dataesr/scientific-paragraphs-categorization huggingface dataset:
Impact of the technical platform on the results obtained by the different MFs To finally test the impact of the transcriptome profiling platforms on the results of the various MF algorithms we took advantage of four ovarian cancer transcriptomic datasets available from TCGA  (Bell et al. , 2011). These four datasets have been profiled with four different platforms: Affymetrix U133, Agilent and Affymetrix HuEx, plus RNAseq. 418 samples are in common among all four datasets. This resource is optimal to evaluate if the profiling platform affects the results of the various MFs. Indeed having four datasets composed of the same samples we are sure that no biological variability is present across them. In the optimal scenario, all the metagenes of an MF algorithm should find a RBH with a metagene of the other three datasets.
To thus assess which MF algorithm is less prone to technical noise, we applied to each MF step 1 and 2 of our new framework. We thus decomposed the four ovarian cancer datasets in 100 components and we then reconstructed the RBH graph. We finally checked the number of RBH links of the different MFs and their average absolute correlation. Stabilized ICA resulted to perform better than alternative approaches also in this case, with 390 links and average correlation of 0. 396 (see Supplementary Table  4  for all the results).
Stabilized ICA identifies consistent biological insights on CRC in respect to previous knowledge In previous sections we showed that Stabilized ICA performs better than alternative approaches according to multiple measures of practical interest for highthroughput data analysis. We thus now concentrate more deeply on the biological insights that can be derived from the RBH graph of this MF algorithm. To this aim we added to the analysis other four datasets: single-cell RNAseq from normal and tumoral CRC tissue  (Li et al. , 2017) , Patient-derived Xeno   5. graft (PDX) CRC Models and liver metastasis (LM)  (Isella et al. , 2017). We then biologically annotated the communities of the RBH graph by using metametagenes and metasamples according to the procedure described in the Methods section.
Finally, one community was found to be related to chromatin silencing and histones. The stromal communities instead include microenvironment signals, such as cancer-associated fibroblasts (CAFs), smooth muscle, immune, complement system and B-cells. Of particular interest is the identification of a community related to B-cells whose association to this cell type was evident not only using the MSigDB signatures (as discussed in Methods), but also from single-cell data. Looking indeed at the metasample of the component obtained from single-cell data and associated to this community we could clearly see B-cells being the most contributing in this component. The technical factors included instead GC-content and gender. Finally, 10 communities have been found to be associated with small groups of genes.
Discussion In this manuscript we compared the three most commonly used matrix factorization methods for their ability to detect reproducible and biologically interpretable signals in independent transcriptomic datasets of the same cancer type (CRC). For one of the methods, Independent Component Analysis, we also compared two protocols of its application to transcriptomic data, named Using multiple runs of ICA for stabilisation and prioritizing stable also significantly contributes to improving their reproducibility (see  (Kairov et al. , 2017). By contrast, PCA components appear to systematically mix multiple sources of transcriptome variability, reducing interpretability. Also, the higherorder PCA components are regularly not reproducible. The main problem of the NMF metagenes is that in application to gene expression data, most of them are strongly correlated with average gene expression.
The metagenes obtained through application of MF methods can be compared to other methods, sharing similar spirit. In particular, attractor metagenes were suggested in order to serve as surrogates of cancer phenotypes  (Cheng et al. , 2013). Attractor metagenes were used as variables in the DREAM Challenge winning approach for predicting breast cancer clinical outcome  (Margolin et al. , 2013). We find ICAbased framework for identifying metagenes more computationally elegant and potentially producing less false positive signatures; however, further study is required to compare the results of both approaches and their computational performances. INSPIRE method uses the latent variable approach to infer modules of co-expressed genes and the dependencies among the modules from multiple expression datasets that may contain different sets of genes  (Celik et al.
R 2 values of the regression of the 100 metagenes computed in GSE39582 on the gender (A-D), proliferation (E-H) and stromal infiltration (I-L) signals. Different colors denote the various MF algorithms used to compute the 100 metagenes: red for Stabilized ICA, green for ICA', violet for PCA and blue for NMF. The x-axis reports the metagenes in ascending order, while y-axis reports the R 2 value. 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 R 2 values of the regression of the 100 metagenes computed in GSE39582 on the gender (A-D), proliferaEon (E-H) and stromal infiltraEon (I-L) signals.
