopolish. 0.98 sensitivity for nanopolish and samtools at 200x cov (still a number of FPs), FPs often from a single strand #gi2019 0.9891140
pmelsted Daniel Cameron on structural variation and CNV from cancer samples. Fully automated oncology reports, no possibility of manual intervention. Wrote 3 software for SV calling (GRIDSS), CNV calling (PURPLE) and interpretation (LINX) #gi2019 0.9881800
chrisamiller

DC: How can we make good, clinic-ready structural variant calls from tumor patients?

  • 110x WGS tumor/normal.

  • Pipeline uses GRIDSS (breakend assembly) -> PURPLE (CN calling) -> LINX (annotation) #gi2019

0.9881800

YiXing77

My student Yang Pan @ypnngaa will present his work on PEGASAS, pathway guided analysis of alternative splicing, at the upcoming Penn #RNA club next Tuesday! He also has a poster about PEGASAS at CSHL #gi2019 this week. #IOTN #Moonshot https://t.co/jzIJSD6wWU

0.9876502

Repealist_

Commuting to @CSHL #gi2019 meet and stopped off at Sutphin Blvd waiting for a train

Have already talked to three Bangla families and one Korean gal

And the morning fishmarkets are truly the view of dreams

One for you @MichaelsCoDub https://t.co/glRsqxmruN 		0.9857315
lizworthey DC: developed a set of tools to better call SVs. Wrote a new GRIDSS based tool for SVs, Purple specifically for CNV, and a tool called LINX for variant interpretation #gi2019 0.9857315
byuhobbes @BenLangmead alternative to the bottom k approach (aka min hashing) is k-partition approach; break up k-mer space into k partitions, take the bottom element of each partition; similar characteristics to min hashing #gi2019 0.9857315
Magdoll Gangavarapu: West Nile virus shown to persist through the seasons and circulate across all regions in California. Unable to link it to surviving in birds (or mosquitos? someone correct me) in winter (no seasonality). #gi2019 0.9849523
byuhobbes @MedhatHelmy7 @MedhatHelmy7 Benchmarked variant calling and phasing tools with GIAB data catalog; better SNV calling performance with 10x coverage from PacBio CCs vs 25x from PacBio CLR or 25x from ONT #gi2019 0.9849523

Topic 4

screen_name text gamma
bnlasse

#gi2019 A Balsubramani; Multi-resolution, interactive, atlas-scale integration of single-cell assays & exper.

Unify datasets from diff experiments? Connect w/ anchors, impute/co-embedding, refine on subpops and repeat.

Their approach=Musica [I don’t think released quite yet] 		0.9891140
lpachter Now Akshay Balsubramani talking about integrating data from single-cell RNA-seq experiments (w/ @anshulkundaje). This is an important topic. Full disclosure: we’ve been partial to @_romain_lopez_’ et al.’s scVI in my lab but constant exciting new ideas in this area. #gi2019 0.9864341
Magdoll Balsubramani: unifying single cell RNA-seq experiments. steps: anchor (find cells of similar cell types) –> impute features –> refine co-embedding. repeat. #gi2019 0.9864341
byuhobbes @Magdoll @Magdoll Suggests that single-cell platforms produce shorter transcripts than bulk full-length cDNA; using proximity to CAGE peaks as orthogonal evidence of 5’ completeness; polyadenylation signals for 3’ completeness #gi2019 0.9857315
lpachter I highly recommend “How to read (single-cell RNA-seq) PCA plots” (by @vallens): https://t.co/Co3A47SZTR #gi2019 He notes that “A particular danger [in interpreting T-shapes] is that it is tempting to interpret this as a bifurcation in the data.” (it almost never is). #gi2019 0.9857315
lpachter A special privilege of attending a @CSHL meeting is that one can learn about recent research via glimpses at unpublished data. But when it comes to methods talks at meetings such as #gi2019 I think there should be a public Github repo or equivalent. https://t.co/kYT0vLduvQ 0.9857315
sexchrlab

In past years, we tried to add a place for abstract submitters to add a link to software repos/web interfaces; I think this would be great to bring back.