List of CRC datasets considered in this comparison. For each dataset, the GEO identifier, the number of samples and the number of computed components is here reported Comparison between the performances of Stabilized ICA and cophNMF. The Results of Stabilized ICA and cophNMF in the different tests reported in the results are here summarizedIn the first columns the names of the main results sections are reported. review)is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under Comparison performances in the regression of the three biological signals: gender, proliferation and stromal infiltration by Stabilized ICA, ICA', NMF and PCA. The table reports the values summarized in Figure4: R^2, BIC, AIC, P percentage of components in the community with a significant regression and dimension of the corresponding community.
review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under CC-BY-NC-ND 4. 0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under. Therefore, INSPIRE shares gen-eral objectives of MF-based meta-analysis but signif-icantly differs in terms of methodology. For example, INSPIRE is based on the assumption of Gaussianity in the data distributions and uses disjoint module definitions rather than metagenes, where each gene can contribute to several biological functions. Lastly, here we compared MF methods in application to cancer transcriptomic datasets. However, the suggested approach can be easily extrapolated to other data types (methylomic, proteomic) or other fields of research collecting massive transcriptomic datasets (such as drug screenings).
Biochem. Biophys. Res. Commun. , 430, 1182-1187. Dataset code number of samples number of components GSE23878 35 18 GSE35896 62 31 GSE13067 74 37 GSE33113 90 45 GSE20916 100 50 GSE37892 130 65 GSE13294 155 78 GSE59857 155 78 GSE17536 177 89 GSE41258 187 94 TCGA GA 264 100 GSE2109 277 100 TCGA HI 332 100 GSE39582 566 100 Supplementary Table1: Test Parameter Stabilized ICA cophNMF Control in the number of false discoveries fraction of disconnected nodes in RBH network 6. 70% 12% Reproducibilit y of the identified components number of RBHs 2900 246 clustering coefficient 0. 412 0. 321 modularity 0. 54 0. 32 number of communities 119 8 average size communities 4. 91 4. 8 Score gender 4. 23E-05 0 Score proliferation 1. 92E-05 1. 38826E-06 Score stromal infiltration 3. 19E-06 2. 09813E-07 Presence of a cluster graph-like topology in the RBH network.
No extra-gastrointestinal manifestation was reported. A first screen using a targeted sequencing of 66 genes known to be associated with intestinal disorders did not detect any possibly damaging rare (frequency < 1%) variants in public or inhouse databases  (Uhlig et al, 2014). P2, a boy born to non-consanguineous parents of Jewish Ashkenazi origin, initially presented at the age of 15. 4 years with non-painful swelling of an ankle and hip. Family history revealed psoriatic arthritis in a maternal uncle and ulcerative colitis in the maternal grandmother. P2 was HLA-B27 negative but had antinuclear antibodies (titre 1:320). He was treated with non-steroidal anti-inflammatory drugs without improvement. Six months later, he became acutely sick with vomiting and abdominal pain, biological evidence of severe intestinal inflammation [white cell counts 16 (4-10 × 10 9 /l), neutrophils 12 (2-7.
Identification of heterozygous compound mutations in ALPI by WES Whole-exome sequencing was performed on trios including affected individuals and their unaffected parents. Annotated data were analysed with in-house software. WES of patient 1 (and parents) resulted in > 144× the mean depth of coverage of the exonic targeted bases covered by a minimum of 30 independent reads and identified 101,319 variants. For P2, exome sequencing coverage was 20× or greater for > 85% of the bases targeted and identified 106,869 variants. Polymorphisms reported in public databases with minor allele frequency (MAF) > 1%, and synonymous variants were filtered out. Potential pathogenicity of each protein-coding variant was evaluated using OMIM (Online Mendelian Inheritance in Man), evolutionary conservation and prediction tools (SIFT, PolyPhen-2.