Genome Informatics slides and posters have and can be posted here (please share!): https://t.co/aWCJRpKmnD

#gi2019 		0.9849523
YiXing77 @DNAwyman of UCI presenting the ENCODE TALON software for long read RNA-seq data analysis https://t.co/7QDZvNwxcn. Also nice to see a figure from our AJHG review https://t.co/QS52kMJaiB by @RNAEddie used in the Intro! #gi2019 https://t.co/MhKOMKNUxO 0.9849523
cshlmeetings Meet @samstudio8 of @unibirmingham! He’s busy at #gi2019. He gave a talk, his work is featured on the cover of the meeting’s abstract book, and is meeting in person the Twitter avatars with whom he’s been messaging the past year or so! #cshlvisitor https://t.co/6HmQ9eKFCb 0.9840830
winhide #gi2019 we are looking for a post doc who wants to work with an amazing team (I mean it!) Want to find the best drug that drives resilience against Alzheimer’s? Join us! - the NIH funded this work. Chat to Sarah Morgan at the meeting. https://t.co/0b4pyljOJl 0.9831071

Topic 5

screen_name text gamma
lizworthey SLH: Process is RNA-seq, run data (on Dragen on AWS) through FusionMap, JAFFA, STARfusion, FusionCatcher, MapSplice, and TopHat fusion with overlap analysis, hierarchical prioritization, knowledge based filtering, and then CAP-CLIA validation of clinically relevant vars #gi2019 0.9902676
bnlasse

#gi2019 S LaHaye: Utilization of ensemble approach for ID of driver fusions in peds cancer

Ensemble approach reduces false +s 6 tools (FusionMap, JAFFA, STARfusion, FusionCatcher, MapSplice, TopHat Fusion) DRAGEN to speedup [seems to ID 98% in test] Seraseq as truth 		0.9899113
chrisamiller SL: Using a ensemble approach of 6 gene-fusion callers to identify fusions in ped cancer. Overlap (by at least 2 callers), prioritize based on evidence, and compare to a knowledge base. Final step is CAP/CLIA RT-PCR or sanger validation #gi2019 0.9895278
bnlasse

#gi2019 Xi Chen, ‘Tissue-specific enhancer functional networks for associating distal regulatory regions to disease’

How interpret/predict fxn of enhancers/disease-associated enhancers? Bayesian inference: https://t.co/JjuT1Ar8pq (try it!)

autism e.g.: https://t.co/TlWmLl7CXY 		0.9886662
lpachter @sinabooeshaghi @GoogleColab @jspacker @jisaacmurray @JunhyongKim @sinabooeshaghi: kallisto | bustools runs up to 100 times faster than Cell Ranger, 25 times faster than Alevin and 4 times faster than STARsolo https://t.co/GGveUbyaUu Many features and capabilities not available with other tools. See poster this afternoon at #gi2019. 0.9876502
chrisamiller

LINE1 activity correlates with poor immunotherapy response.

Suggests that LINE1 high tumors are cloaked in a way that’s sidesteps activation with std imm. therapy (if they weren’t cloaked, they’d already be gone, since high LINE1 triggers response in normal cells!) #gi2019 		0.9870707
lizworthey gloria integration of ALzheimers disease genetics and myeloid cell genomics to revel novel risk mechanisms HiC, epigenomics, GWAS hits to identify causal genes and loci and validated in microglia #gi2019 0.9870707
lizworthey anoushka joglekar on enhanced interpretation of single-cell isoform RNA sequencing to reveal distinct programs of alternative splicing in the developing mouse brain correlated to RNA splicing machinery #gi2019 0.9870707
Magdoll .@dsurujon : gene expression is more chaotic in low fitness bacteria, this means using entropy (measuring chaos in gene expression) can predict fitness. but need to model for co-expressed genes that break the independence assumption. #gi2019 0.9864341
lizworthey Katherin Woolley-Allen asking what is the weakest level off transcriptional factor binding that can exert an effect; evolution has gone further towards lower and lower affinity binding sites acting in combination #gi2019 0.9849523

Topic 6

screen_name text gamma
byuhobbes @s_ramach @s_ramach Question: how are ROHs distributed in the genome? Parent-child data in 23andMe has revealed extremely long IBD segments in putatively normal individuals; reflection of uniparental disomy, where both haplotypes inherited from a single parent #gi2019 0.9876502
bnlasse

#gi2019 Karine Le Roch, ‘Comparative 3D genome organization in Apicomplexan parasites’

Overall, work supports link between genome organization and gene expression in more virulent pathogens

learn more from their recent pubs: https://t.co/0bG5uj8tvD https://t.co/Fc3Ar3U8re 		0.9876502
lizworthey SA: using a combination of 30x 10X, 40x ONT, and 40x PacBio and aligning with Long ranger and NGMLR. calling with lumpy, manta, SvABA, GROCSV, NAIBR, LongRanger, sniffles, PBSV and combined using survivor methods #gi2019 0.9876502
GenomeBiology SR: has been looking at runs of homozygosity (ROH) in 23andMe data. Parent-child data reveals extremely long shared segments eg child has whole chromosome with no sequence shared with father - called uniparental disomy #gi2019 0.9870707
CalvinH43357785

Uncanny Attraction #astroworldfestival #AUSvPAK #Bigil #BREAKING #crush #ChangeForWonho #ChaseYoung #DeathStrading #DoctorSleepMovie #EricCiaramella #EpsteinSuicideCoverUp #EXOonearewe #Ethiopia #FlashbackFriday #FursuitFriday #gi2019 #GymJordan #G_I_DLE

https://t.co/FZVvn45dCp 		0.9864341
TwilightForce1

sPaCe oVeRtAkEn

#astroworldfestival #AUSvPAK #Bigil #BREAKING #crush #ChangeForWonho #ChaseYoung #DeathStrading #DoctorSleepMovie #EricCiaramella #EpsteinSuicideCoverUp #EXOonearewe #Ethiopia #FlashbackFriday #FursuitFriday #gi2019 #GymJordan #G_I_DLE

https://t.co/HAxVeeEsFk 		0.9864341
Magdoll Nakka: runs of homozygosity (ROH) are associated w divergence from Africa. Diff classes of ROH have diff mean/variance in population. How to study ROH distribution within a genome? @23andMe parent-child data! #gi2019 0.9864341
kasukawa

quantifying isoform expression in scRNA-seq data with STARsolo-Quant #gi2019

Quantifying each isoform based on the distribution function (by Maximum likelihood estimation) for distance to TTS and UMI barcoding. 		0.9864341
lpachter Interesting mention of kernel Canonical Correlation Analysis (KCCA) at #gi2019 by @KarineLeRoch1 for coupling genome organization data with gene expression data. Nonlinear CCA is complex and still not widely used in genomics. Related: https://t.co/ux3wgq7XpQ 0.9864341
Magdoll Nakka: mining 23&me parent-child data revealed cases of uniparental disomy (UPD) where both chromosomes of a parent is preserved with no copy from the other parent. This occurs due to non-disjunction during meiosis O__O #gi2019 0.9857315

Topic 7

screen_name text gamma
lizworthey KG: main goal of consortia is to provide real-time high definition reconstructions of the micro- (e.g., city/county) and macro-level (e.g., state/country) spread and evolution of WNV by sequencing from infected birds, mosquitoes, and patients #gi2019 0.9891140
Magdoll Dilthey: Applies MetMaps to PacBio HMP & ONT Zymo mock community achieves high read assignment on both. Caveat: reduced recall due to min RL 1kb; HMW DNA required. #gi2019 Paper here: https://t.co/KxePwF8jwM 0.9881800
byuhobbes @jkpritch @jkpritch Recent metaanalysis of schizophrenia GWAS studies found 108 genome-wide significant loci; most hits are difficult to interpret, and only explain 10% of the observed heritability (“missing heritability” problem); enormous number of small effects #gi2019 0.9876502
FadelBerkadar