Active ALPI consists of two identically processed subunits (each lacking the first 19 and last 24 aa) bound to the cell surface via a post-translationally added GPI anchor  (Fig 2D). All mutations were designated as disease causing by the majority of in silico predictions tools, with three variants resulting in the substitution of residues highly conserved across species (A97T, A350V and A360; Fig  EV2 ) and one variant (Q439X) introducing a premature stop codon. Moreover, the combined annotation-dependent depletion (CADD) scores of each variant were well above the mutation significance cut-off (MSC) of 3. 13 defined for ALPI (Table  1 ). All mutations were either absent or present in only a heterozygous state at a frequency of less than 0. 001% in the Exome Aggregation Consortium (ExAC) database (Table  1 ;  Lek et al, 2016).
broadinstitute. org/gatk/guide/topic?name=best-practices). Candidate variants were ranked by filtering out common polymorphisms reported in public databases [Human Gene Mutation Database (HGMD), NHLBI GO Exome Sequencing Project (ESP), 1000 Genomes Project, Exome Aggregation Consortium (ExAc), database SNP (dbSNP)] or seen in the 10,681 exomes sequenced at Institut Imagine from families affected with genetic diseases. PolyPhen-2, SIFT and Mutation Taster were used to predict consequences of mutations on protein function. Mutations were next ranked on the basis of the predicted impact of each variant by combined annotation-dependent depletion (CADD), and compared with the mutation significance cut-off (MSC), a gene-level-specific cut-off for CADD scores  (Itan et al, 2016).
Sequence analysis and molecular modelling of ALPI 3D structure The 3D model of human ALPI was built from the crystal structure of human placental alkaline phosphatase (entry code 1ew2;  Le Du et al, 2001). Sequence homology between placental and intestinal alkaline phosphatases was assessed by alignment using the Basic Local Alignment Search Tool, BLAST  (Altschul et al, 1997; Appendix Fig S1). The full-atom model of ALPI was next calculated with the program MODELLER  (Sanchez & Sali, 2000). Conservation analysis was then performed based on our 3D model of ALPI using the fully automated evolutionary approach as implemented on ConSurf server  (Ashkenazy et al, 2016). Finally, visualization, analysis and figure preparation of the 3D model were performed using PyMol software (DeLano, W. L. The PyMOL Molecular Graphics System 2002).
Cell lysis, immunoblotting and flow cytometry Total proteins were solubilized in RIPA buffer (Sigma, Saint Quentin Fallavier, France) supplemented with 1× proteinase inhibitor cocktail mix (Roche, Sigma). Following separation by SDS-PAGE, immunoblotting was performed using Ab against ALPI (ab54776, 1 lg/ml, Abcam, Paris, France) and GAPDH (3683, 1:2,000, Cell Signaling). Surface cell staining of transduced cell lines was performed according to standard flow cytometry protocol using primary Ab against ALPI (ab54776, 1 lg/ml, Abcam), and secondary BV510 goat anti-mouse (Poly4053, 1:100, Sony Biotechnologies, Weybridge, UK) was used. Data were analysed on FACS Canto II (BD Biosciences, Rungis, France) using FlowJo software. assessing p-nitrophenyl phosphate (pNPP) dephosphorylation using Alkaline Phosphatase Assay Kit (ab83369, Abcam) according to the manufacturer's instructions.
Slides were washed and incubated with donkey anti-rabbit IgG H+L-rhodamine conjugate (705-095-147, Jackson ImmunoResearch Waltham, USA) and donkey anti-goat IgG H+L-FITC conjugate  Jackson ImmunoResearch Waltham)  for 2 h at room temperature in darkness. RedDot2 (1:200, Biotium, Hayward, USA) was used at a dilution of 1:200 for nuclear counter staining. These sections were mounted overnight with Vectashield fluorescence mounting medium (Vector Labs, Burlingame, USA). Fluorescent confocal images of normal, IBDs and mutant duodenums or ileums for ALPI, TNAP and E-cadherin double-stained sections were obtained using a Leica confocal laser scanning microscope (model TCS-SPE) and LAS-AF software (Leica Microsystems Leica Microsystems, Wetzlar, Germany). Image processing was carried out with Adobe Photoshop CS3 software.
Acknowledgements This work was supported by  Institutional grants  from  INSERM , by the European grant  ERC-2013-AdG-339407-IMMUNOBIOTA , by the  Investissement d'Avenir  grant  ANR-10-IAHU-01 , by the  Fondation Princesse Grace , by  Fondation Maladies Rares. NCB benefits of an  AP-HP Contrat d'Interface. AMM is supported by  Leona M. and Harry B. Helmsley Charitable Trust  and the  Canadian Institute of Health Research (CIHR).