A few words about novoSplice poster for the Genome Informatics meeting at CSHL #gi2019

  • The poster explains the general workflow of novoSplice besides preliminary benchmarking results using both simulated and real reads. Algorithmic details of the splic…https://t.co/fxeHNScOal
0.9870707
BBFCreativeEnt It must suck to support a racist president. This quote will bite you in the ass when you are up for reelection….It must suck to loose BIG to a democrat…and have to work in the private sector!#ThursdayMotivation #redcup #gi2019 #WashingtonPost #NYTimes #art #washingtinTimes https://t.co/aK9vZlnawo 0.9864341
Magdoll Mahmoud: PRICNESS: mapping (NGMLR/minimap2), SNV (Clair), SV (Sniffles), Phasing (WhatsHap, Princess-subtools), optionally can use parental SNPs and methylation (nano polish) . Also stats. #gi2019 0.9864341
ascendox RT mike_schatz “RT StevenSalzberg1: SamKovaka talking about”read until" sequencing on nanopore sequencers. Still experimental, but very cool that the sequencer can recognize DNA species in real time, and stop sequencing a read by reversing the current #gi2019" 0.9864341
lpachter at #gi2019 RP is suggesting that transcriptome alignment (substrate for RSEM, eXpress, kallisto..) is not as good as genome alignment. A comparison was performed by @alexlachmann et al. in https://t.co/Bg5QhHA4EY. They conclude “the quality of the predictions is almost identical” https://t.co/M8XM0eKAer 0.9864341
David_McGaughey Made it to #gi2019. First time staying at cshl Banbury campus. If you do scRNA stuffs make time to bother me about me 750k+, 14 study ocular integration project while you wait to talk to @pmelsted at poster session 1 (105). https://t.co/D87VAc39T9 0.9857315
lizworthey philip kleinert; CADD-SV tool to score the effect of SVs - whether they have strong effect on health by training to differentiate between benign and pathogenic. Use evolutionary motivated approach #gi2019 0.9849523

Topic 8

screen_name text gamma
bnlasse

#gi2019 Naihui Zhou: Exploring 3D spatial dependency of gene expr using Markov random fields

hypothesis: expr is spatially dependent

developed PHiMRF https://t.co/YQjn6CRXGO prob model for RNA-seq data accounting for gene locals in 3D genome (spatial dependency for count data) 		0.9914725
bnlasse

#gi2019 Sam Kovaka: Rapidly mapping raw @nanopore signal w/ UNCALLED to enable real-time targeted seq

ReadUntil seq bg: https://t.co/L5obZVjusq

UNCALLED: Maps raw nanopore signals from fast5 files to large DNA refs (preprint soon!) https://t.co/gyahq5GDBd 		0.9895278
Repealist_

Incidental window seat right near the front, space to get work done,

and it starts raining just as I’m leaving Dublin?

All the promising makings of a great journey to #gi2019 and #SUNY.

Slán a chairde 🇮🇪 tá sí ag dul go Nua-Eabhrac 🇺🇸! https://t.co/GTcyz95iNn 		0.9881800
pmelsted BL: Hyperlog (HLL) can process array of bits using SIMD values. Uses a bit more space by using a different base 1.19, fills up 8-bits rather than 6-bits with base 2. HLL performs better with lopsided data (large ratio of sizes between two sets) #gi2019 0.9881800
lpachter I agree we should not hold scientific meetings on weekends. I also think we should not hold scientific meetings on weekdays. Scientists with kids face enormous logistical challenges on weekdays (kid pickup/dropoff, school events, activities, etc.) #gi2019 https://t.co/ifuJZuV3ci 0.9876502
chrisamiller FN: answering why ancient LINEs so frequently show up in RNAseq. To make a long story short, seq similarity causes mismapping, and their tool TeXP can correct for this. Shows that basically all autonomous transcription is from recent families, as expected #gi2019 0.9864341
bnlasse