For more information Online Mendelian Inheritance in Man (OMIM), http://www. omim. org/; UCSC Genome Browser, http://genome. ucsc. edu/; PolyPhen-2, http://genetics. bwh. ha rvard. edu/pph2/index. shtml; SIFT, http://sift. bii. a-star. edu. sg/; Mutation Taster, http://www. mutationtaster. org/; Human Gene Mutation Database, http://www. hgmd. cf. ac. uk/ac/index. php, NHLBI GO Exome Sequencing Project (ESP), http:// evs. gs. washington. edu/EVS/; 1000 Genomes Project, http://www. internationa lgenome. org/data; dbSNP, https://www. ncbi. nlm. nih. gov/projects/SNP/; Exome Aggregation Consortium (ExAC) Browser, http://exac. broadinstitute. org/; The Mutation Significance Cut-off (MSC) Server, http://pec630. rockefeller. edu:8080/ MSC/; Clustal Omega, https://www. ebi. ac. uk/Tools/msa/clustalo/.
Results A new reference assembly of the domestic horse genome. We generated a new reference assembly of the domestic horse using Sanger, short-read, and long-read sequencing data as well as physical chromosome maps. This new reference is derived from the same female Thoroughbred horse, Twilight, that produced EquCab2, and includes her mitochondrial genome. We used both previously published data and newly generated data to generate this reference assembly. The previously published datasets are comprised of the data used to construct EquCab2: Sanger sequencing data, BAC-end pairs 2 , and a physical map containing radiation hybrid and FISH markers  20. For this assembly, we generated shotgun Illumina short reads, Chicago and Hi-C proximity ligation libraries, PacBio long reads, and 10× Chromium linked reads.
As there is no existing software or method for creating an assembly from this combination of data types, we developed a custom pipeline to leverage the strengths of each of these datasets. First, we used the high coverage (45×) and accuracy of Illumina short reads to generate so-called super reads with MaSuRCA  21. We assembled these super reads together with the long and accurate but lower coverage (6. 8×) Sanger reads to create an initial assembly with Celera Assembler  22. We scaffolded this initial assembly with the long insert-size Chicago and Hi-C proximity ligation libraries using the HiRise scaffolder  23. To identify and correct misassemblies, we mapped all physical markers and sequence data, including BAC-end sequences, to the resulting scaffolds. We filled gaps in the corrected scaffolds with PacBio reads, which are longer than Sanger reads, using PBJelly.
3a. In addition, EquCab3 has more sequence assigned to chromosomes, giving reads more total sequence to map to, also demonstrated by Fig. 3a  from the length increase in chr31 from EquCab2 to EquCab3. Finally, EquCab3 improves the characterization of GC-rich regions. The total GC content of EquCab3 is roughly equivalent to that of EquCab2 (both near 41. 6%). However, the guanine-cytosine (GC) fraction of the WGS reads for the two FAANG horses that mapped to EquCab3, but failed to map to EquCab2 is 48. 9%. The GC content for the entire WGS dataset is 41. 8%. This demonstrates an improvement in the characterization of GCrich regions of the equine genome and is largely attributable to the PCR-free library preparations now in common use. We also assessed the quality of EquCab3 by aligning ancient DNA (aDNA) reads to it.
Out of 4104 mammalian universal orthologs, BUSCO found 4092 (99. 7%) as complete orthologs in EquCab3 with 5 fragmented and 7 missing, compared to 4064 (99. 0%) complete orthologs in EquCab2 with 27 fragmented and 13 missing. EquCab3's higher BUSCO score indicates that it is more complete than EquCab2. Comparative Annotation Toolkit (CAT) is a software pipeline that leverages whole-genome alignments, existing annotations, and comparative gene prediction tools to simultaneously annotate multiple genomes, defining orthologous relationships and discovering gene family expansion and contraction  27. CAT also diagnoses assembly quality by investigating the rate of gene model-breaking indels seen in transcript projections from a reference, as well as looking at the rate of transcript projections that map in a disjointed fashion.
, Hercules, CA, USA) prior to sequencing for maximization of the number of clusters in the sequencing flowcell. The PCR-free shotgun library was first sequenced on a MiSeq with v3 reagents to generate paired reads 300 nt in length. The fragment sizes were confirmed by measuring the distribution of insert sizes in the mapped MiSeq dataset. The mode of the distribution was 504 bp with an average insert size of 544. 18 bp. The library was subsequently sequenced on two lanes of the HiSeq2500 for 151 cycles from each end using a TruSeq Rapid SBS Sequencing Kit1 v1. The fastq read files were generated with the bcl2fastq v1. 8. 4 Conversion Software (Illumina, San Diego, CA, USA). PacBio: Ten micrograms of high molecular weight genomic DNA from Twilight was sheared with gTUBES (Covaris) in an Eppendorf ® 5424 centrifuge at 4800 RPM for 2 ×60 s.