#gi2019 Ben Langmead: Genomic sketching w/ HyperLogLog

Sketching=how to sift&summarize huge datasets so can answer similarity ?s later

Dashing w/ HyperLogLog https://t.co/5MWtP6xfPD https://t.co/byoPzN12XA https://t.co/GSykouIW4c

[review of interest: https://t.co/OO5AklzeAz] 		0.9857315
GrameneDatabase If you missed @ajo2995 Andrew Olson’s delightful talk on Crop PanGenome Sites at #gi2019, look for us at the @cshlmeetings Wine and Cheese to savor a TE Cabernet and avoid being haunted by the ghost of Barbara McClintock https://t.co/eM88kVKzXv 0.9857315
Magdoll plot twist: Narechania, just like everyone else, is ditching base-alignments and going for k-mers. Alright, k-mer based ortholog matrix to infer HGT. But too many k-mers, so gotta compress them without info loss. #gi2019 0.9857315
hdashnow Yesterday I got my official PhD passed email while I was on stage at #gi2019 talking about work I’ve done since submitting my PhD in June. That is considered a relatively fast turn-around for an Australian PhD assessment! Thanks for being an awesome PhD supervisor @AliciaOshlack 0.9849523

Topic 9

screen_name text gamma
Magdoll (not related to #gi2019 but another TV idea - patient is admitted to Nationwide Childrens Hospital w rare disease and - panning to dramatic gradient boosted decision tree - reveals the patient has some ancestry from exotic land coinciding w mother’s younger traveling years) 0.9886662
bnlasse @lizworthey @UABSOM @UABPathology @uabpeds #gi2019 @lizworthey showing examples of software developed by her group for use by non-informatics experts and cases evaluated by her team’s secondary analysis pipeline including a ‘B-allele’ tool to look for chimerism/mosaicism missed by traditional pipelines 0.9870707
kasukawa

Plant genomes. Highly variable in the maize genome.

Gramene is a curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species. https://t.co/8TFAvyA56a

#gi2019 		0.9864341
GenomeBiology KR: looking at chronic lymphocytic leukemia. More prevalent in men than women. Patients can survive for years without treatment. 8-12% of patients have TP53 mutation, which corresponds with lower survival. Over 50% of patients with refractory CLL have no known marker #gi2019 0.9857315
Ailith_Ewing Anyone interested in chromothripsis in high grade serous ovarian cancer? Check out Stuart Brown’s poster this afternoon! And chat to Stuart, a PhD student with @DrColinSemple, Charlie Gourley and myself, to hear all about it! #gi2019 0.9849523
bnlasse @lizworthey @UABSOM @UABPathology @uabpeds #gi2019 sequencing approaches have been great, also seeing advances in software engineering/genome informatics/comp bio allowing us to identify other important variation (e.g., mobile insertions, etc.) @lizworthey 0.9849523
byuhobbes MM: SURFDAWave also trained a model to discriminate between neutral, sweep, and adaptive introgression; classification performance increased by supplementing 1D stats with 2D stats #gi2019 0.9840830
lizworthey AR: In house dataset contained pedigree data allowing access to confirmed parental ancestries so were able to determine if methods accurately predicted the composition in such individuals #gi2019 0.9840830
lizworthey Jiao Sun discussing computational methods to explore the role of post-transcriptional regulation in cancer; including integrative model for alternative polyadenylation #gi2019 0.9831071
bnlasse @lizworthey @UABSOM @UABPathology @uabpeds #gi2019 @lizworthey see another tool here: https://t.co/T7tCfipNOu; also discussing strategies they are developing for examining modifier variants that might explain differences in disease presentation and outcomes 0.9831071

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