1 pipeline with a minimum insert read length set to 1 kb. Reads of insert had a mean of four passes and length of 11,785 bp. From the total initial read count of 5,934,426, we were able to create circular consensus (. ccs) reads totaling 371,943 reads. The remainder of the reads were used to generate an error corrected subreads file using canu  28  (version 1. 0) consisting of 5,562,483 reads. These two datasets were used in the PBJelly runs described below. CHiCago library: We generated a CHiCago library as previously described 23 using blood from Twilight. Hi-C library: We generated a Hi-C library with primary fibroblasts from Twilight using a Hi-C protocol modified such that the chromatin immobilization took place on magnetic beads. We crosslinked the fibroblasts in formaldehyde, and lysed, washed, and resuspended as described by Lieberman-Aiden et al.
The subsetted Illumina reads were used as input into an iterative assembler (mia version 1. 0)  39  , using the horse mitochondrial sequence (NC_001640. 1) as the reference with a slope of 175 and intercept of 100. Sanger data were used to determine the correct number of 8-mer repeats in the control region  40. Sanger reads were trimmed using Figaro (version 1. 05)  41  and aligned to the initial mitochondrial assembly using bwasw (version 0. 7. 12)  42. Alignments were manually inspected by eye using IGV (version 2. 4)  43. Sanger reads that aligned to the control region were extracted, visualized by eye, and compared to the initial mitochondrial assembly. One Sanger read spanned both sides of the control region 8-mer repeats and was used to update the number of 8-mer repeats in the mitochondrial assembly.
The updated mitochondrial assembly sequence was used as the reference sequence for an assembly with mia, using 40 million randomly selected Illumina reads, with a slope of 180 and intercept of 100. The assembly was filtered such that sites not having at least 10-fold coverage and 90% consensus among bases were changed to N. The final assembly had an average coverage of 40×, and 6Ns. The new Twilight mitochondrial sequence has been deposited into GenBank (accession number MH586816). Quality control and assessment. Read mapping: Short-read sequence data generated in the initial phase of the equine FAANG project was mapped to both EquCab2 and EquCab3 for comparison of mapping fractions. These data can be found at the Sequence Read Archive. Both WGS sequence (40×) and RNA-seq (avg 20 M reads/tissue) datasets from eight tissue types for each of two animals were trimmed using TrimGalore (a wrapper for Cutadapt  44  ).
Full details including the project, biosample, and run accession numbers can be found in Supplementary Data 3. For WGS data, the program BWA 36 (version 0. 6. 1) aln module was used to align the reads to the reference. BWA sampe was used to produce a SAM file. SAMtools 45 (version 0. 1. 18) was used to convert from SAM to BAM format. Picard (version 1. 65) FixMateInformation and MarkDuplicates modules were used, followed by GATK  46  (version 1. 5) RealignerTargetCreator, and IndelRealigner (validation_strictness set to LENIENT for each). For the RNA-seq data, the mapping program STAR 47 (version 2. 5. 3a) was used with default parameters except for the following: --readFilesCommand zcat --outSAMtype BAM Sorted-ByCoordinate --outBAMsortingThreadN 16 -outSAMunmapped Within. Polishing: Since Twilight's sequence data and EquCab3 were derived from the same animal, any homozygous differences between the PE data and the reference of which they are a component are likely errors.
The differing bases were likely contributions from the sequence data generated on other platforms used for the assembly such as the Sanger or PacBio data. The errors are either with the reference or with the miscalled/undersampled genotypes derived by the variant discovery software. To evaluate these positions, we performed variant discovery and genotyping with the UnifiedGenotyper using the Twilight PE data, the two FAANG thoroughbreds, and two additional thoroughbreds from Sarkar et al. 12  whose data were downloaded from the Sequence Read Archive (see Data availability) and mapped as described above. The UnifiedGenotyper was used in discovery mode on the cohort. The resulting variant call format file was then parsed with custom java software  48  looking for positions at which the Twilight data produced a homozygous genotype differing from the reference.